<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing with OASIS Tables v3.0 20080202//EN" "journalpub-oasis3.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" xml:lang="en" dtd-version="3.0">
  <front>
    <journal-meta><journal-id journal-id-type="publisher">ACP</journal-id><journal-title-group>
    <journal-title>Atmospheric Chemistry and Physics</journal-title>
    <abbrev-journal-title abbrev-type="publisher">ACP</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Atmos. Chem. Phys.</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1680-7324</issn><publisher>
    <publisher-name>Copernicus Publications</publisher-name>
    <publisher-loc>Göttingen, Germany</publisher-loc>
  </publisher></journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5194/acp-20-8593-2020</article-id><title-group><article-title>Airborne in situ measurements of aerosol size distributions and black carbon across the Indo-Gangetic Plain during SWAAMI–RAWEX</article-title><alt-title>Airborne in situ measurements of aerosol size distributions and BC across the IGP</alt-title>
      </title-group><?xmltex \runningtitle{Airborne in situ measurements of aerosol size distributions and BC across the IGP}?><?xmltex \runningauthor{M. M. Gogoi et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Gogoi</surname><given-names>Mukunda Madhab</given-names></name>
          <email>dr_mukunda@vssc.gov.in</email>
        <ext-link>https://orcid.org/0000-0003-1008-911X</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Jayachandran</surname><given-names>Venugopalan Nair</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-7486-3947</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Vaishya</surname><given-names>Aditya</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-7415-5572</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Babu</surname><given-names>Surendran Nair Suresh</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3 aff4">
          <name><surname>Satheesh</surname><given-names>Sreedharan Krishnakumari</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Moorthy</surname><given-names>Krishnaswamy Krishna</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-7234-3868</ext-link></contrib>
        <aff id="aff1"><label>1</label><institution>Space Physics Laboratory, Vikram Sarabhai Space Centre,
Thiruvananthapuram – 695022, India</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>School of Arts and Sciences &amp; Global Centre for Environment and
Energy,<?xmltex \hack{\break}?> Ahmedabad University, Ahmedabad – 380009, India</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Centre for Atmospheric and Oceanic Sciences, Indian Institute of
Science, Bengaluru – 560012, India</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Divecha Centre for Climate Change, Indian Institute of Science,
Bengaluru – 560012, India</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Mukunda Madhab Gogoi (dr_mukunda@vssc.gov.in)</corresp></author-notes><pub-date><day>22</day><month>July</month><year>2020</year></pub-date>
      
      <volume>20</volume>
      <issue>14</issue>
      <fpage>8593</fpage><lpage>8610</lpage>
      <history>
        <date date-type="received"><day>16</day><month>February</month><year>2020</year></date>
           <date date-type="rev-request"><day>27</day><month>February</month><year>2020</year></date>
           <date date-type="rev-recd"><day>24</day><month>May</month><year>2020</year></date>
           <date date-type="accepted"><day>12</day><month>June</month><year>2020</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2020 </copyright-statement>
        <copyright-year>2020</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://acp.copernicus.org/articles/.html">This article is available from https://acp.copernicus.org/articles/.html</self-uri><self-uri xlink:href="https://acp.copernicus.org/articles/.pdf">The full text article is available as a PDF file from https://acp.copernicus.org/articles/.pdf</self-uri>
      <abstract><title>Abstract</title>
    <p id="d1e148">During the combined South-West Asian Aerosol–Monsoon Interactions and Regional
Aerosol Warming Experiment (SWAAMI–RAWEX), collocated airborne
measurements of aerosol number–size distributions in the size (diameter)
regime 0.5 to 20 <inline-formula><mml:math id="M1" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m and black carbon (BC) mass concentrations were
made across the Indo-Gangetic Plain (IGP), for the first time, from three
distinct locations, just prior to the onset of the Indian summer monsoon. These
measurements provided an east–west transect of region-specific properties of
aerosols as the environment transformed from mostly arid conditions of the
western IGP (represented by Jodhpur, JDR) having dominance of natural
aerosols to the central IGP (represented by Varanasi, VNS) having very high
anthropogenic emissions, to the eastern IGP (represented by the coastal
station Bhubaneswar, BBR) characterized by a mixture of the IGP outflow and
marine aerosols. Despite these, the aerosol size distribution revealed an
increase in coarse mode concentration and coarse mode mass fraction
(fractional contribution to the total aerosol mass) with the increase in
altitude across the entire IGP, especially above the well-mixed region.
Consequently, both the mode radii and geometric mean radii of the size
distributions showed an increase with altitude. However, near the surface
and within the atmospheric boundary layer (ABL), the features were specific
to the different subregions, with the highest coarse mode mass fraction
(<inline-formula><mml:math id="M2" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">MC</mml:mi></mml:msub><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">72</mml:mn></mml:mrow></mml:math></inline-formula> %) in the western IGP and highest
accumulation fraction in the central IGP with the eastern IGP
in between. The elevated coarse mode fraction is attributed to mineral dust
load arising from local production as well as due to advection from the
west. This was further corroborated by data from the Cloud-Aerosol
Transport System (CATS) on board the International Space Station (ISS),
which also revealed that the vertical extent of dust aerosols reached as
high as 5 km during this period. Mass concentrations of BC were moderate
(<inline-formula><mml:math id="M3" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M4" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M5" 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>) with very little altitude variation
up to 3.5 km, except over VNS where very high concentrations were seen near
the surface and within the ABL. The BC-induced atmospheric heating rate was
highest near the surface at VNS (<inline-formula><mml:math id="M6" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.81</mml:mn></mml:mrow></mml:math></inline-formula> K d<inline-formula><mml:math id="M7" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>), while
showing an increasing pattern with altitude at BBR (<inline-formula><mml:math id="M8" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.35</mml:mn></mml:mrow></mml:math></inline-formula> K d<inline-formula><mml:math id="M9" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at the ceiling altitude).</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e258">The Indo-Gangetic Plain (IGP) remains one of the global hot spots of
aerosols. The prevailing high aerosol loading and the relative abundance of
its constituents (being a mixture of natural and anthropogenic species) are
known to show significant seasonality (Gautam et al., 2011; Praveen et al.,
2012; Moorthy et al., 2016; Vaishya et al., 2018; Rana et al., 2019; Brooks
et al., 2019). This arises due to combined effects of the dense population
and the associated anthropogenic and<?pagebreak page8594?> industrial activities, as well as the
loose alluvial soil of this region having vast semiarid and arid
characteristics to the west. A dense network of thermal power plants,
several of them being coal fired, is among the prominent sources of
anthropogenic emissions over the region. This is abetted by the synoptic
meteorology with its strong seasonality (Gautam et al., 2010; Nath et al.,
2018; Singh et al., 2019) and the orography that slopes down from the west
to east bound on the north and south respectively by the Himalayas and the
Aravalli ranges and Bihar Plateau forming a confined channel (Moorthy et al.,
2007; Gogoi et al., 2017). For accurate quantification of the radiative
implications of this complex aerosol system, several concerted studies have
been made using ground-based (Giles et al., 2012; Bansal et al., 2019) and
space-borne measurements (Srivastava, 2016; Mhawish et al., 2017; Kumar et
al., 2018) as well as numerical modeling (Govardhan et al., 2019). However,
most of these studies have uncertainties arising out of the ill-represented
altitude variation in aerosol properties due to sparse measurements. Height-resolved in situ measurements of aerosol properties are indispensable not
only in this regard but also for understanding aerosol–cloud interactions.</p>
      <p id="d1e261">In recent years, a few campaign-mode airborne measurements have been made
over this region to estimate the altitude-resolved properties of aerosols
that are important in aerosol–radiation interactions (Padmakumari et al.,
2013; Babu et al., 2016; Nair et al., 2016; Vaishya et al., 2018; Gogoi et
al., 2019). These include the measurements of aerosol scattering and
absorption coefficients conducted as part of the Regional Aerosol Warming
Experiment (RAWEX; Babu et al., 2016) to delineate the spatiotemporal
variability in the altitude distribution of aerosol single-scattering albedo
(SSA) across the IGP during winter and pre-monsoon seasons and aerosol and
cloud parameter measurements conducted as part of the Cloud Aerosol
Interaction and Precipitation Enhancement Experiment (CAIPEEX; Kulkarni et
al., 2012). Some studies have reported significant contribution of dust
and black carbon (BC) to the elevated aerosol load (Praveen et al., 2012; Kedia et al.,
2014; Pandey et al., 2017; Li et al., 2016) and their potential role to act
as ice nuclei (IN; Padmakumari et al., 2013). However, despite its importance in
radiative interactions and cloud condensation nuclei (CCN) activation, the
altitude-resolved measurements of aerosol size distribution are extremely
sparse, or nonexistent, especially just prior to the onset of the Indian
summer monsoon, when the sources of aerosols, their mixing and transport
pathways are all complex. The information on aerosol size distribution is
important for accurately describing the phase function, which describes the
angular variation in the scattered intensity. The knowledge of its vertical
variation would thus improve the accuracy of aerosol radiative forcing
estimation and hence heating rates. Such information is virtually
nonexistent over this region. Further, the knowledge of the variation in
size distribution with altitude would be useful in better understanding the
aerosol–cloud interactions and CCN characteristics during the evolving and
active phases of the Indian monsoon. This was part of the important information sought under SWAAMI–RAWEX
(<uri>https://gtr.ukri.org/projects?ref=NE/L013886/1</uri>, last access: 9 July 2020 and
<uri>http://spl.gov.in/SPL/index.php/arfs-research/field-campaigns/asfasf</uri>, last access: 9 July 2020) –
a joint India–UK field experiment involving airborne measurements using
Indian and UK aircrafts during different phases of the Indian monsoon, starting
from just prior to the onset of monsoon (i.e., in the beginning of June).</p>
      <p id="d1e270">During this campaign, vertical profiles of various aerosol parameters have
been measured using an instrumented aircraft from three base stations
– representing the western, central and eastern end of the IGP – from 1 to 20 June 2016. Some important
results on the optical and CCN characteristics are already reported (Vaishya
et al., 2018; Jayachandran et al., 2020). In the present study, we have
examined the vertical profiles of aerosol number–size distributions in the
size (diameter) regime 0.5 to 20 <inline-formula><mml:math id="M10" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m and black carbon (BC) mass
concentrations. The results are presented and discussed in light of
other supporting information.</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Experimental details and database</title>
<sec id="Ch1.S2.SS1">
  <label>2.1</label><title>Study region and flight details</title>
      <p id="d1e296">The base stations (Fig. 1), from where the aircraft operations were
carried out, represented distinct regions of the IGP. Jodhpur (JDR;
26.25<inline-formula><mml:math id="M11" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 73.04<inline-formula><mml:math id="M12" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) in the western IGP is an arid/semiarid region with low urban activities, lying downwind of the Great Indian
Desert to its west (JDR has a population density of 161 km<inline-formula><mml:math id="M13" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>). Varanasi
(VNS; 25.44<inline-formula><mml:math id="M14" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 82.85<inline-formula><mml:math id="M15" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) in the central IGP is located
downwind of Jodhpur, characterized by extensive anthropogenic activities
(automobiles, small and large-scale industries and thermal power plants, and
widespread agricultural activities) by its dense population (density 2399 km<inline-formula><mml:math id="M16" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>). Bhubaneswar (BBR; 20.25<inline-formula><mml:math id="M17" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 85.81<inline-formula><mml:math id="M18" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) is
an urban location in the eastern IGP (population density of 2131 km<inline-formula><mml:math id="M19" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>)
and experiences the influence of the marine aerosol component from the
Bay of Bengal (<inline-formula><mml:math id="M20" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">50</mml:mn></mml:mrow></mml:math></inline-formula> km away from the base station) in addition
to the influence of IGP outflow and local aerosol sources from nearby
thermal (coal-based) power plants, mining and fertilizer-based industries,
etc. (Panda and Das, 2016). The northwestern part of India has an undulating
topography, due to which monsoon currents lose moisture while crossing the
western mountain ranges (Aravalli) and resulting in dry arid regions (Moorthy
et al., 2007). Strong dust-raising winds are a common feature of the IGP in
general and its western parts in particular from April to July (Banerjee
et al., 2019). In the central IGP, VNS and its environs hold largely even
topography, where the Ganges is the principal river. In the eastern IGP, BBR
is topographically made up of western<?pagebreak page8595?> uplands and eastern lowlands, with
hillocks in the western and northern parts. These base stations thus
provided a west–east cross section of the highly aerosol-laden IGP, where
the aerosol characteristics are known to change longitudinally. The spatial
map of aerosol optical depth (AOD) at 550 nm (Fig. 1) clearly shows the existence of higher
aerosol loading (AOD <inline-formula><mml:math id="M21" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">0.5</mml:mn></mml:mrow></mml:math></inline-formula>) over the observational site during
the study period.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><?xmltex \currentcnt{1}?><label>Figure 1</label><caption><p id="d1e412">Three distinct base stations: (i) Jodhpur (JDR; 26.25<inline-formula><mml:math id="M22" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 73.04<inline-formula><mml:math id="M23" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) in the western IGP, (ii) Varanasi (VNS;
25.44<inline-formula><mml:math id="M24" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 82.85<inline-formula><mml:math id="M25" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) in the central IGP and (iii) Bhubaneswar (BBR; 20.25<inline-formula><mml:math id="M26" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 85.81<inline-formula><mml:math id="M27" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) in the eastern
coastal IGP, from where the aircraft measurements were conducted. The
spatial map of AOD at 550 nm obtained from the MODIS sensor
(MOD08_D3_6.1, Dark Target and Deep Blue
combined mean) on board the Terra satellite during the study period (1–20 June
2016) is shown in the background.</p></caption>
          <?xmltex \igopts{width=213.395669pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f01.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><?xmltex \currentcnt{2}?><label>Figure 2</label><caption><p id="d1e478"><bold>(a)</bold> The onset (actual) of the SW monsoon at different parts of India, shown by the yellow and pink (solid) lines. The horizontal and vertical flight paths during each of the flights at <bold>(b)</bold> Bhubaneswar (BBR), <bold>(c)</bold> Varanasi (VNS) and <bold>(d)</bold> Jodhpur (JDR).</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f02.png"/>

