ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-17-257-2017Variations in O3, CO, and CH4 over the Bay of Bengal during the
summer monsoon season: shipborne measurements and model simulationsGirachImran A.imran.girach@gmail.comOjhaNarendranarendra.ojha@mpic.dehttps://orcid.org/0000-0002-8840-5699NairPrabha R.PozzerAndreahttps://orcid.org/0000-0003-2440-6104TiwariYogesh K.KumarK. Ravihttps://orcid.org/0000-0001-6222-004XLelieveldJoshttps://orcid.org/0000-0001-6307-3846Space Physics Laboratory, Vikram Sarabhai Space Centre,
Thiruvananthapuram 695022, IndiaDepartment of Atmospheric Chemistry, Max Planck Institute for
Chemistry, Mainz 55128, GermanyIndian Institute of Tropical Meteorology, Pune 411 008, IndiaNational Institute of Polar Research, Tachikawa, JapanDepartment of Environmental Geochemical Cycle Research, JAMSTEC,
Yokohama, JapanImran A. Girach (imran.girach@gmail.com) and
Narendra Ojha (narendra.ojha@mpic.de)5January20171712572757July201613July201617November20168December2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/17/257/2017/acp-17-257-2017.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/17/257/2017/acp-17-257-2017.pdf
We present shipborne measurements of surface ozone (O3), carbon
monoxide (CO), and methane (CH4) over the Bay of Bengal (BoB), the first
time such measurements have been performed during the summer monsoon season,
as a part of the Continental Tropical Convergence Zone (CTCZ) experiment
during 2009. O3, CO, and CH4 mixing ratios exhibited significant
spatial and temporal variability in the ranges of 8–54 nmol mol-1,
50–200 nmol mol-1, and 1.57–2.15 µmol mol-1, with means
of 29.7 ± 6.8 nmol mol-1, 96 ± 25 nmol mol-1, and
1.83 ± 0.14 µmol mol-1, respectively. The average mixing
ratios of trace gases over BoB in air masses from central/northern India
(O3: 30 ± 7 nmol mol-1; CO:
95 ± 25 nmol mol-1;
CH4: 1.86 ± 0.12 µmol mol-1) were not statistically
different from those in air masses from southern India (O3: 27 ± 5 nmol mol-1; CO:
101 ± 27 nmol mol-1; CH4: 1.72 ± 0.14 µmol mol-1). Spatial variability is observed to be most
significant for CH4 with higher mixing ratios in the air masses from
central/northern India, where higher CH4 levels are seen in the
SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric
CartograpHY) data. O3 mixing ratios over the BoB showed large
reductions (by ∼ 20 nmol mol-1) during four rainfall
events. Temporal changes in the meteorological parameters, in conjunction
with O3 vertical profile, indicate that these low-O3 events are
associated with downdrafts of free-tropospheric O3-poor air masses.
While the observed variations of O3 and CO are successfully reproduced
using the Weather Research and Forecasting model with Chemistry (WRF-Chem),
this model overestimates mean concentrations by about 6 and 16 % for
O3 and CO, respectively, generally overestimating O3 mixing ratios
during the rainfall events. An analysis of modelled O3 along air mass
trajectories show mean en route O3 production rate of about 4.6 nmol mol-1 day-1 in the outflow towards the BoB. Analysis of the
various tendencies from model simulations during an event on 10 August
2009, reproduced by the model, shows horizontal advection rapidly
transporting O3-rich air masses from near the coast across the BoB. This
study fills a gap in the availability of trace gas measurements over the
BoB and, when combined with data from previous campaigns, reveals large
seasonal amplitude (∼ 39 and ∼ 207 nmol mol-1 for O3 and CO, respectively) over the northern BoB.
Introduction
Tropospheric ozone (O3) is the third most important greenhouse gas,
contributing to global warming and climate change with a radiative forcing of
0.40 ± 0.20 Wm-2 (IPCC, 2013). O3 is also a pivotal trace gas
in tropospheric chemistry, as it is a major source of hydroxyl radical (OH),
which removes most of the organic compounds and pollutants from the
atmosphere and controls the oxidation capacity of the troposphere (e.g.