        </fig>

      <p id="d1e499">Figure 2a shows the actual dates of onset of the monsoon at different parts
of India in 2016. As can be seen from the figure, despite a delayed onset at
the southern tip of India, the monsoon advanced fast into the central/northern
parts of India. Yet, all the flights from the respective base
stations were completed ahead of the start of the monsoon to that station. At
the eastern IGP, the aircraft flights were made from BBR before the onset
of monsoon over India; at VNS, the flights were conducted while monsoon
advanced only to the central peninsula. The final set of flights was
conducted at JDR when the monsoon covered most of the central and eastern
part of India, but had yet to progress towards the northwestern parts.</p>
      <p id="d1e502">From each of the base stations, four to five flights were carried out on
successive days in different horizontal directions about the station, as
shown by the ground projections (horizontal lines in Fig. 2a), with a view
to obtain an average subregional representation in the shortest time
possible. During each of the flights, measurements were made at six discrete
levels following a staircase configuration as shown in Fig. 2 (for BBR,
VNS and JDR, respectively). Accordingly, the aircraft initially climbed to
the base/ceiling altitude, stabilized and made a horizontal flight along the
projected track for about 30 min before climbing up (descending down) to the
next higher (lower) levels and stabilizing. This procedure was repeated for
all levels (<inline-formula><mml:math id="M28" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.5</mml:mn></mml:mrow></mml:math></inline-formula>, 1, 1.5, 2, 2.5 and 3 km a.g.l.). The ceiling altitude was restricted to 3.5 km based on the
unpressurized mode of operation of the aircraft. All the flights were
carried out around midday since thorough vertical mixing is established by
the daytime convective boundary layer eddies.</p>
</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Onboard instrumentation</title>
      <p id="d1e523">The measurements were carried out aboard the instrumented aircraft
(Beechcraft 200) fitted with an iso-kinetic inlet, mounted (front facing) at
the bottom of the fuselage for aspirating ambient aerosols as detailed in
earlier papers (Babu et al., 2016; Vaishya et al., 2018; Gogoi et al.,
2019). A constant volumetric flow of 70 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> was maintained using an external
pump connected to the main inlet assembly, which provided iso-kinetic flow
for the average speed of 300 km h<inline-formula><mml:math id="M30" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> maintained by the aircraft during the
entire campaign. The efficiency of this inlet system has already been proven
in several previous campaigns (Babu et al., 2016; Nair et al., 2016; Gogoi
et al., 2019).</p>
<sec id="Ch1.S2.SS2.SSS1">
  <label>2.2.1</label><title>Measurement of aerosol size distribution</title>
      <p id="d1e557">A factory-calibrated, aerodynamic particle sizer (APS) spectrometer (TSI,
model 3321) is used for the measurement of aerosol size distribution. It
measures size-resolved number concentration of the ambient aerosols in the
size range from 0.5 to 20 <inline-formula><mml:math id="M31" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m, over 52 channels spaced equally in
logarithmic size bins, at a sampling frequency of 1 min. Aerosol
particles in this size range are most important in influencing the optical
(scattering and extinction) and CCN and IN characteristics.</p>
      <p id="d1e568">The APS measures the concentration of particles in terms of their
aerodynamic diameters by comparing the velocity of a particle (controlled by
an accelerating flow field) to that of a unit density sphere having the same
velocity. Particle velocity is estimated from the measurement of time of
flight (Mitchell and Nagel, 1999). In the present study a sheath flow at 4 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> (liters per minute) was maintained against the sample flow of 1 L min<inline-formula><mml:math id="M33" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The
instrument automatically adjusts the flow rates with changes in ambient
pressure to maintain the specified flow rates. Occasionally, when the
aircraft passed through clouds, the aerosol number concentration shot up
from the otherwise stable values. Such outliers are removed following
2<inline-formula><mml:math id="M34" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> criteria, wherein data points at a particular level lying outside
2<inline-formula><mml:math id="M35" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> values of the level average were removed. Such
screened-out points were <inline-formula><mml:math id="M36" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:math></inline-formula> % of the total. The consistency in
the flow was periodically checked each time, before start of measurements
from the new base station. Similarly, the optical components and tubing of
the system were cleaned immediately after moving to a new base station.</p>
      <?pagebreak page8596?><p id="d1e619">The TSI APS (3321) is suitable for operating at 10 % to 90 % RH
(non-condensing) and 10–40 <inline-formula><mml:math id="M37" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C ambient temperature. For BBR, it is
likely that aerosols grew under high-RH conditions but might have also
shrunk due to higher instrument temperature compared to ambient conditions. However,
more controlled laboratory experiments are required to ascertain the
response of the APS to hygroscopic growth of particles.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS2">
  <label>2.2.2</label><title>Measurement of black carbon aerosols</title>
      <p id="d1e639">Mass concentration of ambient BC aerosols was estimated using a seven-channel
aethalometer (model AE33, Magee Scientific, USA), which measures the
attenuation of light that passes through the aerosol-laden filter at
wavelengths of 370, 470, 520, 590, 660, 880 and 950 nm. The loading (or
shadowing) effect arising out of the successive deposition of aerosols in
the filter media is automatically compensated for in real time in the
new-generation Aethalometer, while the multiple scattering effects were
minimized by using advanced filter tape material (Drinovec et al.,2015). In
the present study, BC mass concentrations were obtained at 1 min intervals
by operating the Aethalometer at 50 % of the maximum attenuation and a
standard mass flow rate of 2 L min<inline-formula><mml:math id="M38" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> under standard temperature (<inline-formula><mml:math id="M39" display="inline"><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">O</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, 293 K)
and pressure (<inline-formula><mml:math id="M40" display="inline"><mml:mrow><mml:msub><mml:mi>P</mml:mi><mml:mi mathvariant="normal">O</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, 1013 hPa). As the unpressurized aircraft climbed
higher, the instrument experienced ambient pressure (<inline-formula><mml:math id="M41" display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) and temperature (<inline-formula><mml:math id="M42" display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>).
In order to maintain the set mass flow, the pumping speed of the instrument
was automatically increased (through an internal program) to aspire more volume
of air. However, the volume of air aspirated at ambient pressure and
temperature must be corrected to standard atmospheric conditions for
the actual estimate of BC (Moorthy et al., 2004). Thus, the actual volume of
air aspirated by the Aethalometer at different atmospheric levels is
              <disp-formula id="Ch1.Ex1"><mml:math id="M43" display="block"><mml:mrow><mml:mi>V</mml:mi><mml:mo>=</mml:mo><mml:msub><mml:mi>V</mml:mi><mml:mi mathvariant="normal">O</mml:mi></mml:msub><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mrow><mml:msub><mml:mi>P</mml:mi><mml:mi mathvariant="normal">O</mml:mi></mml:msub><mml:mi>T</mml:mi></mml:mrow><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">O</mml:mi></mml:msub></mml:mrow></mml:mfrac></mml:mstyle><mml:mo>.</mml:mo></mml:mrow></mml:math></disp-formula>
            Thus, true BC mass concentration (<inline-formula><mml:math id="M44" display="inline"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) is
              <disp-formula id="Ch1.E1" content-type="numbered"><label>1</label><mml:math id="M45" display="block"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:msubsup><mml:mi>M</mml:mi><mml:mi mathvariant="normal">BC</mml:mi><mml:mo>∗</mml:mo></mml:msubsup><mml:msup><mml:mfenced open="[" close="]"><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mrow><mml:msub><mml:mi>P</mml:mi><mml:mi mathvariant="normal">O</mml:mi></mml:msub><mml:mi>T</mml:mi></mml:mrow><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">O</mml:mi></mml:msub></mml:mrow></mml:mfrac></mml:mstyle></mml:mfenced><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>.</mml:mo></mml:mrow></mml:math></disp-formula>
            Here, <inline-formula><mml:math id="M46" display="inline"><mml:mrow><mml:msubsup><mml:mi>M</mml:mi><mml:mi mathvariant="normal">BC</mml:mi><mml:mo>∗</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> is the instrument-measured raw mass concentration of
BC at ambient pressure and temperature. Details of the aethalometer
principle, operation, uncertainty involved and error budget are reported in earlier literature (Weingartner et al., 2003; Arnott et al., 2005;
Gogoi et al., 2017). In general, the instrumental uncertainty ranges from
50 % at 0.05 <inline-formula><mml:math id="M47" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M48" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> to 6 % at 1 <inline-formula><mml:math id="M49" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M50" 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> (Corrigan et al., 2006), and the uncertainty in the estimation of
absorption coefficients is around 10 % (Vaishya et al., 2018).</p>
</sec>
</sec>
<sec id="Ch1.S2.SS3">
  <label>2.3</label><title>General synoptic meteorology during the campaign</title>
      <p id="d1e847">The meteorological conditions across the IGP during the campaign period were
generally hot (surface temperature, <inline-formula><mml:math id="M51" display="inline"><mml:mrow><mml:mi>T</mml:mi><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">34.7</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">2.8</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M52" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C at JDR, <inline-formula><mml:math id="M53" display="inline"><mml:mrow><mml:mn mathvariant="normal">39</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">1.9</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M54" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C at VNS and <inline-formula><mml:math id="M55" display="inline"><mml:mrow><mml:mn mathvariant="normal">32.8</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">3.6</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M56" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C
at BBR at the time of flight takeoff), with low to moderate relative
humidity (RH) at JDR (RH <inline-formula><mml:math id="M57" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">40</mml:mn></mml:mrow></mml:math></inline-formula> %) and VNS (RH <inline-formula><mml:math id="M58" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">60</mml:mn></mml:mrow></mml:math></inline-formula> %). The value of RH at BBR was relatively higher (as high as 80 %)
associated with its coastal proximity, in addition to the influence of mild
pre-monsoon rainfall during<?pagebreak page8597?> the first (1 June 2016; light rain during
noon), third (3 June 2016; heavy rain <inline-formula><mml:math id="M59" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">60</mml:mn></mml:mrow></mml:math></inline-formula> mm in the night)
and fourth (4 June 2016; light rain in the morning and during noon) days of
observations. The records of <inline-formula><mml:math id="M60" display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula> and RH were obtained from the sensors
on board the aircraft, while the rainfall data were obtained from the airport
meteorological department at BBR.</p>
</sec>
<sec id="Ch1.S2.SS4">
  <label>2.4</label><title>Supporting data</title>
      <p id="d1e963">Supporting data used in this study include aerosol backscattering
coefficients and depolarization ratio measured by the Cloud-Aerosol Transport System (CATS) aboard the
International Space Station (ISS). The CATS is comprised of an elastic
backscatter lidar consisting of two high-repetition-rate (4–5 kHz), low-energy (1–2 mJ) Nd:YVO<inline-formula><mml:math id="M61" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:math></inline-formula> lasers operating at three wavelengths (1064,
532 and 355 nm). The receiver subsystem consists of a 60 cm telescope
having a 110 <inline-formula><mml:math id="M62" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">rad</mml:mi></mml:mrow></mml:math></inline-formula> field of view, photon-counting detectors and
associated control electronics (Yorks et al., 2014, 2016). As the altitude of
ISS orbit is about 405 km (51<inline-formula><mml:math id="M63" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> inclination), CATS provides a
comprehensive coverage of the tropics and midlatitudes, with nearly a
3 d repeat cycle. Level 2 data of CATS
(<uri>https://cats.gsfc.nasa.gov/data/</uri>, last access: 9 July 2020) are used (Lee et al., 2019) in the
present study, which provide the geophysical parameters, such as the
vertical feature mask, profiles of cloud and aerosol properties (i.e.,
extinction, particle backscatter), and layer-integrated parameters (i.e.,
lidar ratio, optical depth). In addition, types of aerosols are also derived
based on CATS aerosol typing algorithms where eight aerosol types (in CATS mode 7.1)
are identified: volcanic, dust, dust mixture, clean/background, polluted
marine, marine, polluted continental and smoke. Incorporating the
information of backscatter color ratio (<inline-formula><mml:math id="M64" display="inline"><mml:mrow><mml:mn mathvariant="normal">1064</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">532</mml:mn></mml:mrow></mml:math></inline-formula> nm) and spectral
depolarization (ratio of perpendicular to parallel backscatter)
ratio (<inline-formula><mml:math id="M65" display="inline"><mml:mrow><mml:mn mathvariant="normal">1064</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">532</mml:mn></mml:mrow></mml:math></inline-formula> nm), CATS operating mode 7.1 provides the characteristics of aerosol regimes
(Yorks et al., 2016) as given in Table 1.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><?xmltex \currentcnt{1}?><label>Table 1</label><caption><p id="d1e1025">Classification of aerosol types for CATS operating mode 7.1 (Yorks et al.,
2016).</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="4">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="left"/>
     <oasis:colspec colnum="4" colname="col4" align="left"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Aerosol type</oasis:entry>
         <oasis:entry colname="col2">Aerosol feature</oasis:entry>
         <oasis:entry colname="col3">Depolarization</oasis:entry>
         <oasis:entry colname="col4">Color ratio</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">base</oasis:entry>
         <oasis:entry colname="col3">ratio (<inline-formula><mml:math id="M66" display="inline"><mml:mrow><mml:msubsup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">1064</mml:mn><mml:mo>′</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col4">(<inline-formula><mml:math id="M67" display="inline"><mml:mrow><mml:msubsup><mml:mi mathvariant="italic">γ</mml:mi><mml:mn mathvariant="normal">1064</mml:mn><mml:mo>′</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>)</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">Volcanic</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M68" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> km</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Dust</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M69" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> km</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M70" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">0.3</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Dust mixture</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M71" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> km</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M72" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.2</mml:mn><mml:mo>&gt;</mml:mo><mml:mi mathvariant="italic">δ</mml:mi><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">0.3</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Clean/background</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M73" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> km</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M74" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.0005</mml:mn></mml:mrow></mml:math></inline-formula> sr<inline-formula><mml:math id="M75" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Polluted marine</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M76" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> km</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M77" display="inline"><mml:mrow><mml:msubsup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">1064</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>/</mml:mo><mml:msubsup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">532</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">50</mml:mn></mml:mrow></mml:math></inline-formula> %</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M78" display="inline"><mml:mrow><mml:msubsup><mml:mi mathvariant="italic">γ</mml:mi><mml:mn mathvariant="normal">532</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>/</mml:mo><mml:msubsup><mml:mi mathvariant="italic">γ</mml:mi><mml:mn mathvariant="normal">1064</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">1.75</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Marine</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M79" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> km</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M80" display="inline"><mml:mrow><mml:msubsup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">1064</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>/</mml:mo><mml:msubsup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">532</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">50</mml:mn></mml:mrow></mml:math></inline-formula> %</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M81" display="inline"><mml:mrow><mml:msubsup><mml:mi mathvariant="italic">γ</mml:mi><mml:mn mathvariant="normal">532</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>/</mml:mo><mml:msubsup><mml:mi mathvariant="italic">γ</mml:mi><mml:mn mathvariant="normal">1064</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">1.75</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Polluted continental</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M82" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> km</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M83" display="inline"><mml:mrow><mml:msubsup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">1064</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>/</mml:mo><mml:msubsup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">532</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">50</mml:mn></mml:mrow></mml:math></inline-formula> %</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M84" display="inline"><mml:mrow><mml:msubsup><mml:mi mathvariant="italic">γ</mml:mi><mml:mn mathvariant="normal">532</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>/</mml:mo><mml:msubsup><mml:mi mathvariant="italic">γ</mml:mi><mml:mn mathvariant="normal">1064</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">1.75</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Smoke</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M85" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> km</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M86" display="inline"><mml:mrow><mml:msubsup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">1064</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>/</mml:mo><mml:msubsup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">532</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">50</mml:mn></mml:mrow></mml:math></inline-formula> %</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M87" display="inline"><mml:mrow><mml:msubsup><mml:mi mathvariant="italic">γ</mml:mi><mml:mn mathvariant="normal">532</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>/</mml:mo><mml:msubsup><mml:mi mathvariant="italic">γ</mml:mi><mml:mn mathvariant="normal">1064</mml:mn><mml:mo>′</mml:mo></mml:msubsup><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">1.75</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

</sec>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>Results and discussion</title>
<sec id="Ch1.S3.SS1">
  <label>3.1</label><title>Aerosol number size distributions</title>
      <p id="d1e1550">Aerosol number size distributions [<inline-formula><mml:math id="M88" display="inline"><mml:mrow><mml:mi mathvariant="normal">d</mml:mi><mml:mo>(</mml:mo><mml:mi>N</mml:mi><mml:mo>)</mml:mo><mml:mo>/</mml:mo><mml:mi mathvariant="normal">d</mml:mi><mml:mo>(</mml:mo><mml:mi>log⁡</mml:mi><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">p</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>], representative of each
of the three subregions of IGP are presented in Fig. 3; the panels from left
to right represent the subregions JDR, VNS and BBR, from the west to
east IGP. Three distributions are shown for each station, representative of
(i) near the surface with proximity to emission sources (600 m a.g.l.), (ii) in
the upper atmospheric boundary layer (ABL, 2000 m a.g.l.) and (iii) in the free troposphere (3100 m a.g.l.)
following the mean ABL heights (<inline-formula><mml:math id="M89" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.3</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.5</mml:mn></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M90" display="inline"><mml:mrow><mml:mn mathvariant="normal">2.3</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.5</mml:mn></mml:mrow></mml:math></inline-formula> and
<inline-formula><mml:math id="M91" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.4</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.2</mml:mn></mml:mrow></mml:math></inline-formula> km for JDR, VNS and BBR respectively; Vaishya et al., 2018)
at local noon time. Aerosol number concentrations below 0.542 <inline-formula><mml:math id="M92" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m are not
size-classified and represented as a single count (between 0.3 and 0.542 <inline-formula><mml:math id="M93" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m); they are shown as a function of altitude in Fig. 4a. The figures
clearly reveal that at all altitudes above different stations, the size
distributions are consistently bimodal, with a prominent accumulation mode
(<inline-formula><mml:math id="M94" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M95" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) and a weaker secondary mode (<inline-formula><mml:math id="M96" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M97" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m). The concentration of particles in the unclassified size regime (below
0.542 <inline-formula><mml:math id="M98" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) showed a gradual decrease with increase in altitude at all
stations and a spatial distinctiveness with the highest near-surface
concentration in the central IGP (most anthropogenically impacted subregion
of the IGP) depicting sharper altitude variation compared with the other two
subregions.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><?xmltex \currentcnt{3}?><label>Figure 3</label><caption><p id="d1e1681">Aerosol number size distributions (mean profiles averaged for all
the days) at three distinct altitudes of JDR, VNS and BBR, representative of
(i) near the surface (600 m a.g.l.) having proximity to emission
sources, (ii) the upper ABL (2000 m a.g.l.) and (iii) the
free troposphere (3100 m). Vertical bars over the points are the ensemble
standard deviations. Individual size distributions at different heights of
<inline-formula><mml:math id="M99" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">500</mml:mn></mml:mrow></mml:math></inline-formula> m intervals are given in Fig. S1 in the Supplement.</p></caption>
          <?xmltex \igopts{width=327.206693pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f03.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><?xmltex \currentcnt{4}?><label>Figure 4</label><caption><p id="d1e1702">Vertical profiles of aerosol number concentrations in the <bold>(a)</bold> unclassified size range of APS (between 0.3 and 0.523 <inline-formula><mml:math id="M100" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m); <bold>(b)</bold> accumulation (<inline-formula><mml:math id="M101" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">AC</mml:mi></mml:msub><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M102" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) and coarse (<inline-formula><mml:math id="M103" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:msub><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M104" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) mode size range.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f04.png"/>

        </fig>

      <p id="d1e1773">As is well-established that during the pre-monsoon and prior to the onset of the
monsoon, both the natural and anthropogenic aerosol species coexist in large
abundance over the IGP. We examined in Fig. 4b, the altitude profiles of
accumulation mode aerosols (<inline-formula><mml:math id="M105" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">AC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, concentration below 1 <inline-formula><mml:math id="M106" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m), which
are mostly attributed to anthropogenic origin and coarse mode aerosols
(above 1 <inline-formula><mml:math id="M107" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m), which are mostly of natural origin. <inline-formula><mml:math id="M108" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">AC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> showed only
weak altitudinal dependence above 1 km at all the subregions; though at
VNS, there was a sharp increase in the concentration below 1 km, obviously
due to source proximity. This feature is seen in Fig. 4a also. This
observation is supported by the collocated measurements of aerosol total
number concentrations (<inline-formula><mml:math id="M109" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">T</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) as measured by a condensation nuclei (CN)
counter aboard the aircraft (Jayachandran et al., 2020) in the size range
above 2.5 nm, showing the highest values of <inline-formula><mml:math id="M110" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">T</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> in the entire altitude range
of measurements over VNS. On the other hand, the vertical profiles of coarse
mode aerosol concentrations (<inline-formula><mml:math id="M111" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) showed significantly large abundance
over the western IGP (arid/semiarid regions) represented by JDR, similar
to the springtime observations reported by Gogoi et al. (2019).</p>
      <p id="d1e1848">These observations are also in line with the reported values of dust
fractions (Vaishya et al., 2018) during the same campaign, showing the
enhancement of dust fraction from 10 % to 20 % at 300 m to more than 90 %
above 2 km altitude at JDR, while the smallest dust faction (<inline-formula><mml:math id="M112" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> %)
was observed at BBR in the entire altitude range. Over the central IGP,
synoptic wind-driven desert dust aerosols lead to elevated layers of
aerosols having a higher dust fraction (<inline-formula><mml:math id="M113" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">50</mml:mn></mml:mrow></mml:math></inline-formula> %). However, it
should be noted that dust over the central IGP is more absorbing in nature
because of its mixing with other anthropogenic emissions (such as BC;
Vaishya et al., 2018), while that over western IGP is rather pristine in
nature. Thus, quantification of the absolute magnitude of coarse mode
aerosol concentrations is very important to understand the significance of
elevated aerosol load on radiative perturbations. The increasing
concentration of coarse mode particles with the increase in altitude across
the entire IGP is another interesting feature in the present study, which is
most conspicuous at the central IGP and least at the west, implying their
increasing role at higher altitude, probably due to the lofted regional dust
and advected mineral dust from west Asian regions.</p>
      <p id="d1e1871">With the goal of quantifying this, the size distribution spectra are averaged
for each altitude level and for each station. From these spectra, the
geometrical mean diameter (<inline-formula><mml:math id="M114" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) is estimated as a function of altitude, using
the following equation:
            <disp-formula id="Ch1.E2" content-type="numbered"><label>2</label><mml:math id="M115" display="block"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mi>exp⁡</mml:mi><mml:mfenced close="]" open="["><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mrow><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mi>l</mml:mi><mml:mi>u</mml:mi></mml:munderover><mml:msub><mml:mi>n</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mi>ln⁡</mml:mi><mml:mo>(</mml:mo><mml:msub><mml:mi>D</mml:mi><mml:mrow><mml:mi mathvariant="normal">p</mml:mi><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>)</mml:mo></mml:mrow><mml:mi>N</mml:mi></mml:mfrac></mml:mstyle></mml:mfenced><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>
          where <inline-formula><mml:math id="M116" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mrow><mml:mi mathvariant="normal">p</mml:mi><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mfenced open="(" close=")"><mml:mrow><mml:mo>=</mml:mo><mml:mo>√</mml:mo><mml:mfenced close=")" open="("><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>×</mml:mo><mml:msub><mml:mi>D</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:mfenced></mml:mrow></mml:mfenced></mml:mrow></mml:math></inline-formula>
denotes the geometric midpoint of each channel of the APS, <inline-formula><mml:math id="M117" display="inline"><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> is the
particle concentration in the <inline-formula><mml:math id="M118" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>th channel and <inline-formula><mml:math id="M119" display="inline"><mml:mrow><mml:mi>N</mml:mi><mml:mo>=</mml:mo><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mi>l</mml:mi><mml:mi>u</mml:mi></mml:munderover><mml:msub><mml:mi>n</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> is the total concentration. Accordingly, <inline-formula><mml:math id="M120" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> of a spectrum of particles is
the 50 % probability point of an equivalent diameter having half of the
particle concentrations larger than this size and the remaining half below. The vertical profiles of <inline-formula><mml:math id="M121" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> and mode (<inline-formula><mml:math id="M122" display="inline"><mml:mrow><mml:mo>=</mml:mo><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">p</mml:mi></mml:msub><mml:mo>(</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mo>max⁡</mml:mo></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>) of the distributions are shown in Fig. 5. It clearly
shows the increase in the coarse mode fraction in the size distribution,
with both the mode and <inline-formula><mml:math id="M123" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> showing a steady increase with altitude,
especially <inline-formula><mml:math id="M124" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>. The rate of increase in <inline-formula><mml:math id="M125" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> with altitude increases from west
to east across the IGP, with the highest values in BBR (Fig. 5b). In the
central IGP where the mixed aerosol type prevails, the increase in <inline-formula><mml:math id="M126" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> within the
ABL is rather weak, but in the free troposphere it increases more sharply
probably due to the faster decrease in the accumulation mode concentration
(Fig. 4) or the prevalence of advected dust at higher altitudes or both.
The previous observations reveal the nonuniform distribution of
dust and anthropogenic sources of aerosols. Nearly steady values of <inline-formula><mml:math id="M127" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> in the entire column at JDR are attributed to the strong convective mixing
of coarse mode dust aerosols up to the lower free-tropospheric region. On
the other hand,<?pagebreak page8599?> altitude variation in accumulation and coarse mode aerosols
is relatively more variable at BBR and VNS, compared to that at JDR
(Fig. 4b) as indicated by the profiles of <inline-formula><mml:math id="M128" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5"><?xmltex \currentcnt{5}?><label>Figure 5</label><caption><p id="d1e2127">Vertical profiles of <bold>(a)</bold> mode and <bold>(b)</bold> geometric mean diameters (<inline-formula><mml:math id="M129" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) of aerosol number size distributions at different heights above the
ground level, indicating the change in the pattern of distribution with
altitude and from the western to the eastern part of the IGP.</p></caption>
          <?xmltex \igopts{width=227.622047pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f05.png"/>

        </fig>

      <p id="d1e2153">Apart from the number-weighted expression of aerosol size distributions, the
mass-weighted distributions carry useful information for quantifying
regional distinctiveness of the dominance of coarse mode particles. Even
though the fine mode aerosols are extremely numerous in the atmosphere and
important for microphysical processes, they represent only a very small
proportion of total particle mass, whereas coarse mode particles, even
though far less numerous, have significant volume. In simple terms,
particle number concentrations are dominant in the fine mode (<inline-formula><mml:math id="M130" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.1</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M131" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m), the surface area is predominantly in the accumulation mode (0.1 to
1 <inline-formula><mml:math id="M132" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) and the volume, and hence mass, is divided between the
accumulation mode and coarse particle mode. In the present study, since the
size range of particle counts is confined in the accumulation and coarse
mode regimes (between 0.5 and 20 <inline-formula><mml:math id="M133" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m), a quantitative picture of
aerosol mass concentrations is obtained by assuming a uniform density equal
to 2 g cm<inline-formula><mml:math id="M134" 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> following Moorthy et al. (1998) and Pillai and Moorthy (2001).
Since the size-resolved particle densities are not known, we did not use
effective density (mass–mobility relationship defined as the mass of the
particle divided by its mobility equivalent volume) of particles to
calculate the mean particle mass size distributions.</p>
      <p id="d1e2203">Figure 6a shows the altitudinal variation in coarse mode aerosol mass
concentrations over all the observational sites, along with the values of
coarse mode mass fractions (<inline-formula><mml:math id="M135" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">MC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>). Over VNS and JDR, consistently higher
values of <inline-formula><mml:math id="M136" display="inline"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> were seen in the entire altitude range. This is in line
with the higher values of coarse mode aerosol concentrations (<inline-formula><mml:math id="M137" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) at
these sites, JDR being the highest. On the other hand, the values of <inline-formula><mml:math id="M138" display="inline"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> at BBR decreased significantly from the surface to the lower free-tropospheric
region. The higher values <inline-formula><mml:math id="M139" display="inline"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> observed near the surface at BBR can be
attributed to the influence of local sea-salt aerosols, however not
affecting the values of <inline-formula><mml:math id="M140" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, due to the abundance of accumulation mode
aerosols over this site.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6"><?xmltex \currentcnt{6}?><label>Figure 6</label><caption><p id="d1e2275">Vertical profiles (mean and standard deviations) of <bold>(a)</bold> coarse mode aerosol mass concentrations (<inline-formula><mml:math id="M141" display="inline"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>); the values are derived from the
aerosol number concentrations at different size bins, assuming a density of
2 g cm<inline-formula><mml:math id="M142" 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> and <bold>(b)</bold> aerosol coarse mode fractions (<inline-formula><mml:math id="M143" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">MC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) at different
locations.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f06.png"/>

        </fig>

      <p id="d1e2324">Similar to that of <inline-formula><mml:math id="M144" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M145" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">MC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> showed (Fig. 6b) gradually
increasing values with altitude at all the locations. The high values of
coarse mode mass fraction and an increasing trend with altitude are
indicative of the role of upper-level transport of dust from the western
desert region, in addition to those contributed locally due to thermal
convective processes. Compared to the other two stations, the highest value of
<inline-formula><mml:math id="M146" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">MC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> (<inline-formula><mml:math id="M147" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">70</mml:mn></mml:mrow></mml:math></inline-formula> %) near the surface was seen at JDR
indicating the role of the arid nature of the region. This exercise clearly
explains the abundance coarse mode dust decreasing from west to east, along
with an increase in the contribution of anthropogenic fine/accumulation
mode aerosols.</p>
      <?pagebreak page8600?><p id="d1e2370">With the goal of examining the transport of mineral dust (by the synoptic
winds), the spatial distributions of UV aerosol index, aerosol types and
aerosol absorption optical depth (AAOD), all derived from the Level-3
OMAERUVd data product (daily, <inline-formula><mml:math id="M148" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.0</mml:mn><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup><mml:mo>×</mml:mo><mml:mn mathvariant="normal">1.0</mml:mn><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>) from the Ozone Monitoring
Instrument (OMI, on board the Aura satellite; Levelt et al., 2006), are
examined. OMAERUV uses the pixel-level Level-2 aerosol data product of OMI
at three wavelengths (355, 388 and 500 nm) to derive AAOD. Higher
values of AAOD at 388 nm are indicative of the presence of dust or biomass
burning aerosols. This is because absorption by dust and organic carbon from
biomass burning sources has strong wavelength dependency, with higher
absorption at near-UV wavelengths. As the period of this campaign was devoid
of major fire activities over the study region (northern India) which
normally peaks in April to May and October to November, corresponding to
burning after the wheat and rice harvests (Vadrevu et al., 2011;
Venkataraman et al., 2006), the AAOD values would be representative of dust
loading. This aspect is confirmed in the subsequent section using lidar
depolarization ratio.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><?xmltex \currentcnt{7}?><label>Figure 7</label><caption><p id="d1e2395">Spatial distribution of <bold>(a)</bold> UV aerosol index, <bold>(b)</bold> aerosol type, <bold>(c)</bold> aerosol absorption optical depth (AAOD) at 388 nm and <bold>(d)</bold> AAOD at 500 nm during June 2016. <bold>(e)</bold> Synoptic wind and temperature at 850 hPa.</p></caption>
          <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f07.png"/>

        </fig>

      <p id="d1e2420">Figure 7a–d show the spatial distributions of UV aerosol index, aerosol
type and AAOD at 388 and 500 nm, while the synoptic winds are shown in
Fig. 7e. A very good association between the westerly advection and dust
loading extending from west to central IGP is noticeable from the figure.
This lends further support to the role of advected dust leading to higher
<inline-formula><mml:math id="M149" display="inline"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M150" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">MC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> at higher altitudes, seen in Fig. 6. In this
context, it is also worth noticing that based on observational data and
regional climate modeling, Banerjee et al. (2019) have clearly shown (in
their Fig. 7) the significant vertical extent of dust loading, of both
local and remote origin, during the pre-monsoon and summer across the IGP
reaching altitudes as high as 600 hPa.</p>
      <p id="d1e2445"><?xmltex \hack{\newpage}?>The volume size distribution of aerosols (shown in Fig. 8) at three
distinct altitude regions of the atmosphere also clearly shows the
altitudinal change in the pattern of distribution, changing from coarse mode
dominance near the surface to accumulation mode dominance at the ceiling
altitude over BBR. Those at JDR, the pattern of distributions remains the
same in the entire column. Similar to JDR, VNS also depicted a significant
enhancement in coarse mode aerosols in the upper levels (at 2 and 3 km
altitudes) of the atmosphere. Similar to these observations, based on the
collocated spectral scattering properties of aerosols obtained during the
same experiment, Vaishya et al. (2018) have reported that the aerosol
population changes from supermicron-mode-dominant natural aerosols to
submicron-mode-dominant anthropogenic aerosols, as we move from west to
east in the IGP. Moreover, the large abundance of coarse particles
(<inline-formula><mml:math id="M151" 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="M152" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) along with significant fine/accumulation mode
aerosols in the column highlights the complex mixture of dust with other
anthropogenic components in all three regions, making a complex scenario
for aerosol radiation and aerosol cloud interaction processes. Based on the
combination of satellite remote sensing and regional climate model
simulations, Banerjee et al. (2019) have also shown the presence of a dry
elevated layer of dust (at altitudes between 850 and 700 hPa, taking place
in multiple layers) during June across the IGP, transported from the Thar
Desert to the northern Bay of Bengal. To ascertain this further, we have
examined the data from CATS aboard ISS.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8"><?xmltex \currentcnt{8}?><label>Figure 8</label><caption><p id="d1e2469">Aerosol volume size distributions (mean profiles averaged for all
the days) at three distinct altitudes (600, 2000 and 3100 m) of the
atmosphere (shown by different color) over JDR, VNS and BBR.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f08.png"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS2">
  <label>3.2</label><title>Inferences from the CATS data</title>
      <p id="d1e2486">Geophysical parameters derived from CATS on board the ISS are very useful to
infer aerosol features in the atmospheric column, especially at altitudes
above the ceiling altitude of the aircraft (3.1 km). In the present study,
we have considered three products from CATS for the campaign period, viz.
(i) depolarization ratio, (ii) attenuated backscatter coefficients and (iii) aerosol types.</p>

      <?xmltex \floatpos{p}?><fig id="Ch1.F9" specific-use="star"><?xmltex \currentcnt{9}?><label>Figure 9</label><caption><p id="d1e2491">Aerosol depolarization ratio (obtained from Cloud-Aerosol
Transport System (CATS) on the International Space Station, ISS) for three
different passes of the ISS over the three subregions during the period of
aircraft observation. The tracks of CATS are shown by the solid lines in
the left panel, and the rectangular boxes in the right panels show the data
over the subregions.</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f09.png"/>

        </fig>

      <p id="d1e2500">Figure 9 shows the vertical cross section of depolarization ratio for three
passes during the campaign period and close to the three subregions
(identified by the rectangular boxes in the figure). Higher values
(<inline-formula><mml:math id="M153" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.3</mml:mn></mml:mrow></mml:math></inline-formula>) of depolarization ratios are seen in the western IGP
(JDR, bottom panel), suggesting the dominance of nonspherical (dust)
particles. The depolarization ratio decreases towards the east across the IGP
with values equal to 0.1 at the central IGP and <inline-formula><mml:math id="M154" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.2</mml:mn></mml:mrow></mml:math></inline-formula> in the
eastern BBR. These lend additional support to the inference on the
influence of dust aerosols during the campaign period. Supporting the
patterns of depolarization ratio, aerosol types (from CATS operating mode 7.1) in
Fig. 10a indicate the significant presence of dust at JDR, while the aerosol
types over VNS and BBR are a mixture of dust and polluted continental and
carbonaceous aerosols. Vertical profiles of total attenuated backscatter
coefficients show the vertical extent of the<?pagebreak page8601?> aerosol layer to be as high as
5 km (as has been shown by Banerjee et al., 2019) over all the sites
(Fig. 10b).</p>