Brasseur et al., 1999; Finlayson-Pitts and Pitts, 2003; Seinfeld and Pandis,
2006). Further, enhanced concentrations of surface O3 have detrimental
effects on human health and vegetation (Heagle, 1989; Seinfeld and Pandis,
2006). Approximately 80 % of tropospheric O3 is produced by in situ
photochemical reactions in the presence of nitrogen oxides (NOx= NO + NO2) involving the precursor gases of methane, non-methane
hydrocarbons (NMHCs), and CO (Fishman et al., 1979; Crutzen et al., 1999;
Seinfeld and Pandis, 2006). The remaining 20 % of tropospheric O3 is
attributed to intrusions of stratospheric air during frontal activities or to
tropopause folding events (Lelieveld and Dentener, 2000; Sprenger et al.,
2007). Depending upon meteorological conditions and the availability of the
aforementioned precursors, a net production or destruction of O3
prevails. The average lifetime of O3 is about 1 week in the lower
troposphere, which leads to large variability in its spatial and temporal
distributions, as compared to the long-lived greenhouse gases. The budget of
tropospheric O3 and its implications for human health, crop yields, and
climate are, however, not yet well quantified, especially over regions in
Asia. This is mainly due to a lack of in situ measurements (e.g. Cooper et
al., 2014; Monks et al., 2015).
Carbon monoxide (CO) is an indirect greenhouse gas which also has adverse
effects on the health of humans and animals (WHO, 1999). Although it does not
have a direct greenhouse effect like methane and carbon dioxide, its role in
atmospheric chemistry is estimated to cause an indirect radiative forcing of
0.23 (0.18–0.29) Wm-2 (IPCC, 2013). The major sources of CO are fossil
fuel combustion, biomass burning, and oxidation of hydrocarbons such as
CH4 and isoprene (e.g. Jacob, 1999; Bergamaschi et al., 2000; Seinfeld
and Pandis, 2006).
Methane (CH4) is one of the major greenhouse gases, with a direct
radiative forcing of 0.48 ± 0.05 Wm-2 (IPCC, 2013). This gas plays
a major role in the climate and in atmospheric chemistry. CH4 is
emitted from variety of natural and anthropogenic sources (Jacob, 1999) and
is removed primarily through its reaction with OH radicals (Fung et al.,
1991; Seinfeld and Pandis, 2006).
The marine regions adjoining South Asia have been observed to have elevated
levels of surface O3 due to the outflow of continental pollution
(Lawrence and Lelieveld, 2010) and minimal chemical loss by titration (e.g.
Lal and Lawrence, 2001; Ojha et al., 2012). Suggested sources for this
elevated O3 and other trace gases observed over the marine regions
surrounding India are anthropogenic, biomass burning, and biogenic emissions
over continental India (Naja et al., 2004; Lawrence and Lelieveld, 2010;
Nair et al., 2011; David et al., 2011). The air masses influenced by
continental emissions undergo chemical transformation, including O3
production, during their transport to the cleaner marine regions. In situ
measurements over the marine regions are required to understand the effects
of direct outflow, en route chemical transformation, and the chemistry in
the transported air masses (Lawrence and Lelieveld, 2010, and references
therein).
The experiments that have been conducted to date over the marine environment
adjacent to the Indian region have revealed considerable spatial
heterogeneity in the distribution of trace gases and aerosols, influences
from source regions such as the Indo-Gangetic Plain (IGP), and radiative
impacts (Nair et al., 2010, 2011; David et al., 2011; Mallik et al., 2013; Moorthy
et al., 2009). Observations made during the Indian Ocean
Experiment (INDOEX; Lal and Lawrence, 2001) and model simulations (Ojha et
al., 2012) both found the O3 mixing ratios over these remote marine
regions to be even higher than those over the upwind continental regions
due to complex O3 chemistry. Lawrence and Lelieveld (2010) provided a
detailed review of the outflow of trace gases and aerosols from South Asia
to the surrounding marine regions. Transport of air masses between the Indian
subcontinent and the adjacent marine regions has strong seasonal dependence
associated with the monsoonal circulation (e.g. Kumar et al., 2015a).
The marine environment of the Bay of Bengal (BoB), the largest bay in the
world, is surrounded by landmasses on three sides, making it highly suitable
to observe enhanced concentrations of trace species. Further, seasonal
changes in synoptic winds make this a unique region to study variations in
trace species due to transport and en route photochemistry. Considering the
aforementioned special characteristics of the BoB, as well as the
considerable heterogeneity of trace gas and aerosol distribution, in situ
measurements covering large areas are essential for investigating the
distribution of pollutants and the controlling processes. Extensive in situ
measurements of various trace gases over the BoB have been conducted in the
following field campaigns: INDOEX during the winter months of 1998 and 1999
(Lelieveld et al., 2001; Mühle et al., 2002); the Integrated Campaign for
Aerosols, gases, and Radiation Budget (ICARB) during the March–May
(pre-monsoon season) of 2006 (Nair et al., 2011; Srivastava et al., 2011, 2012); the winter-ICARB (W-ICARB) during
December–January 2009 (Girach and Nair, 2010, 2014; David et al., 2011);
the Bay of Bengal Experiment (BOBEX)-I during February–March 2001 (Lal et
al., 2006); the Bay of Bengal Process Studies (BOBPS) during
September–October 2002 (Sahu et al., 2006); BOBEX–II during February 2003
(Lal et al., 2007); and the other campaign conducted during
October–November 2010 (Mallik et al., 2013).
Cruise track (continuous black line) of the Research Vessel
Sagar Kanya along with synoptic winds at 925 hPa (black thin
arrows) and NOx emissions in background colour map. The dates
corresponding to approximate ship positions are marked along the track. The
start and end position of the cruise, stationary position of the ship, and
Thiruvananthapuram are shown by the circle, triangle and square,
respectively.
Although earlier studies have covered the spatio-temporal distribution of
trace gases during most seasons over the BoB, there is still a lack of
observations over the BoB during the summer monsoon season (June–August).
The Asian summer monsoon circulation provides a pathway for pollution
transport into the stratosphere (Randel et al., 2010), and observations
taken during monsoon season capture a time of high water-vapour loading over
the BoB. Deep convection during the summer monsoon can uplift boundary layer
pollution to higher altitudes; the pollution is then distributed over a larger
region, thereby influencing air quality and climate over much larger regions
(Lawrence and Lelieveld, 2010), extending as far as, for example, over the
Mediterranean (e.g. Lelieveld et al., 2002; Scheeren et al., 2003). Such in
situ measurements are also essential given the fact that satellite remote
sensing of boundary layer O3 has relatively higher uncertainty. The
uncertainties in satellite retrievals of trace species are particularly high
during the summer monsoon season, as the view of satellite instruments is
frequently obscured by thick clouds.
In the present paper, the ship-based measurements of surface O3, CO,
and CH4 over the BoB are presented for the summer monsoon season of
2009. These observations were carried out as a part of the Continental
Tropical Convergence Zone (CTCZ) experiment (http://www.incois.gov.in/portal/datainfo/pdctcz.jsp) under
the Indian Climate Research Programme (ICRP) of the Government of India. In
this study, the spatial and temporal variations of O3 over the BoB and
the effects of transport are analysed. These observations are compared with
simulations from a regional model, Weather Research and Forecasting coupled
with Chemistry (WRF-Chem). The sharp reductions observed in O3 during
rainfall events are investigated in greater detail.
The cruise track and background conditions
Figure 1 shows the cruise track of the Oceanic Research Vessel (ORV)
Sagar Kanya during the CTCZ campaign (cruise number SK 261). The
arrows marked on the track show the direction of the ship, which sailed from
Chennai (80.3∘ E, 13.1∘ N; marked by a circle) on 16 July
2009. The cruise offered greater coverage in the northern BoB than the
southern or central BoB areas. To take time series measurements, the ship
was kept stationary for 15 days (22 July to 6 August 2009) at
89∘ E, 19∘ N as marked by a triangle in the figure.
After several tracks, covering latitude sector 11.0 to 21.1∘ N and
longitude sector 80.3 to 90.1∘ E, the cruise ended on 17 August
2009 at Chennai, for a total of 32 days of voyage. The average wind pattern
at 925 hPa (NCEP/NCAR reanalysis; http://www.esrl.noaa.gov/psd) during the
cruise period is shown in Fig. 1. The prevailing westerly and
southwesterly winds transport O3 and its precursors from the Indian
landmass to the BoB during the study period. The spatial distribution of
emissions of NOx, an O3 precursor gas, is also shown as colour map
in Fig. 1. NOx emissions are obtained from the Intercontinental
Chemical Transport Experiment Phase B (INTEX-B) inventory (Zhang et al.,
2009), which is representative of the year 2006. NOx emissions are
relatively higher over parts of eastern and southern India as compared to
central India. The square tagged as Thiruvananthapuram shows the location
corresponding to the measurements shown in Fig. 9.