      <?xmltex \floatpos{p}?><fig id="Ch1.F10" specific-use="star"><?xmltex \currentcnt{10}?><label>Figure 10</label><caption><p id="d1e2526">Transects of <bold>(a)</bold> aerosol types (1 – marine, 2 – marine mixture, 3 – dust, 4 – dust mixture, 5 – clean/background, 6 – polluted continental, 7 – smoke, 8 – volcanic) and <bold>(b)</bold> backscatter coefficients (Bs, km<inline-formula><mml:math id="M155" 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> Sr<inline-formula><mml:math id="M156" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) at 1064 nm obtained during the period of aircraft observation corresponding to the overpass of the ISS.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f10.png"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS3">
  <label>3.3</label><title>Vertical profiles of BC</title>
      <p id="d1e2573">BC is the chief anthropogenic absorbing aerosol species, and the IGP is
known to be among the global hot spots of it (Govardhan et al., 2019). The height
resolved information on <inline-formula><mml:math id="M157" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> is important not only in radiative
forcing but also in CCN activation as well (Bhattu et al., 2016). Collocated
measurements of BC during SWAAMI–RAWEX have been used to examine the
vertical profiles of BC and its variation across the IGP prior to the onset of
the Indian summer monsoon. Figure 11a shows the vertical profiles of BC for
the three subregions. Each profile is the average of all the profiles
obtained from measurements made from each of the base stations. It is seen
that BC remained low (<inline-formula><mml:math id="M158" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M159" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M160" 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>) and depicted
very weak altitude variations at the western and eastern IGP regions, while
in the central IGP there is a rapid decrease in BC from the high value
(<inline-formula><mml:math id="M161" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M162" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M163" 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>) near the surface. Above 2 km, all the
profiles overlap, though a weak increase is indicated over BBR, which is
examined later. The very high values of BC close to the surface at VNS are
attributed to the wide-spread anthropogenic activities in the central<?pagebreak page8602?> IGP
including the cluster of thermal power plants in that region. Consequently,
the columnar concentration of BC (integrated up to 3.1 km) is also the
highest at VNS.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F11"><?xmltex \currentcnt{11}?><label>Figure 11</label><caption><p id="d1e2650">Vertical profiles of <bold>(a)</bold> mean values of BC mass concentrations (<inline-formula><mml:math id="M164" display="inline"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) and <bold>(b)</bold> BC mass fractions (<inline-formula><mml:math id="M165" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) at JDR, VNS and BBR.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f11.png"/>

        </fig>

      <p id="d1e2687">However, the vertical profiles of the fractional contribution of BC
(<inline-formula><mml:math id="M166" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) to the total composite aerosol mass (estimated from the volume
size distribution, considering a uniform density of 2 g cm<inline-formula><mml:math id="M167" 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>, especially in
view of the abundance of dust) shows (Fig. 11b) subregional
distinctiveness. It remains the lowest (<inline-formula><mml:math id="M168" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">6</mml:mn></mml:mrow></mml:math></inline-formula> %) in the
western IGP, with very little altitude variation. In the central IGP,
<inline-formula><mml:math id="M169" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> is quite high (<inline-formula><mml:math id="M170" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">15</mml:mn></mml:mrow></mml:math></inline-formula> % to 20 %) within the ABL
and drops off fast above 2 km approaching the values seen for the western
IGP. <inline-formula><mml:math id="M171" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> depicts an elevated peak at around 1 km above ground level
at VNS, while at BBR, higher <inline-formula><mml:math id="M172" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> values occur at still higher
altitudes, where the near-surface values are much lower and
comparable to those at JDR. There is a steady increase in <inline-formula><mml:math id="M173" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> from near the
surface to higher altitudes, and above 2 km the values are comparable to
the peak values seen at VNS (at <inline-formula><mml:math id="M174" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> km altitude). Despite
this, the integrated BC concentration at BBR falls in between that of JDR and VNS,
mainly because of the large values occurring in the lower atmosphere at VNS.
It may be recalled that based on SWAAMI–RAWEX aircraft measurements,
Vaishya et al. (2018) have reported uniform scattering
characteristics across the IGP, while the absorption coefficients
showed subregional distinctiveness leading to a west-to-east gradient
(decrease) in the vertical structure of single-scattering albedo (SSA).</p>
      <p id="d1e2789">Investigation of the vertical profiles of BC mass concentrations on
individual days (Fig. S2 in the Supplement) helps to see the distinctiveness
in each subregion, resulting from the spatially heterogeneous nature of
emission sources and advection, especially at BBR where the inland profiles,
made during flights perpendicular to the coastline (on 2 and 3 June), show significantly higher values of BC at higher altitudes than those
along the coastline. At BBR, this arises mainly because of spatially
heterogeneous source impacts. The regions towards the northwest of BBR are
characterized by large-scale urban and industrial activities (“Ambient air
quality status and trends in Odisha: 2006–2014”). Similarly, near-surface
BC concentrations at VNS were higher when the flights were confined to the
NE, NW and SW of the city center, while the values in the SE sector were
lower. On the other hand, at JDR, the profiles revealed a better spatial
homogeneity.</p>
      <p id="d1e2792">To quantify the climatic implications of BC, the heating rate profiles of BC
are examined based on the estimation of shortwave aerosol direct radiative
forcing (DRF) due to BC alone. DRF due to BC represents the difference
between the DRF for aerosols with and without the BC component. The in situ
values of scattering (<inline-formula><mml:math id="M175" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">sca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) and absorption (<inline-formula><mml:math id="M176" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">abs</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>)
coefficients measured on board the aircraft were used to estimate spectral
values of AOD (layer-integrated <inline-formula><mml:math id="M177" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">sca</mml:mi></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">abs</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>),
single-scattering albedo (SSA) and asymmetry parameter (<inline-formula><mml:math id="M178" display="inline"><mml:mi>g</mml:mi></mml:math></inline-formula>) for each level,
assuming a well-mixed layer of 200 m above and below the measurement
altitude (details are available in Vaishya et al., 2018). The layer mean
values of AOD, SSA and Legendre moments of the aerosol phase function
(derived from the Henyey–Greenstein approximation) are used as input in the
Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART; Ricchiazzi et
al., 1998) model to estimate diurnally averaged DRF (net flux with and
without aerosols) at the top (DRF<inline-formula><mml:math id="M179" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">TOA</mml:mi></mml:msub></mml:math></inline-formula>) and bottom (DRF<inline-formula><mml:math id="M180" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">SUR</mml:mi></mml:msub></mml:math></inline-formula>) of each
of the layers. The atmospheric forcing (DRF<inline-formula><mml:math id="M181" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">ATM</mml:mi></mml:msub></mml:math></inline-formula>) for each of the levels
is then estimated as
            <disp-formula id="Ch1.E3" content-type="numbered"><label>3</label><mml:math id="M182" display="block"><mml:mrow><mml:msub><mml:mi mathvariant="normal">DRF</mml:mi><mml:mi mathvariant="normal">ATM</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:msub><mml:mi mathvariant="normal">DRF</mml:mi><mml:mi mathvariant="normal">TOA</mml:mi></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi mathvariant="normal">DRF</mml:mi><mml:mi mathvariant="normal">SUR</mml:mi></mml:msub><mml:mo>.</mml:mo></mml:mrow></mml:math></disp-formula>
          In order to estimate the forcing due to BC alone, optical parameters for
aerosols were deduced again. For this, values of <inline-formula><mml:math id="M183" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">abs</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> were
segregated into the contributions by BC (<inline-formula><mml:math id="M184" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) and organic carbon (OC) (<inline-formula><mml:math id="M185" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">OC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>), where <inline-formula><mml:math id="M186" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> was estimated following inverse
wavelength dependence of BC (e.g., Vaishya et al., 2017). Based on this, a
new set of AOD and SSA for BC-free atmosphere is calculated and fed into
SBDART for estimating DRF<inline-formula><mml:math id="M187" display="inline"><mml:msub><mml:mi/><mml:mtext>ALL-BC</mml:mtext></mml:msub></mml:math></inline-formula> without the BC component. Thus, DRF due to BC is
            <disp-formula id="Ch1.E4" content-type="numbered"><label>4</label><mml:math id="M188" display="block"><mml:mrow><mml:msub><mml:mi mathvariant="normal">DRF</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:msub><mml:mi mathvariant="normal">DRF</mml:mi><mml:mi mathvariant="normal">ALL</mml:mi></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi mathvariant="normal">DRF</mml:mi><mml:mtext>ALL-BC</mml:mtext></mml:msub><mml:mo>.</mml:mo></mml:mrow></mml:math></disp-formula>
          Here, DRF<inline-formula><mml:math id="M189" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">ALL</mml:mi></mml:msub></mml:math></inline-formula> represents forcing due to all the aerosol components,
including BC.</p>
      <?pagebreak page8604?><p id="d1e2987">The vertical profiles of atmospheric heating rate (HR, estimated based on
the atmospheric pressure difference between the top and bottom of each layer and
aerosol-induced forcing in that layer) due to BC alone show (Fig. 12)
maximum influence of BC in trapping the SW radiation at VNS, followed by BBR
and JDR. Interestingly, the altitudinal profiles of heating rate are
distinctly different over the regions, with BBR showing an increase with
altitude, while VNS shows the opposite pattern with maximum heating
(<inline-formula><mml:math id="M190" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.81</mml:mn></mml:mrow></mml:math></inline-formula> K d<inline-formula><mml:math id="M191" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) at 500 m above ground. Enhanced heating
at 500–2000 m altitude is seen at JDR. These results indicate the dominant
role of absorbing aerosols near the surface at VNS, while the atmospheric
perturbation due to elevated layers of absorbing aerosols is conspicuous at
BBR (HR <inline-formula><mml:math id="M192" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.35</mml:mn></mml:mrow></mml:math></inline-formula> K d<inline-formula><mml:math id="M193" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at the ceiling altitude). The
column-integrated values of atmospheric forcing due to BC alone are 7.9, 14.3 and 8.4 W m<inline-formula><mml:math id="M194" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at JDR, VNS and BBR,
respectively.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F12"><?xmltex \currentcnt{12}?><label>Figure 12</label><caption><p id="d1e3048">Vertical profiles of atmospheric heating rate due to BC (solid
lines) and composite (dashed lines) aerosols for the regions of the IGP: <bold>(a)</bold> JDR in western IGP, <bold>(b)</bold> VNS in central IGP and <bold>(c)</bold> BBR in eastern IGP. Data
for the composite heating rate profiles are from Vaishya et al. (2018).</p></caption>
          <?xmltex \igopts{width=199.169291pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f12.png"/>

        </fig>

      <p id="d1e3066">In this context, we have examined the possible role of the large network of
thermal power plants (TPPs) over the northern part of India, which is
reported to have a significant contribution to regional emissions (Singh et
al., 2019). These include the emissions of <inline-formula><mml:math id="M195" 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>, <inline-formula><mml:math id="M196" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M197" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, CO,
volatile organic compounds (VOCs), suspended particulate matter (PM<inline-formula><mml:math id="M198" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> and PM<inline-formula><mml:math id="M199" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">10</mml:mn></mml:msub></mml:math></inline-formula>, including BC and OC) and
other trace metals like mercury (Guttikanda and Jawahar, 2014; Sahu et al.,
2017), dispersing over large areas through stacks. Fly ash from coal-fired
power plants causes severe environmental degradation in the nearby
environments (5–10 km) of TPPs (Tiwari et al., 2019). Over the IGP, since
more than 70 % of the thermal power plants are coal based, emissions of
<inline-formula><mml:math id="M200" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M201" 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> make up more than 47 % of the total emission share,
while the relative share of PM<inline-formula><mml:math id="M202" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> and <inline-formula><mml:math id="M203" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> is <inline-formula><mml:math id="M204" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">15</mml:mn></mml:mrow></mml:math></inline-formula> % and
30 % (GAINS, 2010). Based on the in situ measurement of BC in fixed and
transit areas in close proximity of seven coal-fired TPPs in Singrauli
(located <inline-formula><mml:math id="M205" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">700</mml:mn></mml:mrow></mml:math></inline-formula> km northwest of BBR), Singh et al. (2019)
have reported that BC concentration reached as high as 200 <inline-formula><mml:math id="M206" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M207" 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
the transit measurements. The Energy and Resources Institute, India, has
also reported that emission levels of the carbonaceous (soot or BC)
particles are estimated to be around 0.061 gm kW h<inline-formula><mml:math id="M208" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> per unit of electricity
from Indian thermal power plants (Vipradas et al., 2004). Based on emission
pathways and ambient PM<inline-formula><mml:math id="M209" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> pollution over India, Venkataraman et al. (2018)
have reported that the types of aerosols emitted from coal burning in
thermal power plants and industry in eastern and peninsular India are
similar to those of residential biomass combustion. The ongoing discussion
thus clearly indicates that TPPs are major sources of BC in the atmosphere.</p>
      <p id="d1e3226">As it is not possible to measure BC from space, to infer the role of
these emissions from thermal power plants in causing the higher BC fraction
at higher altitude over BBR, we have examined the spatial distribution of
the concentrations of the co-emitted <inline-formula><mml:math id="M210" 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 <inline-formula><mml:math id="M211" 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> in Fig. 13, in
which the locations of major coal-based TPPs
(<uri>https://www.ntpc.co.in/en/power-generation/coal-based-power-stations</uri>, last access: 9 July 2020) are
also marked. The data are obtained from OMI on board the Aura satellite. Higher
concentrations of <inline-formula><mml:math id="M212" 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 <inline-formula><mml:math id="M213" 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> are readily discernible from the
figure around the regions (marked in the figure) during the period of flight
experiments where there are clusters of TPPs. As the energy consumption is the
highest during summer and most dependent on TPPs, these TPPs should be
operating to near full capacity. This provides indirect support to the
high concentrations of BC (co-emitted) at higher levels. In general, these
TPPs have tall stacks (heights in the range 200 to 400 m) and aid easy
ventilation to the lower free-tropospheric altitudes.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F13"><?xmltex \currentcnt{13}?><label>Figure 13</label><caption><p id="d1e3278"><bold>(a)</bold> Geographic position of thermal power plants (TPP) over India, along with the spatial map of <bold>(b)</bold> <inline-formula><mml:math id="M214" 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> tropospheric column density (molecules cm<inline-formula><mml:math id="M215" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) and <bold>(c)</bold> <inline-formula><mml:math id="M216" 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> column amount (DU, 1 DU <inline-formula><mml:math id="M217" display="inline"><mml:mrow><mml:mo>=</mml:mo><mml:mn mathvariant="normal">2.69</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mn mathvariant="normal">10</mml:mn><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M218" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) over the northern part of India.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f13.png"/>

        </fig>

      <?pagebreak page8605?><p id="d1e3359">To further ascertain this, the spectral properties of aerosol absorption are
examined. First, we have examined the frequency distribution of absorption
Ångström exponent (<inline-formula><mml:math id="M219" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">α</mml:mi><mml:mi mathvariant="normal">abs</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, derived from the linear fit on
log-log scale between corresponding absorption coefficients to Aethalometer
wavelengths) in Fig. 14, separately for the mixed layer (ML, below 1.5 km)
and above (<inline-formula><mml:math id="M220" display="inline"><mml:mrow><mml:mo>≥</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> km). The frequency distribution of <inline-formula><mml:math id="M221" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">α</mml:mi><mml:mi mathvariant="normal">abs</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> reveals a clear shift towards lower values as we move from JDR to BBR,
both within the ML and above, even though the values of <inline-formula><mml:math id="M222" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">α</mml:mi><mml:mi mathvariant="normal">abs</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> are mostly between 1 and 1.5. Based on laboratory studies and field
investigations, it has been shown that the higher values of <inline-formula><mml:math id="M223" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">α</mml:mi><mml:mi mathvariant="normal">abs</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> (<inline-formula><mml:math id="M224" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula>) are representative of biomass burning
emissions, while the values of <inline-formula><mml:math id="M225" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> are indicative of fossil fuel
combustions (Kirchstetter et al., 2004). The values of <inline-formula><mml:math id="M226" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">α</mml:mi><mml:mi mathvariant="normal">abs</mml:mi></mml:msub><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> are indicative of the presence of biomass burning, whose
relative abundance increases with the steepness of the absorption spectra, as
has been reported elsewhere from the laboratory experiments (Hopkins et al.,
2007).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F14"><?xmltex \currentcnt{14}?><label>Figure 14</label><caption><p id="d1e3454"><bold>(a)</bold> Frequency of occurrences of  absorption Ångström exponent (<inline-formula><mml:math id="M227" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">α</mml:mi><mml:mi mathvariant="normal">abs</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) below 1.5 km and above 2.5 km altitude; <bold>(b)</bold> variation in BC mass concentrations corresponding to different values of <inline-formula><mml:math id="M228" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">α</mml:mi><mml:mi mathvariant="normal">abs</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> is shown in the right panels for the same two altitude regimes at distinct locations of northern India.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f14.png"/>

        </fig>

      <p id="d1e3490"><?xmltex \hack{\newpage}?>Examining Fig. 14 in the above light, it emerges that a significant
contribution of BC from fossil fuel combustions mixed with biomass burning
origin prevails at higher altitudes over BBR, while the association between
the two decreases abruptly from ML to a higher height at VNS. The consistent
higher values of BC in the column associated with the values of <inline-formula><mml:math id="M229" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">α</mml:mi><mml:mi mathvariant="normal">abs</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> lying between 1 and 1.5 can also be due to the aging of BC at
higher heights, during which BC mixes with other species and its Ångström
exponent increases. This is because the spectral dependence of absorption steepens when
BC (even though its source could be fossil fuel) is coated with a concentric
shell of weakly absorbing material (Gogoi et al., 2017). Further
investigations are needed in this direction.</p>
</sec>
<sec id="Ch1.S3.SS4">
  <label>3.4</label><title>Inter-seasonal variability: a case study at JDR</title>
      <p id="d1e3513">The spatial variation in the altitude profiles of <inline-formula><mml:math id="M230" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">AC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M231" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M232" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">MC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> and
<inline-formula><mml:math id="M233" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> across the IGP hints to several possible implications of their
direct and indirect effects. Altitudinal increases in the values of <inline-formula><mml:math id="M234" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> and
<inline-formula><mml:math id="M235" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">MC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> along with depolarization ratios are indicative of the presence
of dust (<inline-formula><mml:math id="M236" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M237" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) in the lower free troposphere, which is
known to produce a long-wave (warming) radiative effect (Miller et al., 2006;
Tegen and Lacis, 1996). Conversely, significant abundance of accumulation
mode aerosols, in general, might contribute significantly to scattering. For
example, a clear seasonal change in the vertical profiles of aerosol
concentrations (<inline-formula><mml:math id="M238" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mtext>T-APS</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>) as measured by APS in the size (diameter)
regime of 0.5 to 20 <inline-formula><mml:math id="M239" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m is noticeable at JDR, changing from the much
steeper variation (vertically) in winter (as reported by Gogoi et al., 2019)
to a near-steady one during prior to the onset of the monsoon (Fig. 15).
Based on airborne measurements during SWAAMI–RAWEX, Vaishya et al. (2018) have reported that<?pagebreak page8606?> the values of SSA at west IGP varied between 0.935
(at 530) in spring and 0.84 (at 530 nm) prior to the onset of the monsoon,
indicating a seasonal change in the aerosol type and consequently their
optical properties.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F15"><?xmltex \currentcnt{15}?><label>Figure 15</label><caption><p id="d1e3622">Vertical profiles of seasonal mean values of aerosol number
concentrations (<inline-formula><mml:math id="M240" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">T</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, as measured by APS in the size (diameter) of regime 0.5 to 20 <inline-formula><mml:math id="M241" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) at Jodhpur during winter 2012 (17–19 December), spring 2013
(18 and 20 May) and just prior to the onset of the monsoon 2016 (17–20 June).</p></caption>
          <?xmltex \igopts{width=227.622047pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f15.png"/>

        </fig>

      <p id="d1e3650">To examine the role of the dynamical processes in different seasons, we have
shown the profiles of vertical velocity (in pressure coordinates from 1000 to 100 hPa) in Fig. 16. These are obtained from ERA-Interim reanalysis
data sets. Here, the positive and negative signs of vertical velocity
(<inline-formula><mml:math id="M242" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>) are indicative of updraft (as indicated by <inline-formula><mml:math id="M243" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>ve values of <inline-formula><mml:math id="M244" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>) and downdraft (as indicated by <inline-formula><mml:math id="M245" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>ve values of <inline-formula><mml:math id="M246" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>). A clear
seasonal transformation is seen, with increasingly stronger updrafts
dominating over the IGP from December to June, with the intensity increasing
from west to east. In the western IGP regions, the sign of vertical velocity seems to change from December to June, progressively enhancing the
magnitude of deep convection towards the onset of the monsoon, imparting stronger
vertical dispersion and more homogeneous distribution of aerosols in the
column.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F16"><?xmltex \currentcnt{16}?><label>Figure 16</label><caption><p id="d1e3691">Vertical profiles of vertical velocity (Pa s<inline-formula><mml:math id="M247" 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>) over the
study locations representing winter (December 2012), spring (May 2013) and
just prior to the onset of the Indian summer monsoon (June 2016) at different
pressure levels from 1000 to 100 hPa. The positive and negative values are
indicative of the descending and ascending motions, respectively. The
horizontal dashed line indicated the ceiling altitude (<inline-formula><mml:math id="M248" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">3.5</mml:mn></mml:mrow></mml:math></inline-formula> km above ground level) of aircraft measurements while the vertical dashed
lines mark the boundary of vertical velocity (<inline-formula><mml:math id="M249" display="inline"><mml:mrow><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0</mml:mn></mml:mrow></mml:math></inline-formula>) changing from positive
to negative and vice versa.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/8593/2020/acp-20-8593-2020-f16.png"/>

        </fig>

      <p id="d1e3732">Regionally, the seasonal transformation of vertical velocity is more
prominent over the eastern IGP BBR, where the magnitude of vertical
velocity is consistently higher from surface to upper-tropospheric regions
prior to the onset of the monsoon. During this period, the head of the Bay of Bengal is
known to be one of the regions where deep convection exists (Bhat et al.,
2001). Since size distribution is a dominant factor in determining the direct
radiative forcing (Tegen and Lacis, 1996; Liao and Seinfeld, 1998; Seinfeld
et al., 2016), a clear seasonal change in the altitudinal variations in
aerosol type and size distributions associated with distinct transport and
convective processes will have a strong radiative impact. In particular the
columnar distribution of coarse mode dust and highly absorbing BC needs
explicit representations in climate models for accurate understanding of the
net top-of-atmosphere (TOA) direct radiative forcing. Apart from the direct radiative
implications, abundance of coarse mode dust particles (having sizes larger
than critical diameter) and aged BC (coated with hygroscopic materials) in
the lower free troposphere can act as CCN in a
supersaturated environment. Recent studies suggest that mineral aerosols are
the dominant IN for cirrus clouds (Storelvmo and Herger, 2014).</p>
</sec>
</sec>
<sec id="Ch1.S4" sec-type="conclusions">
  <label>4</label><title>Summary and conclusions</title>
      <p id="d1e3744">Extensive airborne measurements of aerosol number–size distribution
profiles are carried out, for the first time across the IGP prior to the
onset of the Indian summer monsoon as part of the South-West Asian Aerosol–Monsoon
Interactions and Regional Aerosol Warming Experiment (SWAAMI–RAWEX), a joint
India–UK field experiment. Collocated measurements of BC profiles are also
carried out. The main findings are as follows.</p>
      <?pagebreak page8607?><p id="d1e3747">Aerosol size distribution depicted significant altitudinal variation in the
coarse mode regime, having the highest coarse mode mass fraction (72 %) near
the surface at the western IGP (represented by Jodhpur – JDR), while BC mass
fractions (<inline-formula><mml:math id="M250" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) as well as aerosol accumulation and coarse mode number
concentrations (<inline-formula><mml:math id="M251" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">AC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) remained nearly steady from the surface to the ceiling
altitude (<inline-formula><mml:math id="M252" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">3.5</mml:mn></mml:mrow></mml:math></inline-formula> km) of the aircraft measurements. However, the
pattern was significantly different at the eastern IGP (represented by
Bhubaneswar – BBR) transforming to gradually decreasing values of coarse
mode mass concentration (<inline-formula><mml:math id="M253" display="inline"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) and <inline-formula><mml:math id="M254" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">AC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, but with a corresponding
increase in the values of <inline-formula><mml:math id="M255" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> with altitude. At subregional scales,
BBR depicted higher spatial (vertical) heterogeneity in the above aerosol
characteristics, while the highest homogeneity was observed at JDR.</p>
      <p id="d1e3816">Number concentrations showed dominance of the accumulation mode near the
surface, with the central IGP (represented by Varanasi – VNS) depicting the
highest values <inline-formula><mml:math id="M256" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">AC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> (<inline-formula><mml:math id="M257" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi mathvariant="normal">BC</mml:mi></mml:msub><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">15</mml:mn></mml:mrow></mml:math></inline-formula> %), while the
coarse mode remained nearly steady throughout the vertical column.</p>
      <p id="d1e3845">Atmospheric heating rate due to BC is highest near the surface at VNS
(<inline-formula><mml:math id="M258" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.81</mml:mn></mml:mrow></mml:math></inline-formula> K d<inline-formula><mml:math id="M259" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>), while showing an increasing pattern
with altitude at BBR (<inline-formula><mml:math id="M260" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.35</mml:mn></mml:mrow></mml:math></inline-formula> K d<inline-formula><mml:math id="M261" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at the ceiling
altitude).</p>
      <p id="d1e3893">Our measurements, supplemented with information from different spaceborne
sensors (Cloud Aerosol Transportation System – CATS aboard International
Space Station – ISS and Ozone Monitoring Instrument – OMI on board the Aura
satellite) and model results clearly indicated the role of mineral dust, both
locally generated and advected from the west Asian region, in contributing
to the aerosol loading across the IGP, especially at free-tropospheric
altitudes. The vertical extents of these layers reached as high as 5 km
during the period of observation.</p>
</sec>

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

      <p id="d1e3901">Data are available upon request from Surendran Nair Suresh Babu (s_sureshbabu@vssc.gov.in).</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e3904">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/acp-20-8593-2020-supplement" xlink:title="pdf">https://doi.org/10.5194/acp-20-8593-2020-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e3913">SNSB, SKS and KKM conceptualized the experiment and finalized the
methodology. SNSB, MMG, VNJ and AV conducted the measurement on board
aircraft. MMG carried out the scientific analysis of the aircraft data and
drafted the manuscript with contributions from AV and VNJ. KKM, SKS and SNSB
carried out the review and editing of the manuscript.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e3919">The authors declare that they have no conflict of interest.</p>
  </notes><notes notes-type="sistatement"><title>Special issue statement</title>

      <p id="d1e3925">This article is part of the special issue “Interactions between aerosols and the South West Asian monsoon”. It is not associated with a conference.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e3931">This study was a part of joint India–UK field campaign, South-West Asian
Aerosol–Monsoon Interactions and Regional Aerosol Warming Experiment (SWAAMI–RAWEX). The aircraft and the flying support were provided by National Remote Sensing Centre (NRSC), Hyderabad. Sreedharan Krishnakumari Satheesh would like to acknowledge the J. C. Bose
Fellowship awarded to him by SERB-DST. Aditya Vaishya was supported by the Department of
Science and Technology, Government of India, through its INSPIRE Faculty
program. We acknowledge the CATS science team for providing valuable data
sets (freely) for scientific applications.</p></ack><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e3936">The RAWEX project is supported by
ISRO (Indian Space Research Organisation), and the SWAAMI project is
supported by MoES (Ministry of Earth Science), Government of India.</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e3942">This paper was edited by B. V. Krishna Murthy and reviewed by two anonymous referees.</p>
  </notes><ref-list>
    <title>References</title>