Experimental details and data
Surface O3 measurements were carried out using an online ultraviolet
(UV) photometric ozone analyzer (model O3 42), manufactured by Environnement
S.A, France. The analyser utilises the absorption of UV radiation by O3
molecules at 253.7 nm and derives O3 mixing ratios using the
Beer–Lambert law. This UV absorption-based analyser has an uncertainty of
about 5 % (Tanimoto et al., 2007), corresponding to ∼ 1.5 nmol mol-1 for
the observed range of O3. Zero noise of the instrument
is 0.5 nmol mol-1. The instrument has a lower detection limit of 1 nmol mol-1 and a linearity of ±1 %. An individual measurement is
performed at a minimum response time of 10 s. The analyzer was
operated on auto-response mode, whereby responses could be 10–90 s
depending upon changes in O3 mixing ratios. However, data were recorded
continuously at 5 min intervals.
Spatial variation of surface O3(a), CO (b), and CH4(c) mixing ratios along the cruise track during the CTCZ campaign.
WRF-Chem simulated spatial distribution of surface O3(d) and CO
(e) averaged during 16 July–17 August 2009.
CO measurements were made using an online CO analyzer (model CO12 Module)
manufactured by Environnement S.A, France. This instrument works on the
principle of nondispersive infrared (NDIR) absorption by CO molecules at
the wavelength of 4.67 µm. The instrument has a lower detection limit
of 50 nmol mol-1, a linearity of 1 %, and a response time of 40 s. The overall uncertainty in hourly CO measurements is estimated to
be ∼ 10 % at a CO value of 150 nmol mol-1 (Sawa et al.,
2007; Tanimoto et al., 2007).
Air was drawn from a height of approximately 15 m above the sea surface
through a Teflon tube. Before and after the cruise, both analyzers were
calibrated, with calibration factors not found to be significantly changed.
The calibrations of both analysers were carried out using appropriate
calibration standards traceable to NIST and a multi-channel calibrator,
following the procedure mentioned in the manuals of analysers. While the O3
analyser was calibrated for mixing ratios of 30 nmol mol-1, the CO
analyser was calibrated for mixing ratios of 1.1 µmol mol-1.
Meteorological parameters such as pressure, temperature, and relative
humidity were measured continuously on board the ship. Trace gas measurements
affected by the ship exhaust were identified and discarded using on-board
wind direction and NOx measurements.
In addition, a total of 29 air samples were collected in 1 L glass
flasks during the cruise and were analysed for CH4 using a gas
chromatograph (GC) coupled with a flame ionisation detector (FID), as
described in Tiwari and Ravi Kumar (2011). These CH4 measurements are
traceable to the WMO standard scale. CH4 standards were obtained from
the WMO Central Calibration Laboratory (CCL) at the National Oceanic and
Atmospheric Administration (NOAA)/Earth System Research Laboratory
(ESRL)/Global Monitoring Division (GMD), located in Boulder, Colorado, USA.
The precision for CH4 measurements was approximately ±0.1 µmol mol-1. A detailed description of the analytical procedure
for CH4 measurement and calibration of GC is given in Ravikumar et al. (2014).
To further study the observed low-O3 events over BoB, measurements made
at Thumba, Thiruvananthapuram, are used as a case study. Using the same
O3 analyzer as the one used for surface O3 measurements over BoB,
continuous measurements of surface O3 were taken at Thumba,
Thiruvananthapuram (David and Nair, 2011; Girach et al., 2012), in July 2011.
Along with various meteorological parameters, rainfall measurements were
also taken at Thumba at 5 min of integration time using an automatic
weather station manufactured by Dynalab Weathertech Pvt. Ltd, India. The
site, Thumba, is situated just ∼ 500 m away from the west
coast, with sandy terrain, and is a less populated area in the city of
Thiruvananthapuram (8.5∘ N, 76.9∘ E) at southern tip of
India. For more details about the Thumba site and measurements please see,
for example, Nair et al. (2002) and David and Nair (2011).