      <ref id="bib1.bib1"><label>1</label><?label 1?><mixed-citation>
Arnott, W. P., Hamasha, K., Moosmuller, H., Sheridan, P. J., and Ohren, J. A.:
Towards aerosol light-absorption measurements with a 7-wavelength
aethalometer: Evaluation with a photoacoustic instrument and 3-wavelength
nephelometer, Aerosol Sci. Tech., 39, 17–29, 2005.</mixed-citation></ref>
      <ref id="bib1.bib2"><label>2</label><?label 1?><mixed-citation>Babu, S. S., Nair, V. S., Gogoi, M. M., and Moorthy, K. K.: Seasonal variation of
vertical distribution of aerosol single scattering albedo over Indian
sub-continent: RAWEX aircraft observations, Atmos. Environ., 125, 312–323,
<ext-link xlink:href="https://doi.org/10.1016/j.atmosenv.2015.09.041" ext-link-type="DOI">10.1016/j.atmosenv.2015.09.041</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bib3"><label>3</label><?label 1?><mixed-citation>Banerjee, P., Satheesh, S. K., Moorthy, K. K., Nanjundiah, R. S., and Nair, V. S.:
Long-range transport of mineral dust to the Northeast Indian Ocean: regional
versus remote sources and the implications, J. Climate, 32, 1525–1549, <ext-link xlink:href="https://doi.org/10.1175/JCLI-D-18-0403.1" ext-link-type="DOI">10.1175/JCLI-D-18-0403.1</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib4"><label>4</label><?label 1?><mixed-citation>
Bansal, O., Singh, A., and Singh, D.: Aerosol Characteristics over the
Northwestern Indo-Gangetic Plain: Clear-Sky Radiative Forcing of Composite
and Black Carbon Aerosol, Aerosol Air Qual. Res., 19, 5–14, 2019.</mixed-citation></ref>
      <ref id="bib1.bib5"><label>5</label><?label 1?><mixed-citation>
Bhat, G. S., Gadgil, S., Kumar, P. V. S., Kalsi, S. R., Madhusoodanan, P.,
Murty, V. S. N., Rao, V. V. K. P., Babu, V. R., Rao, L. V. G., Rao, R. R.,
Ravichandran, R., Reddy, K. G., Rao, P. S., Sengupta, D., Sikka, D. R., Swain,
J., and Vinayachandran, P. N.: BOBMEX: The Bay of Bengal Monsoon Experiment,
B. Am. Meteorol. Soc., 82,  2217–2243, 2001.</mixed-citation></ref>
      <ref id="bib1.bib6"><label>6</label><?label 1?><mixed-citation>
Bhattu, D., Tripathi, S., and Chakraborty, A.: Deriving aerosol hygroscopic
mixing state from size-resolved ccn activity and HR-TOF-AMS measurements,
Atmos. Environ., 142, 57–70, 2016.</mixed-citation></ref>
      <ref id="bib1.bib7"><label>7</label><?label 1?><mixed-citation>Brooks, J., Allan, J. D., Williams, P. I., Liu, D., Fox, C., Haywood, J., Langridge, J. M., Highwood, E. J., Kompalli, S. K., O'Sullivan, D., Babu, S. S., Satheesh, S. K., Turner, A. G., and Coe, H.: Vertical and horizontal distribution of submicron aerosol chemical composition and physical characteristics across northern India during pre-monsoon and monsoon seasons, Atmos. Chem. Phys., 19, 5615–5634, <ext-link xlink:href="https://doi.org/10.5194/acp-19-5615-2019" ext-link-type="DOI">10.5194/acp-19-5615-2019</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib8"><label>8</label><?label 1?><mixed-citation>Corrigan, C. E., Ramanathan, V., and Schauer, J. J.: Impact of monsoon
transitions on the physical and optical properties of aerosols, J. Geophys.
Res., 111, D18208, <ext-link xlink:href="https://doi.org/10.1029/2005JD006370" ext-link-type="DOI">10.1029/2005JD006370</ext-link>, 2006.</mixed-citation></ref>
      <?pagebreak page8608?><ref id="bib1.bib9"><label>9</label><?label 1?><mixed-citation>Drinovec, L., Močnik, G., Zotter, P., Prévôt, A. S. H., Ruckstuhl, C., Coz, E., Rupakheti, M., Sciare, J., Müller, T., Wiedensohler, A., and Hansen, A. D. A.: The ”dual-spot” Aethalometer: an improved measurement of aerosol black carbon with real-time loading compensation, Atmos. Meas. Tech., 8, 1965–1979, <ext-link xlink:href="https://doi.org/10.5194/amt-8-1965-2015" ext-link-type="DOI">10.5194/amt-8-1965-2015</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib10"><label>10</label><?label 1?><mixed-citation>
GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies): Scenarios for cost-effective control of air pollution and greenhouse gases in India, International Institute of Applied Systems Analysis, Laxenburg, Austria, 2010.</mixed-citation></ref>
      <ref id="bib1.bib11"><label>11</label><?label 1?><mixed-citation>Gautam, R., Hsu, N. C., and Lau, K. M.: Premonsoon aerosol characterization and
radiative effects over the Indo-Gangetic Plains: Implications for regional
climate warming, J. Geophys. Res., 115, D17208, <ext-link xlink:href="https://doi.org/10.1029/2010JD013819" ext-link-type="DOI">10.1029/2010JD013819</ext-link>,
2010.</mixed-citation></ref>
      <ref id="bib1.bib12"><label>12</label><?label 1?><mixed-citation>Gautam, R., Hsu, N. C., Tsay, S. C., Lau, K. M., Holben, B., Bell, S., Smirnov, A., Li, C., Hansell, R., Ji, Q., Payra, S., Aryal, D., Kayastha, R., and Kim, K. M.: Accumulation of aerosols over the Indo-Gangetic plains and southern slopes of the Himalayas: distribution, properties and radiative effects during the 2009 pre-monsoon season, Atmos. Chem. Phys., 11, 12841–12863, <ext-link xlink:href="https://doi.org/10.5194/acp-11-12841-2011" ext-link-type="DOI">10.5194/acp-11-12841-2011</ext-link>, 2011.</mixed-citation></ref>
      <ref id="bib1.bib13"><label>13</label><?label 1?><mixed-citation>Giles, D. M., Holben, B. N., Eck, T. F., Sinyuk, A., Smirnov, A., Slutsker,
I., Dickerson, R. R., Thompson, A. M., and Schafer, J. S.: An analysis of
AERONET aerosol absorption properties and classifications representative of
aerosol source regions, J. Geophys. Res., 117, D17203,
<ext-link xlink:href="https://doi.org/10.1029/2012JD018127" ext-link-type="DOI">10.1029/2012JD018127</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib14"><label>14</label><?label 1?><mixed-citation>Gogoi, M. M., Babu, S. S., Moorthy, K. K., Bhuyan, P. K., Pathak, B., Subba, T.,
Chutia, L., Kundu, S. S., Bharali, C., Borgohain, A., Guha, A., De, B. K.,
Singh, B., and Chin, M.: Radiative effects of absorbing aerosols over
northeastern India: Observations and model simulations, J. Geophys. Res.,
122, 1–26, <ext-link xlink:href="https://doi.org/10.1002/2016JD025592" ext-link-type="DOI">10.1002/2016JD025592</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib15"><label>15</label><?label 1?><mixed-citation>Gogoi, M. M., Lakshmi, N. B., Nair, V. S., Kompalli, S. K., Moorthy, K. K., and
Babu, S. S.: Seasonal contrast in the vertical profiles of aerosol
number concentrations and size distributions over India: implications from
RAWEX aircraft campaign, J. Earth Sys. Sc., 128, 225, <ext-link xlink:href="https://doi.org/10.1007/s12040-019-1246-y" ext-link-type="DOI">10.1007/s12040-019-1246-y</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib16"><label>16</label><?label 1?><mixed-citation>Govardhan, G., Satheesh, S. K., Moorthy, K. K., and Nanjundiah, R.: Simulations of black carbon over the Indian region: improvements and implications of diurnality in emissions, Atmos. Chem. Phys., 19, 8229–8241, <ext-link xlink:href="https://doi.org/10.5194/acp-19-8229-2019" ext-link-type="DOI">10.5194/acp-19-8229-2019</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib17"><label>17</label><?label 1?><mixed-citation>Guttikunda, S. K. and Jawahar, P.: Atmospheric emissions and pollution from
the coal-fired thermal power plants in India, Atmos. Environ., 92, 449–460,
<ext-link xlink:href="https://doi.org/10.1016/j.atmosenv.2014.04.057" ext-link-type="DOI">10.1016/j.atmosenv.2014.04.057</ext-link>, 2014.</mixed-citation></ref>
      <ref id="bib1.bib18"><label>18</label><?label 1?><mixed-citation>
Hopkins, R. J., Tivanski, A. V., Marten, B. D., and Gilles, M. K.: Chemical
bonding and structure of black carbon reference materials and individual
carbonaceous atmospheric aerosols, J. Aerosol Sci. 38, 573–591, 2007.</mixed-citation></ref>
      <ref id="bib1.bib19"><label>19</label><?label 1?><mixed-citation>Jayachandran, V. N., Suresh Babu, S. N., Vaishya, A., Gogoi, M. M., Nair, V. S., Satheesh, S. K., and Krishna Moorthy, K.: Altitude profiles of cloud condensation nuclei characteristics across the Indo-Gangetic Plain prior to the onset of the Indian summer monsoon, Atmos. Chem. Phys., 20, 561–576, <ext-link xlink:href="https://doi.org/10.5194/acp-20-561-2020" ext-link-type="DOI">10.5194/acp-20-561-2020</ext-link>, 2020.</mixed-citation></ref>
      <ref id="bib1.bib20"><label>20</label><?label 1?><mixed-citation>
Kedia, S., Ramachandran, S., Holben, B. N., and Tripathi, S. N.: Quantification of
aerosol type, and sources of aerosols over the Indo-Gangetic Plain, Atmos.
Environ., 98, 607–619, 2014.</mixed-citation></ref>
      <ref id="bib1.bib21"><label>21</label><?label 1?><mixed-citation>Kirchstetter, T. W., Novakov, T., and Hobbs, P. V.: Evidence that the
spectral dependence of light absorption byaerosols is affected by organic
carbon, J. Geophys. Res., 109, D21208, <ext-link xlink:href="https://doi.org/10.1029/2004JD004999" ext-link-type="DOI">10.1029/2004JD004999</ext-link>, 2004.</mixed-citation></ref>
      <ref id="bib1.bib22"><label>22</label><?label 1?><mixed-citation>
Kulkarni, J. R., Maheskumar, R. S., Morwal, S. B., Padma Kumari, B., Konwar, M., Deshpande, C. G., Joshi, R. R., Bhalwankar, R. V., Pandithurai, G., Safai, P. D., Narkhedkar, S. G., Dani, K. K., Nath, A., Nair, S., Sapre, V. V., Puranik, P.
V., Kandalgaonkar, S., Mujumdar, V. R., Khaladkar, R. M., Vijayakumar, R.,
Prabha, T. V., and Goswami, B. N.: The Cloud Aerosol Interactions and
Precipitation Enhancement Experiment (CAIPEEX): Overview and Preliminary
Results, Curr. Sci. India, 102, 413–425, 2012.</mixed-citation></ref>
      <ref id="bib1.bib23"><label>23</label><?label 1?><mixed-citation>
Kumar, M., Parmar, K. S., Kumar, D. B., Mhawish, A., Broday, D. M., Malla,
R. K., and Banerjeea, T.: Long-term aerosol climatology over Indo-Gangetic Plain:
Trend, prediction and potential source fields, Atmos. Environ., 180, 37–50,
2018.</mixed-citation></ref>
      <ref id="bib1.bib24"><label>24</label><?label 1?><mixed-citation>Lee, L., Zhang, J., Reid, J. S., and Yorks, J. E.: Investigation of CATS aerosol products and application toward global diurnal variation of aerosols, Atmos. Chem. Phys., 19, 12687–12707, <ext-link xlink:href="https://doi.org/10.5194/acp-19-12687-2019" ext-link-type="DOI">10.5194/acp-19-12687-2019</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib25"><label>25</label><?label 1?><mixed-citation>Levelt, P. F., van den Oord, G. H. J., Dobber, M. R., Mälkki, A.,
Visser, H., de Vries, J., Stammes, P., Lundell, J. O. V., and Saari, H.: The
Ozone Monitoring Instrument, IEEE T. Geosci. Remote, 44,
1093–1101, <ext-link xlink:href="https://doi.org/10.1109/TGRS.2006.872333" ext-link-type="DOI">10.1109/TGRS.2006.872333</ext-link>, 2006.</mixed-citation></ref>
      <ref id="bib1.bib26"><label>26</label><?label 1?><mixed-citation>Li, Z., Lau, W. K. M., Ramanathan, V., Wu, G., Ding, Y., Manoj, M. G., Liu, J., Qian, Y., Li, J., Zhou, T., Fan, J., Rosenfeld, D., Ming, Y., Wang, Y., Huang, J., Wang, B., Xu, X., Lee, S. S., Cribb, M., Zhang, F., Yang, X., Zhao, C., Takemura, T., Wang, K., Xia, X., Yin, Y., Zhang, H., Guo, J., Zhai, P. M., Sugimoto, N., Babu, S. S., and Brasseur, G. P.: Aerosol and monsoon climate interactions over Asia, Aerosol
and monsoon climate interactions over Asia, Rev. Geophys., 54, 866–929,
<ext-link xlink:href="https://doi.org/10.1002/2015RG000500" ext-link-type="DOI">10.1002/2015RG000500</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bib27"><label>27</label><?label 1?><mixed-citation>
Liao, H. and Seinfeld, J. H.: Radiative forcing by mineral dust aerosols:
Sensitivity to key variables, J. Geophys. Res., 103, 31637–31645, 1998.</mixed-citation></ref>
      <ref id="bib1.bib28"><label>28</label><?label 1?><mixed-citation>
Mhawish, A., Banerjeea, T., Broday, D. M., Misra, A., and Tripathi, S. N.:
Evaluation of MODIS Collection 6 aerosol retrieval algorithms over
Indo-Gangetic Plain: Implications of aerosols types and mass loading, Remote
Sens. Environ., 201, 297–313, 2017.</mixed-citation></ref>
      <ref id="bib1.bib29"><label>29</label><?label 1?><mixed-citation>Miller, R. L., Cakmur, R. V., Perlwitz, J. P., Geogdzhayev, I. V., Ginoux, P., Kohfeld, K. E., Koch, D., Prigent, C., Ruedy, R., Schmidt, G. A., and Tegen, I.: Mineral dust aerosols in the NASA Goddard Institute
for Space Sciences ModelE atmospheric general circulation model, J. Geophys.
Res., 111, D06208, <ext-link xlink:href="https://doi.org/10.1029/2005JD005796" ext-link-type="DOI">10.1029/2005JD005796</ext-link>, 2006.</mixed-citation></ref>
      <ref id="bib1.bib30"><label>30</label><?label 1?><mixed-citation>
Mitchell, J. P. and Nagel, M. W.: Time-of-flight aerodynamic particle size
analysers: their use and limitations for the evaluation of medical aerosols,
J. Aerosol Med., 12, 217–240, 1999.</mixed-citation></ref>
      <ref id="bib1.bib31"><label>31</label><?label 1?><mixed-citation>
Moorthy, K. K., Satheesh, S. K., and Murthy, B. V. K.: Characteristics of spectral
optical depths and size distributions of aerosols over tropical oceanic
regions, J. Atmos. Sol.-Terr. Phy., 60, 981–992, 1998.</mixed-citation></ref>
      <ref id="bib1.bib32"><label>32</label><?label 1?><mixed-citation>Moorthy, K. K., Babu, S. S., Sunilkumar, S. V., Gupta, P. K., and Gera, B. S.:
Altitude profiles of aerosol BC, derived from aircraf<?pagebreak page8609?>t measurements over an
inland urban location in India, Geophys. Res. Lett., 31, L22103,
<ext-link xlink:href="https://doi.org/10.1029/2004GL021336" ext-link-type="DOI">10.1029/2004GL021336</ext-link>, 2004.</mixed-citation></ref>
      <ref id="bib1.bib33"><label>33</label><?label 1?><mixed-citation>Moorthy, K. K., Babu, S. S., Satheesh, S. K., Srinivasan, J., and Dutt, C. B. S.:
Dust absorption over the “Great Indian Desert” inferred using ground-based
and satellite remote sensing, J. Geophys. Res., 112, D09206,
<ext-link xlink:href="https://doi.org/10.1029/2006JD007690" ext-link-type="DOI">10.1029/2006JD007690</ext-link>, 2007.</mixed-citation></ref>
      <ref id="bib1.bib34"><label>34</label><?label 1?><mixed-citation>Moorthy, K. K., Satheesh, S. K., and Kotamarthi, V. R.: Evolution of aerosol
research in India and the RAWEX–GVAX: an overview, Curr. Sci. India, 111, 53–75, <ext-link xlink:href="https://doi.org/10.18520/cs/v111/i1/53-75" ext-link-type="DOI">10.18520/cs/v111/i1/53-75</ext-link>,
2016.</mixed-citation></ref>
      <ref id="bib1.bib35"><label>35</label><?label 1?><mixed-citation>Nair, V. S., Babu, S. S., Gogoi, M. M., and Moorthy, K. K.: Large-scale
enhancement in aerosol absorption in the lower free troposphere over
continental India during spring, Geophys. Res. Lett., 43, 11453–11461,
<ext-link xlink:href="https://doi.org/10.1002/2016GL070669" ext-link-type="DOI">10.1002/2016GL070669</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bib36"><label>36</label><?label 1?><mixed-citation>Nath, R., Luo, Y., Chen, W., and Cui, X.: On the contribution of internal
variability and external forcing factors to the Cooling trend over the Humid
Subtropical Indo-Gangetic Plain in India, Sci. Rep., 8, 18047,
<ext-link xlink:href="https://doi.org/10.1038/s41598-018-36311-5" ext-link-type="DOI">10.1038/s41598-018-36311-5</ext-link>, 2018.</mixed-citation></ref>
      <ref id="bib1.bib37"><label>37</label><?label 1?><mixed-citation>
Padmakumari, B., Maheskumar, R. S., Harikishan, G., Morwal, S. B., Prabha,
T. V., and Kulkarni, J. R.: In situ measurements of aerosol vertical and spatial
distributions over continental India during the major drought year 2009,
Atmos. Environ., 80, 107–121, 2013.</mixed-citation></ref>
      <ref id="bib1.bib38"><label>38</label><?label 1?><mixed-citation>Panda, U. and Das, T.: Micro-structural analysis of individual aerosol coarse
particles during different seasons at an eastern coastal site in India,
Atmos. Pollut. Res.,  8, 196–207, <ext-link xlink:href="https://doi.org/10.1016/j.apr.2016.08.012" ext-link-type="DOI">10.1016/j.apr.2016.08.012</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bib39"><label>39</label><?label 1?><mixed-citation>Pandey, S. K., Vinoj, V., Landu, K., and Babu, S. S.: Declining pre-monsoon
dust loading over South Asia: Signature of a changing regional climate, Sci.
Rep., 7, 16062, <ext-link xlink:href="https://doi.org/10.1038/s41598-017-16338-w" ext-link-type="DOI">10.1038/s41598-017-16338-w</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib40"><label>40</label><?label 1?><mixed-citation>
Pillai, P. S. and Moorthy, K. K.: Aerosol mass-size distributions at a
tropical coastal environment: Response to mesoscale and synoptic processes,
Atmos. Environ., 35, 4099–4112, 2001.</mixed-citation></ref>
      <ref id="bib1.bib41"><label>41</label><?label 1?><mixed-citation>Praveen, P. S., Ahmed, T., Kar, A., Rehman, I. H., and Ramanathan, V.: Link between local scale BC emissions in the Indo-Gangetic Plains and large scale atmospheric solar absorption, Atmos. Chem. Phys., 12, 1173–1187, <ext-link xlink:href="https://doi.org/10.5194/acp-12-1173-2012" ext-link-type="DOI">10.5194/acp-12-1173-2012</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib42"><label>42</label><?label 1?><mixed-citation>
Rana, A., Jia, S., and Sarkar, S.: Black carbon aerosol in India: A
comprehensive review of current status and future prospects, Atmos. Res.,
218, 207–230, 2019.</mixed-citation></ref>
      <ref id="bib1.bib43"><label>43</label><?label 1?><mixed-citation>
Ricchiazzi, P., Yang, S., Gautier, C., and Sowle, D.: SBDART: A research and
teaching software tool for plane-parallel radiative transfer in the Earth's
atmosphere, B. Am. Meteorol. Soc., 79, 2101–2114, 1998.</mixed-citation></ref>
      <ref id="bib1.bib44"><label>44</label><?label 1?><mixed-citation>Sahu, S. K., Ohara. T., and Beig, G.: The role of coal technology in
redefining India's climate change agents and other pollutants, Environ. Res.
Lett., 12, 105006, <ext-link xlink:href="https://doi.org/10.1088/1748-9326/aa814a" ext-link-type="DOI">10.1088/1748-9326/aa814a</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib45"><label>45</label><?label 1?><mixed-citation>
Seinfeld, J. H., Bretherton, C., Carslaw, K. S., Coe, H., DeMott, P. J., Dunlea, E. J., Feingold, G.,  Ghan, S., Guenther, A. B., Kahn, R., Kraucunas, I., Kreidenweis, S. M., Molinal, M. J., Nenes, A., Penner, J. E., Prather, K. A., Ramanathan, V., Ramaswamy, V., Rasch, P. J., Ravishankara, A. R.,  Rosenfeld, D., Stephens, G., and Wood, R.: Improving our fundamental understanding of the
role of aerosol-cloud interactions in the climate system, P. Natl. Acad.
Sci. USA, 113, 5781–5790, 2016.</mixed-citation></ref>
      <ref id="bib1.bib46"><label>46</label><?label 1?><mixed-citation>Singh, A., Mahata, K. S., Rupakheti, M., Junkermann, W., Panday, A. K., and Lawrence, M. G.: An overview of airborne measurement in Nepal – Part 1: Vertical profile of aerosol size, number, spectral absorption, and meteorology, Atmos. Chem. Phys., 19, 245–258, <ext-link xlink:href="https://doi.org/10.5194/acp-19-245-2019" ext-link-type="DOI">10.5194/acp-19-245-2019</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib47"><label>47</label><?label 1?><mixed-citation>Srivastava, R.: Trends in aerosol optical properties over South Asia, Int.
J. Climatol., 37, 371–380, <ext-link xlink:href="https://doi.org/10.1002/joc.4710" ext-link-type="DOI">10.1002/joc.4710</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bib48"><label>48</label><?label 1?><mixed-citation>Storelvmo, T. and Herger, N.: Cirrus cloud susceptibility to the injection
of ice nuclei in the upper troposphere, J. Geophys. Res., 119, 2375–2389,
<ext-link xlink:href="https://doi.org/10.1002/2013JD020816" ext-link-type="DOI">10.1002/2013JD020816</ext-link>, 2014.</mixed-citation></ref>
      <ref id="bib1.bib49"><label>49</label><?label 1?><mixed-citation>
Tegen, I. and Lacis, A. A.: Modelling of particle size distribution and its
influence on the radiative properties of mineral dust aerosol, J. Geophys.
Res., 101, 19237–19244 1996.</mixed-citation></ref>
      <ref id="bib1.bib50"><label>50</label><?label 1?><mixed-citation>
Tiwari, M. K., Bajpai, S., and Dewangan, U. K.: Environmental Issues in Thermal
Power Plants – Review in Chhattisgarh Context, J. Mater. Environ. Sci.,
10, 1123–1134, 2019.</mixed-citation></ref>
      <ref id="bib1.bib51"><label>51</label><?label 1?><mixed-citation>
Vadrevu, K. P., Ellicott, E., Badarinath, K. V. S., and Vermote, E.: MODIS derived
fire characteristics and aerosol optical depth variations during the
agricultural residue burning season, north India, Environ. Pollut., 159,
1560–1569, 2011.</mixed-citation></ref>
      <ref id="bib1.bib52"><label>52</label><?label 1?><mixed-citation>Vaishya, A., Singh, P., Rastogi, S., and Babu, S. S.: Aerosol black carbon
quantification in the central Indo-Gangetic Plain: Seasonal heterogeneity
and source apportionment, Atmos. Res., 185, 13–21,
<ext-link xlink:href="https://doi.org/10.1016/j.atmosres.2016.10.001" ext-link-type="DOI">10.1016/j.atmosres.2016.10.001</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib53"><label>53</label><?label 1?><mixed-citation>Vaishya, A., Babu, S. N. S., Jayachandran, V., Gogoi, M. M., Lakshmi, N. B., Moorthy, K. K., and Satheesh, S. K.: Large contrast in the vertical distribution of aerosol optical properties and radiative effects across the Indo-Gangetic Plain during the SWAAMI–RAWEX campaign, Atmos. Chem. Phys., 18, 17669–17685, <ext-link xlink:href="https://doi.org/10.5194/acp-18-17669-2018" ext-link-type="DOI">10.5194/acp-18-17669-2018</ext-link>, 2018.</mixed-citation></ref>
      <ref id="bib1.bib54"><label>54</label><?label 1?><mixed-citation>Venkataraman, C., Habib, G., Kadamba, D., Shrivastava, M., Leon, J. F.,
Crouzille, B., Boucher, O., and Streets, D. G.: Emissions from open biomass
burning in India: Integrating the inventory approach with high-resolution
Moderate Resolution Imaging Spectroradiometer (MODIS) active-fire and land
cover data, Global Biogeochem. Cy., 20, GB2013, <ext-link xlink:href="https://doi.org/10.1029/2005GB002547" ext-link-type="DOI">10.1029/2005GB002547</ext-link>,
2006.</mixed-citation></ref>
      <ref id="bib1.bib55"><label>55</label><?label 1?><mixed-citation>Venkataraman, C., Brauer, M., Tibrewal, K., Sadavarte, P., Ma, Q., Cohen, A., Chaliyakunnel, S., Frostad, J., Klimont, Z., Martin, R. V., Millet, D. B., Philip, S., Walker, K., and Wang, S.: Source influence on emission pathways and ambient PM<inline-formula><mml:math id="M262" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> pollution over India (2015–2050), Atmos. Chem. Phys., 18, 8017–8039, <ext-link xlink:href="https://doi.org/10.5194/acp-18-8017-2018" ext-link-type="DOI">10.5194/acp-18-8017-2018</ext-link>, 2018.</mixed-citation></ref>
      <ref id="bib1.bib56"><label>56</label><?label 1?><mixed-citation>
Vipradas, M., Babu, Y. D., Garud, S., and Kumar, A.: Preparation of road map
for mainstreaming wind energy in India, TERI project report No. 2002RT66,
The Energy and Resources Institute, New Delhi, India, 2004.</mixed-citation></ref>
      <ref id="bib1.bib57"><label>57</label><?label 1?><mixed-citation>
Weingartner, E., Saathoff, H., Schnaiter, M., Streit, N., Bitnar, B., and
Baltensperger, U.: Absorption of light by soot particles: Determination of
the absorption coefficient by means of aethalometers, J. Aerosol Sci., 34,
1445–1463, 2003.</mixed-citation></ref>
      <?pagebreak page8610?><ref id="bib1.bib58"><label>58</label><?label 1?><mixed-citation>Yorks, J. E., McGill, M. J., Scott, V. S., Wake, S. W., Kupchock, A., Hlavka, D. L., Hart, W. D., and Selmer, P. A.: The Airborne Cloud–Aerosol Transport System: Overview and
Description of the Instrument and Retrieval Algorithms, J. Atmos. Ocean.
Tech., 31, 2482–2497, <ext-link xlink:href="https://doi.org/10.1175/JTECH-D-14-00044.1" ext-link-type="DOI">10.1175/JTECH-D-14-00044.1</ext-link>, 2014.</mixed-citation></ref>
      <ref id="bib1.bib59"><label>59</label><?label 1?><mixed-citation>Yorks, J. E.., McGill, M. J., Palm, S. P., Hlavka, D. L., Selmer, P. A., Nowottnick, E. P., Vaughan, M. A., Rodier, S. D., and Hart, W. D.: An overview of the CATS level 1 processing algorithms and data
products, Geophys. Res. Lett., 43, 4632–4639, <ext-link xlink:href="https://doi.org/10.1002/2016GL068006" ext-link-type="DOI">10.1002/2016GL068006</ext-link>,
2016.</mixed-citation></ref>

  </ref-list></back>
    <!--<article-title-html>Airborne in situ measurements of aerosol size distributions and black carbon across the Indo-Gangetic Plain during SWAAMI–RAWEX</article-title-html>
<abstract-html><p>During the combined South-West Asian Aerosol–Monsoon Interactions and Regional
Aerosol Warming Experiment (SWAAMI–RAWEX), collocated airborne
measurements of aerosol number–size distributions in the size (diameter)
regime 0.5 to 20&thinsp;µm and black carbon (BC) mass concentrations were
made across the Indo-Gangetic Plain (IGP), for the first time, from three
distinct locations, just prior to the onset of the Indian summer monsoon. These
measurements provided an east–west transect of region-specific properties of
aerosols as the environment transformed from mostly arid conditions of the
western IGP (represented by Jodhpur, JDR) having dominance of natural
aerosols to the central IGP (represented by Varanasi, VNS) having very high
anthropogenic emissions, to the eastern IGP (represented by the coastal
station Bhubaneswar, BBR) characterized by a mixture of the IGP outflow and
marine aerosols. Despite these, the aerosol size distribution revealed an
increase in coarse mode concentration and coarse mode mass fraction
(fractional contribution to the total aerosol mass) with the increase in
altitude across the entire IGP, especially above the well-mixed region.
Consequently, both the mode radii and geometric mean radii of the size
distributions showed an increase with altitude. However, near the surface
and within the atmospheric boundary layer (ABL), the features were specific
to the different subregions, with the highest coarse mode mass fraction
(<i>F</i><sub>MC</sub> ∼ 72&thinsp;%) in the western IGP and highest
accumulation fraction in the central IGP with the eastern IGP
in between. The elevated coarse mode fraction is attributed to mineral dust
load arising from local production as well as due to advection from the
west. This was further corroborated by data from the Cloud-Aerosol
Transport System (CATS) on board the International Space Station (ISS),
which also revealed that the vertical extent of dust aerosols reached as
high as 5&thinsp;km during this period. Mass concentrations of BC were moderate
( ∼ 1&thinsp;µg&thinsp;m<sup>−3</sup>) with very little altitude variation
up to 3.5&thinsp;km, except over VNS where very high concentrations were seen near
the surface and within the ABL. The BC-induced atmospheric heating rate was
highest near the surface at VNS ( ∼ 0.81&thinsp;K&thinsp;d<sup>−1</sup>), while
showing an increasing pattern with altitude at BBR ( ∼ 0.35&thinsp;K&thinsp;d<sup>−1</sup> at the ceiling altitude).</p></abstract-html>
<ref-html id="bib1.bib1"><label>1</label><mixed-citation>
Arnott, W. P., Hamasha, K., Moosmuller, H., Sheridan, P. J., and Ohren, J. A.:
Towards aerosol light-absorption measurements with a 7-wavelength
aethalometer: Evaluation with a photoacoustic instrument and 3-wavelength
nephelometer, Aerosol Sci. Tech., 39, 17–29, 2005.
</mixed-citation></ref-html>
<ref-html id="bib1.bib2"><label>2</label><mixed-citation>
Babu, S. S., Nair, V. S., Gogoi, M. M., and Moorthy, K. K.: Seasonal variation of
vertical distribution of aerosol single scattering albedo over Indian
sub-continent: RAWEX aircraft observations, Atmos. Environ., 125, 312–323,
<a href="https://doi.org/10.1016/j.atmosenv.2015.09.041" target="_blank">https://doi.org/10.1016/j.atmosenv.2015.09.041</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib3"><label>3</label><mixed-citation>
Banerjee, P., Satheesh, S. K., Moorthy, K. K., Nanjundiah, R. S., and Nair, V. S.:
Long-range transport of mineral dust to the Northeast Indian Ocean: regional
versus remote sources and the implications, J. Climate, 32, 1525–1549, <a href="https://doi.org/10.1175/JCLI-D-18-0403.1" target="_blank">https://doi.org/10.1175/JCLI-D-18-0403.1</a>, 2019.
</mixed-citation></ref-html>
<ref-html id="bib1.bib4"><label>4</label><mixed-citation>
Bansal, O., Singh, A., and Singh, D.: Aerosol Characteristics over the
Northwestern Indo-Gangetic Plain: Clear-Sky Radiative Forcing of Composite
and Black Carbon Aerosol, Aerosol Air Qual. Res., 19, 5–14, 2019.
</mixed-citation></ref-html>
<ref-html id="bib1.bib5"><label>5</label><mixed-citation>
Bhat, G. S., Gadgil, S., Kumar, P. V. S., Kalsi, S. R., Madhusoodanan, P.,
Murty, V. S. N., Rao, V. V. K. P., Babu, V. R., Rao, L. V. G., Rao, R. R.,
Ravichandran, R., Reddy, K. G., Rao, P. S., Sengupta, D., Sikka, D. R., Swain,
J., and Vinayachandran, P. N.: BOBMEX: The Bay of Bengal Monsoon Experiment,
B. Am. Meteorol. Soc., 82,  2217–2243, 2001.
</mixed-citation></ref-html>
<ref-html id="bib1.bib6"><label>6</label><mixed-citation>
Bhattu, D., Tripathi, S., and Chakraborty, A.: Deriving aerosol hygroscopic
mixing state from size-resolved ccn activity and HR-TOF-AMS measurements,
Atmos. Environ., 142, 57–70, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib7"><label>7</label><mixed-citation>
Brooks, J., Allan, J. D., Williams, P. I., Liu, D., Fox, C., Haywood, J., Langridge, J. M., Highwood, E. J., Kompalli, S. K., O'Sullivan, D., Babu, S. S., Satheesh, S. K., Turner, A. G., and Coe, H.: Vertical and horizontal distribution of submicron aerosol chemical composition and physical characteristics across northern India during pre-monsoon and monsoon seasons, Atmos. Chem. Phys., 19, 5615–5634, <a href="https://doi.org/10.5194/acp-19-5615-2019" target="_blank">https://doi.org/10.5194/acp-19-5615-2019</a>, 2019.
</mixed-citation></ref-html>
<ref-html id="bib1.bib8"><label>8</label><mixed-citation>
Corrigan, C. E., Ramanathan, V., and Schauer, J. J.: Impact of monsoon
transitions on the physical and optical properties of aerosols, J. Geophys.
Res., 111, D18208, <a href="https://doi.org/10.1029/2005JD006370" target="_blank">https://doi.org/10.1029/2005JD006370</a>, 2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib9"><label>9</label><mixed-citation>
Drinovec, L., Močnik, G., Zotter, P., Prévôt, A. S. H., Ruckstuhl, C., Coz, E., Rupakheti, M., Sciare, J., Müller, T., Wiedensohler, A., and Hansen, A. D. A.: The ”dual-spot” Aethalometer: an improved measurement of aerosol black carbon with real-time loading compensation, Atmos. Meas. Tech., 8, 1965–1979, <a href="https://doi.org/10.5194/amt-8-1965-2015" target="_blank">https://doi.org/10.5194/amt-8-1965-2015</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib10"><label>10</label><mixed-citation>
GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies): Scenarios for cost-effective control of air pollution and greenhouse gases in India, International Institute of Applied Systems Analysis, Laxenburg, Austria, 2010.
</mixed-citation></ref-html>
<ref-html id="bib1.bib11"><label>11</label><mixed-citation>
Gautam, R., Hsu, N. C., and Lau, K. M.: Premonsoon aerosol characterization and
radiative effects over the Indo-Gangetic Plains: Implications for regional
climate warming, J. Geophys. Res., 115, D17208, <a href="https://doi.org/10.1029/2010JD013819" target="_blank">https://doi.org/10.1029/2010JD013819</a>,
2010.
</mixed-citation></ref-html>
<ref-html id="bib1.bib12"><label>12</label><mixed-citation>
Gautam, R., Hsu, N. C., Tsay, S. C., Lau, K. M., Holben, B., Bell, S., Smirnov, A., Li, C., Hansell, R., Ji, Q., Payra, S., Aryal, D., Kayastha, R., and Kim, K. M.: Accumulation of aerosols over the Indo-Gangetic plains and southern slopes of the Himalayas: distribution, properties and radiative effects during the 2009 pre-monsoon season, Atmos. Chem. Phys., 11, 12841–12863, <a href="https://doi.org/10.5194/acp-11-12841-2011" target="_blank">https://doi.org/10.5194/acp-11-12841-2011</a>, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib13"><label>13</label><mixed-citation>
Giles, D. M., Holben, B. N., Eck, T. F., Sinyuk, A., Smirnov, A., Slutsker,
I., Dickerson, R. R., Thompson, A. M., and Schafer, J. S.: An analysis of
AERONET aerosol absorption properties and classifications representative of
aerosol source regions, J. Geophys. Res., 117, D17203,
<a href="https://doi.org/10.1029/2012JD018127" target="_blank">https://doi.org/10.1029/2012JD018127</a>, 2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib14"><label>14</label><mixed-citation>
Gogoi, M. M., Babu, S. S., Moorthy, K. K., Bhuyan, P. K., Pathak, B., Subba, T.,
Chutia, L., Kundu, S. S., Bharali, C., Borgohain, A., Guha, A., De, B. K.,
Singh, B., and Chin, M.: Radiative effects of absorbing aerosols over
northeastern India: Observations and model simulations, J. Geophys. Res.,
122, 1–26, <a href="https://doi.org/10.1002/2016JD025592" target="_blank">https://doi.org/10.1002/2016JD025592</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib15"><label>15</label><mixed-citation>
Gogoi, M. M., Lakshmi, N. B., Nair, V. S., Kompalli, S. K., Moorthy, K. K., and
Babu, S. S.: Seasonal contrast in the vertical profiles of aerosol
number concentrations and size distributions over India: implications from
RAWEX aircraft campaign, J. Earth Sys. Sc., 128, 225, <a href="https://doi.org/10.1007/s12040-019-1246-y" target="_blank">https://doi.org/10.1007/s12040-019-1246-y</a>, 2019.
</mixed-citation></ref-html>
<ref-html id="bib1.bib16"><label>16</label><mixed-citation>
Govardhan, G., Satheesh, S. K., Moorthy, K. K., and Nanjundiah, R.: Simulations of black carbon over the Indian region: improvements and implications of diurnality in emissions, Atmos. Chem. Phys., 19, 8229–8241, <a href="https://doi.org/10.5194/acp-19-8229-2019" target="_blank">https://doi.org/10.5194/acp-19-8229-2019</a>, 2019.
</mixed-citation></ref-html>
<ref-html id="bib1.bib17"><label>17</label><mixed-citation>
Guttikunda, S. K. and Jawahar, P.: Atmospheric emissions and pollution from
the coal-fired thermal power plants in India, Atmos. Environ., 92, 449–460,
<a href="https://doi.org/10.1016/j.atmosenv.2014.04.057" target="_blank">https://doi.org/10.1016/j.atmosenv.2014.04.057</a>, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib18"><label>18</label><mixed-citation>
Hopkins, R. J., Tivanski, A. V., Marten, B. D., and Gilles, M. K.: Chemical
bonding and structure of black carbon reference materials and individual
carbonaceous atmospheric aerosols, J. Aerosol Sci. 38, 573–591, 2007.
</mixed-citation></ref-html>
<ref-html id="bib1.bib19"><label>19</label><mixed-citation>
Jayachandran, V. N., Suresh Babu, S. N., Vaishya, A., Gogoi, M. M., Nair, V. S., Satheesh, S. K., and Krishna Moorthy, K.: Altitude profiles of cloud condensation nuclei characteristics across the Indo-Gangetic Plain prior to the onset of the Indian summer monsoon, Atmos. Chem. Phys., 20, 561–576, <a href="https://doi.org/10.5194/acp-20-561-2020" target="_blank">https://doi.org/10.5194/acp-20-561-2020</a>, 2020.
</mixed-citation></ref-html>
<ref-html id="bib1.bib20"><label>20</label><mixed-citation>
Kedia, S., Ramachandran, S., Holben, B. N., and Tripathi, S. N.: Quantification of
aerosol type, and sources of aerosols over the Indo-Gangetic Plain, Atmos.
Environ., 98, 607–619, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib21"><label>21</label><mixed-citation>
Kirchstetter, T. W., Novakov, T., and Hobbs, P. V.: Evidence that the
spectral dependence of light absorption byaerosols is affected by organic
carbon, J. Geophys. Res., 109, D21208, <a href="https://doi.org/10.1029/2004JD004999" target="_blank">https://doi.org/10.1029/2004JD004999</a>, 2004.
</mixed-citation></ref-html>
<ref-html id="bib1.bib22"><label>22</label><mixed-citation>
Kulkarni, J. R., Maheskumar, R. S., Morwal, S. B., Padma Kumari, B., Konwar, M., Deshpande, C. G., Joshi, R. R., Bhalwankar, R. V., Pandithurai, G., Safai, P. D., Narkhedkar, S. G., Dani, K. K., Nath, A., Nair, S., Sapre, V. V., Puranik, P.
V., Kandalgaonkar, S., Mujumdar, V. R., Khaladkar, R. M., Vijayakumar, R.,
Prabha, T. V., and Goswami, B. N.: The Cloud Aerosol Interactions and
Precipitation Enhancement Experiment (CAIPEEX): Overview and Preliminary
Results, Curr. Sci. India, 102, 413–425, 2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib23"><label>23</label><mixed-citation>
Kumar, M., Parmar, K. S., Kumar, D. B., Mhawish, A., Broday, D. M., Malla,
R. K., and Banerjeea, T.: Long-term aerosol climatology over Indo-Gangetic Plain:
Trend, prediction and potential source fields, Atmos. Environ., 180, 37–50,
2018.
</mixed-citation></ref-html>
<ref-html id="bib1.bib24"><label>24</label><mixed-citation>
Lee, L., Zhang, J., Reid, J. S., and Yorks, J. E.: Investigation of CATS aerosol products and application toward global diurnal variation of aerosols, Atmos. Chem. Phys., 19, 12687–12707, <a href="https://doi.org/10.5194/acp-19-12687-2019" target="_blank">https://doi.org/10.5194/acp-19-12687-2019</a>, 2019.
</mixed-citation></ref-html>
<ref-html id="bib1.bib25"><label>25</label><mixed-citation>
Levelt, P. F., van den Oord, G. H. J., Dobber, M. R., Mälkki, A.,
Visser, H., de Vries, J., Stammes, P., Lundell, J. O. V., and Saari, H.: The
Ozone Monitoring Instrument, IEEE T. Geosci. Remote, 44,
1093–1101, <a href="https://doi.org/10.1109/TGRS.2006.872333" target="_blank">https://doi.org/10.1109/TGRS.2006.872333</a>, 2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib26"><label>26</label><mixed-citation>