A vertical profile of O3 was measured on 28 July 2011 at Thumba using
an electrochemical concentration cell ozonesonde (EN-SCI 2ZV7 ECC; Komhyr,
1969; Komhyr et al., 1995). The accuracy of such ozonesondes is reported to be about
±5–10 % up to ∼ 30 km (Smit et al., 2007). More
details of this measurement technique can be found in Ojha et al. (2014).
The accumulated rainfall for every 3 h interval from the Tropical
Rainfall Measuring Mission (TRMM; with a horizontal grid size of
0.25∘× 0.25∘) is also utilised in this study
to complement the on-board rainfall measurements. The 3B42 algorithm is used
to calculate precipitation and root-mean-square precipitation-error
estimates; these two estimates were then used to compute hourly and daily
rainfall estimates (Huffman et al., 1995).
The gridded (2∘× 2∘) monthly column-averaged
CH4 (level 3, version 6) retrievals from SCIAMACHY (SCanning Imaging
Absorption spectroMeter for Atmospheric CartograpHY) instrument on board the
Envisat satellite were used to infer concentrations over Indian land
regions. The IMAP-DOAS (iterative maximum a posteriori differential
optical absorption spectroscopy) algorithm was used, which retrieves CH4
utilising the spectra (i.e. 1000–1750 nm) from the near infrared
channel no. 6 (Frankenberg et al., 2005).
The WRF-Chem options used for parameterisation of atmospheric
processes.
Atmospheric processScheme usedFeatures of the schemeCloud microphysicsLin et al. schemeSophisticated parameterisation including ice, snow, and(Lin et al., 1983)graupel processes; suitable for high-resolution simulations.Longwave radiationRapid Radiative TransferAccurate scheme utilises look-up tables for efficiency andModel (RRTM; Mlawer et al., 1997)accounts for multiple bands and microphysical properties.Shortwave radiationGoddard shortwave schemeTwo-stream multi-band scheme using O3(Chou and Suarez, 1994)from climatology and includes cloud effects.Surface layerMonin–Obukhov schemeBased on Monin–Obukhov with Zilitinkevich thermal roughness(Janjic, 1996)length and standard similarity functions from look-up tables.Land surface optionNoah land surface modelUnified NCEP/NCAR/AFWA scheme with soil(Chen and Dudhia, 2001)temperature and moisture in four layers, fractionalsnow cover and frozen soil physics. This includes themodifications for better representation of processesover ice sheets and snow covered areas.Urban surface physicsUrban canopy modelThree-category urban canopy model with surfaceeffects for roofs, walls and streets.Planetary boundary layerMellor–Yamada–JanjicOne-dimensional prognostic turbulent kineticscheme (Janjic, 2002)energy scheme; local vertical mixing is included.Cumulus parameterisationGrell 3D ensemble schemeImproved version of the GD scheme suitable(Grell, 1993; Grell and Devenyi, 2002)for coarse as well as high-resolution simulations.Model simulations
WRF-Chem (Grell
et al., 2005) version 3.5.1 was used to simulate meteorological and chemical
fields during the campaign period. The model domain (Fig. 2d–e) is defined
on the Mercator projection, centred at 80∘ E, 15.5∘ N,
at a spatial resolution of 15 km × 15 km. The model has 51 vertical levels
from surface to 10 hPa. The simulations were conducted for the period of
29 June to 31 August 2009, covering the complete measurement period. The
meteorological inputs have been adopted from ERA-Interim reanalyses by the
ECMWF. Horizontal winds, temperature, and water vapour are nudged above the
planetary boundary layer using a nudging coefficient of 0.0003 s-1 (Kumar et al., 2015b), employing the four-dimensional data assimilation
(FDDA) technique. Anthropogenic emissions of CO, NOx, SO2, and
NMVOCs are provided by a regional emission inventory that was developed to
support INTEX-B (Zhang et al., 2009; Kumar et al., 2012b; Ojha et al., 2016). This
inventory is representative of the year 2006. Aerosol emissions are provided
by the Hemispheric Transport of Air Pollution (HTAP v2) inventory
(Janssens-Maenhout et al., 2015). Biomass burning emissions from NCAR Fire
Inventory (FINN; Wiedinmyer et al., 2011) and biogenic emissions calculated
online using MEGAN (Guenther et al., 2006) were used in the simulations.