Li, Z., Lau, W. K. M., Ramanathan, V., Wu, G., Ding, Y., Manoj, M. G., Liu, J., Qian, Y., Li, J., Zhou, T., Fan, J., Rosenfeld, D., Ming, Y., Wang, Y., Huang, J., Wang, B., Xu, X., Lee, S. S., Cribb, M., Zhang, F., Yang, X., Zhao, C., Takemura, T., Wang, K., Xia, X., Yin, Y., Zhang, H., Guo, J., Zhai, P. M., Sugimoto, N., Babu, S. S., and Brasseur, G. P.: Aerosol and monsoon climate interactions over Asia, Aerosol
and monsoon climate interactions over Asia, Rev. Geophys., 54, 866–929,
<a href="https://doi.org/10.1002/2015RG000500" target="_blank">https://doi.org/10.1002/2015RG000500</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib27"><label>27</label><mixed-citation>
Liao, H. and Seinfeld, J. H.: Radiative forcing by mineral dust aerosols:
Sensitivity to key variables, J. Geophys. Res., 103, 31637–31645, 1998.
</mixed-citation></ref-html>
<ref-html id="bib1.bib28"><label>28</label><mixed-citation>
Mhawish, A., Banerjeea, T., Broday, D. M., Misra, A., and Tripathi, S. N.:
Evaluation of MODIS Collection 6 aerosol retrieval algorithms over
Indo-Gangetic Plain: Implications of aerosols types and mass loading, Remote
Sens. Environ., 201, 297–313, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib29"><label>29</label><mixed-citation>
Miller, R. L., Cakmur, R. V., Perlwitz, J. P., Geogdzhayev, I. V., Ginoux, P., Kohfeld, K. E., Koch, D., Prigent, C., Ruedy, R., Schmidt, G. A., and Tegen, I.: Mineral dust aerosols in the NASA Goddard Institute
for Space Sciences ModelE atmospheric general circulation model, J. Geophys.
Res., 111, D06208, <a href="https://doi.org/10.1029/2005JD005796" target="_blank">https://doi.org/10.1029/2005JD005796</a>, 2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib30"><label>30</label><mixed-citation>
Mitchell, J. P. and Nagel, M. W.: Time-of-flight aerodynamic particle size
analysers: their use and limitations for the evaluation of medical aerosols,
J. Aerosol Med., 12, 217–240, 1999.
</mixed-citation></ref-html>
<ref-html id="bib1.bib31"><label>31</label><mixed-citation>
Moorthy, K. K., Satheesh, S. K., and Murthy, B. V. K.: Characteristics of spectral
optical depths and size distributions of aerosols over tropical oceanic
regions, J. Atmos. Sol.-Terr. Phy., 60, 981–992, 1998.
</mixed-citation></ref-html>
<ref-html id="bib1.bib32"><label>32</label><mixed-citation>
Moorthy, K. K., Babu, S. S., Sunilkumar, S. V., Gupta, P. K., and Gera, B. S.:
Altitude profiles of aerosol BC, derived from aircraft measurements over an
inland urban location in India, Geophys. Res. Lett., 31, L22103,
<a href="https://doi.org/10.1029/2004GL021336" target="_blank">https://doi.org/10.1029/2004GL021336</a>, 2004.
</mixed-citation></ref-html>
<ref-html id="bib1.bib33"><label>33</label><mixed-citation>
Moorthy, K. K., Babu, S. S., Satheesh, S. K., Srinivasan, J., and Dutt, C. B. S.:
Dust absorption over the “Great Indian Desert” inferred using ground-based
and satellite remote sensing, J. Geophys. Res., 112, D09206,
<a href="https://doi.org/10.1029/2006JD007690" target="_blank">https://doi.org/10.1029/2006JD007690</a>, 2007.
</mixed-citation></ref-html>
<ref-html id="bib1.bib34"><label>34</label><mixed-citation>
Moorthy, K. K., Satheesh, S. K., and Kotamarthi, V. R.: Evolution of aerosol
research in India and the RAWEX–GVAX: an overview, Curr. Sci. India, 111, 53–75, <a href="https://doi.org/10.18520/cs/v111/i1/53-75" target="_blank">https://doi.org/10.18520/cs/v111/i1/53-75</a>,
2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib35"><label>35</label><mixed-citation>
Nair, V. S., Babu, S. S., Gogoi, M. M., and Moorthy, K. K.: Large-scale
enhancement in aerosol absorption in the lower free troposphere over
continental India during spring, Geophys. Res. Lett., 43, 11453–11461,
<a href="https://doi.org/10.1002/2016GL070669" target="_blank">https://doi.org/10.1002/2016GL070669</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib36"><label>36</label><mixed-citation>
Nath, R., Luo, Y., Chen, W., and Cui, X.: On the contribution of internal
variability and external forcing factors to the Cooling trend over the Humid
Subtropical Indo-Gangetic Plain in India, Sci. Rep., 8, 18047,
<a href="https://doi.org/10.1038/s41598-018-36311-5" target="_blank">https://doi.org/10.1038/s41598-018-36311-5</a>, 2018.
</mixed-citation></ref-html>
<ref-html id="bib1.bib37"><label>37</label><mixed-citation>
Padmakumari, B., Maheskumar, R. S., Harikishan, G., Morwal, S. B., Prabha,
T. V., and Kulkarni, J. R.: In situ measurements of aerosol vertical and spatial
distributions over continental India during the major drought year 2009,
Atmos. Environ., 80, 107–121, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib38"><label>38</label><mixed-citation>
Panda, U. and Das, T.: Micro-structural analysis of individual aerosol coarse
particles during different seasons at an eastern coastal site in India,
Atmos. Pollut. Res.,  8, 196–207, <a href="https://doi.org/10.1016/j.apr.2016.08.012" target="_blank">https://doi.org/10.1016/j.apr.2016.08.012</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib39"><label>39</label><mixed-citation>
Pandey, S. K., Vinoj, V., Landu, K., and Babu, S. S.: Declining pre-monsoon
dust loading over South Asia: Signature of a changing regional climate, Sci.
Rep., 7, 16062, <a href="https://doi.org/10.1038/s41598-017-16338-w" target="_blank">https://doi.org/10.1038/s41598-017-16338-w</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib40"><label>40</label><mixed-citation>
Pillai, P. S. and Moorthy, K. K.: Aerosol mass-size distributions at a
tropical coastal environment: Response to mesoscale and synoptic processes,
Atmos. Environ., 35, 4099–4112, 2001.
</mixed-citation></ref-html>
<ref-html id="bib1.bib41"><label>41</label><mixed-citation>
Praveen, P. S., Ahmed, T., Kar, A., Rehman, I. H., and Ramanathan, V.: Link between local scale BC emissions in the Indo-Gangetic Plains and large scale atmospheric solar absorption, Atmos. Chem. Phys., 12, 1173–1187, <a href="https://doi.org/10.5194/acp-12-1173-2012" target="_blank">https://doi.org/10.5194/acp-12-1173-2012</a>, 2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib42"><label>42</label><mixed-citation>
Rana, A., Jia, S., and Sarkar, S.: Black carbon aerosol in India: A
comprehensive review of current status and future prospects, Atmos. Res.,
218, 207–230, 2019.
</mixed-citation></ref-html>
<ref-html id="bib1.bib43"><label>43</label><mixed-citation>
Ricchiazzi, P., Yang, S., Gautier, C., and Sowle, D.: SBDART: A research and
teaching software tool for plane-parallel radiative transfer in the Earth's
atmosphere, B. Am. Meteorol. Soc., 79, 2101–2114, 1998.
</mixed-citation></ref-html>
<ref-html id="bib1.bib44"><label>44</label><mixed-citation>
Sahu, S. K., Ohara. T., and Beig, G.: The role of coal technology in
redefining India's climate change agents and other pollutants, Environ. Res.
Lett., 12, 105006, <a href="https://doi.org/10.1088/1748-9326/aa814a" target="_blank">https://doi.org/10.1088/1748-9326/aa814a</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib45"><label>45</label><mixed-citation>
Seinfeld, J. H., Bretherton, C., Carslaw, K. S., Coe, H., DeMott, P. J., Dunlea, E. J., Feingold, G.,  Ghan, S., Guenther, A. B., Kahn, R., Kraucunas, I., Kreidenweis, S. M., Molinal, M. J., Nenes, A., Penner, J. E., Prather, K. A., Ramanathan, V., Ramaswamy, V., Rasch, P. J., Ravishankara, A. R.,  Rosenfeld, D., Stephens, G., and Wood, R.: Improving our fundamental understanding of the
role of aerosol-cloud interactions in the climate system, P. Natl. Acad.
Sci. USA, 113, 5781–5790, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib46"><label>46</label><mixed-citation>
Singh, A., Mahata, K. S., Rupakheti, M., Junkermann, W., Panday, A. K., and Lawrence, M. G.: An overview of airborne measurement in Nepal – Part 1: Vertical profile of aerosol size, number, spectral absorption, and meteorology, Atmos. Chem. Phys., 19, 245–258, <a href="https://doi.org/10.5194/acp-19-245-2019" target="_blank">https://doi.org/10.5194/acp-19-245-2019</a>, 2019.
</mixed-citation></ref-html>
<ref-html id="bib1.bib47"><label>47</label><mixed-citation>
Srivastava, R.: Trends in aerosol optical properties over South Asia, Int.
J. Climatol., 37, 371–380, <a href="https://doi.org/10.1002/joc.4710" target="_blank">https://doi.org/10.1002/joc.4710</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib48"><label>48</label><mixed-citation>
Storelvmo, T. and Herger, N.: Cirrus cloud susceptibility to the injection
of ice nuclei in the upper troposphere, J. Geophys. Res., 119, 2375–2389,
<a href="https://doi.org/10.1002/2013JD020816" target="_blank">https://doi.org/10.1002/2013JD020816</a>, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib49"><label>49</label><mixed-citation>
Tegen, I. and Lacis, A. A.: Modelling of particle size distribution and its
influence on the radiative properties of mineral dust aerosol, J. Geophys.
Res., 101, 19237–19244 1996.
</mixed-citation></ref-html>
<ref-html id="bib1.bib50"><label>50</label><mixed-citation>
Tiwari, M. K., Bajpai, S., and Dewangan, U. K.: Environmental Issues in Thermal
Power Plants – Review in Chhattisgarh Context, J. Mater. Environ. Sci.,
10, 1123–1134, 2019.
</mixed-citation></ref-html>
<ref-html id="bib1.bib51"><label>51</label><mixed-citation>
Vadrevu, K. P., Ellicott, E., Badarinath, K. V. S., and Vermote, E.: MODIS derived
fire characteristics and aerosol optical depth variations during the
agricultural residue burning season, north India, Environ. Pollut., 159,
1560–1569, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib52"><label>52</label><mixed-citation>
Vaishya, A., Singh, P., Rastogi, S., and Babu, S. S.: Aerosol black carbon
quantification in the central Indo-Gangetic Plain: Seasonal heterogeneity
and source apportionment, Atmos. Res., 185, 13–21,
<a href="https://doi.org/10.1016/j.atmosres.2016.10.001" target="_blank">https://doi.org/10.1016/j.atmosres.2016.10.001</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib53"><label>53</label><mixed-citation>
Vaishya, A., Babu, S. N. S., Jayachandran, V., Gogoi, M. M., Lakshmi, N. B., Moorthy, K. K., and Satheesh, S. K.: Large contrast in the vertical distribution of aerosol optical properties and radiative effects across the Indo-Gangetic Plain during the SWAAMI–RAWEX campaign, Atmos. Chem. Phys., 18, 17669–17685, <a href="https://doi.org/10.5194/acp-18-17669-2018" target="_blank">https://doi.org/10.5194/acp-18-17669-2018</a>, 2018.
</mixed-citation></ref-html>
<ref-html id="bib1.bib54"><label>54</label><mixed-citation>
Venkataraman, C., Habib, G., Kadamba, D., Shrivastava, M., Leon, J. F.,
Crouzille, B., Boucher, O., and Streets, D. G.: Emissions from open biomass
burning in India: Integrating the inventory approach with high-resolution
Moderate Resolution Imaging Spectroradiometer (MODIS) active-fire and land
cover data, Global Biogeochem. Cy., 20, GB2013, <a href="https://doi.org/10.1029/2005GB002547" target="_blank">https://doi.org/10.1029/2005GB002547</a>,
2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib55"><label>55</label><mixed-citation>
Venkataraman, C., Brauer, M., Tibrewal, K., Sadavarte, P., Ma, Q., Cohen, A., Chaliyakunnel, S., Frostad, J., Klimont, Z., Martin, R. V., Millet, D. B., Philip, S., Walker, K., and Wang, S.: Source influence on emission pathways and ambient PM<sub>2.5</sub> pollution over India (2015–2050), Atmos. Chem. Phys., 18, 8017–8039, <a href="https://doi.org/10.5194/acp-18-8017-2018" target="_blank">https://doi.org/10.5194/acp-18-8017-2018</a>, 2018.
</mixed-citation></ref-html>
<ref-html id="bib1.bib56"><label>56</label><mixed-citation>
Vipradas, M., Babu, Y. D., Garud, S., and Kumar, A.: Preparation of road map
for mainstreaming wind energy in India, TERI project report No. 2002RT66,
The Energy and Resources Institute, New Delhi, India, 2004.
</mixed-citation></ref-html>
<ref-html id="bib1.bib57"><label>57</label><mixed-citation>
Weingartner, E., Saathoff, H., Schnaiter, M., Streit, N., Bitnar, B., and
Baltensperger, U.: Absorption of light by soot particles: Determination of
the absorption coefficient by means of aethalometers, J. Aerosol Sci., 34,
1445–1463, 2003.
</mixed-citation></ref-html>
<ref-html id="bib1.bib58"><label>58</label><mixed-citation>
Yorks, J. E., McGill, M. J., Scott, V. S., Wake, S. W., Kupchock, A., Hlavka, D. L., Hart, W. D., and Selmer, P. A.: The Airborne Cloud–Aerosol Transport System: Overview and
Description of the Instrument and Retrieval Algorithms, J. Atmos. Ocean.
Tech., 31, 2482–2497, <a href="https://doi.org/10.1175/JTECH-D-14-00044.1" target="_blank">https://doi.org/10.1175/JTECH-D-14-00044.1</a>, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib59"><label>59</label><mixed-citation>
Yorks, J. E.., McGill, M. J., Palm, S. P., Hlavka, D. L., Selmer, P. A., Nowottnick, E. P., Vaughan, M. A., Rodier, S. D., and Hart, W. D.: An overview of the CATS level 1 processing algorithms and data
products, Geophys. Res. Lett., 43, 4632–4639, <a href="https://doi.org/10.1002/2016GL068006" target="_blank">https://doi.org/10.1002/2016GL068006</a>,
2016.
</mixed-citation></ref-html>--></article>