Gas-phase chemistry in the model is represented by the second-generation
Regional Acid Deposition Model (RADM2; Stockwell et al., 1990), and the
aerosol module is based on MADE SORGAM (Binkowski and Shankar, 1995;
Ackermann et al., 1998; Schell et al., 2001). Initial and boundary
conditions for chemical fields are provided by the MOZART-4/GEOS5 data. The
options used to parameterise different atmospheric processes are given in
Table 1. For more information about meteorological nudging, chemical
mechanisms, emissions, boundary conditions, and evaluation of WRF-Chem
against in situ measurements and satellite data over the Indian region,
please see, for example, Kumar et al. (2012a, b, 2015a, b), Ansari et al. (2016), and Ojha et al. (2016). Model-simulated mean spatial distributions
of O3 and CO over the model domain during the study period are shown in
Fig. 2d–e.
Five-day air mass back trajectories during the study period ending
at the measurement locations (small black circles) grouped for corresponding
air masses from (a) central/northern India and (b) southern India. The cross
symbols along the trajectories represent each back-day. The colour scale
shows the height (in km) of the trajectories.
Variations in observed CH4(a), CO (b), O3(c), and
percentage residence time over land (d) along with WRF-Chem simulated
O3 and CO (blue line) during the campaign. Events of sharp decrease in
O3 during rainfall are marked by vertical red lines (Fig. 8).
(e) Variations in measurement locations.
Results and discussionVariations in O3, CO, and CH4 over the BoB
Figure 2a–c show the observed variations in O3, CO, and CH4 along
the ship track during 16 July to 17 August 2009. The mixing ratios of
trace gases show large spatio-temporal variations over the BoB. Levels of
O3 and CO varied in the ranges of 8–54 (average of
29.7 ± 6.8 nmol mol-1) and 50–200 nmol mol-1 (average of
96 ± 25 nmol mol-1), respectively. As CO mixing ratios below the
detection limit of the instrument are discarded from the analysis, the
reported minimum and average values of CO mixing ratios are therefore
slightly higher than their actual values. CH4 mixing ratios are
observed to range from 1.57 to 2.15 µmol mol-1, with an average of
1.83 ± 0.14 nmol mol-1. Average CH4 mixing ratios showed a
significant difference of ∼ 0.14 µmol mol-1
between northern (81–91∘ E, 16–21.5∘ N) and central
(80–91∘ E, 11–16∘ N) BoB during the study period. In
addition to sailing across the BoB, the ship was also kept stationary for
15 days, from 22 July to 6 August 2009 at 89∘ E,
19∘ N. During this time period, surface O3, CO, and CH4 mixing ratios are observed to fall into the
range of 9–46 nmol mol-1, 58–144 nmol mol-1, and 1.71–1.89 µmol mol-1,
respectively, with temporally averaged mixing ratios of 28 ± 7 nmol mol-1, 91 ± 19 nmol mol-1, and
1.81 ± 0.06 µmol mol-1, respectively.
The HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model
was used to simulate 5-day backward air mass trajectories arriving at 500 m (a height that falls within the marine atmospheric boundary layer) above
the measurement locations (Draxler and Rolph, 2003; Rolph, 2003; http://www.arl.noaa.gov/ready.html), as shown in the Fig. 3. Trajectories
are colour-coded to show the altitude variations of the air parcels along
their path. The influences of two different air masses are observed over the
BoB during the CTCZ experiment. Over the central BoB, the backward air
trajectories cross southern India (i.e. < 13∘ N), where a
belt of elevated anthropogenic emissions (5–20 mol km-2 h-1 of
NOx; see Fig. 1) is located. In contrast, most of the air trajectories
over northern BoB come across the central Indian region, where anthropogenic
emissions are relatively lower. For example, with the exception of a few
hotspots, NOx emissions north of 13∘ N are in the range of
1–10 mol km-2 h-1 (Fig. 1). The O3 and CO mixing ratios
over BoB in air masses from central/northern India (Fig. 3a) are slightly
higher or comparable (O3: 30 ± 7; CO: 95 ± 25 nmol mol-1) to those (O3: 27 ± 5; CO:
101 ± 27 nmol mol-1) in air masses from southern India (Fig. 3b).
The observed spatio-temporal variations of trace gases are investigated by
calculating the fractional residence time of air masses over land, using
HYSPLIT simulated 5-day backward air trajectories. Figure 4a–c show the
temporal variations of O3, CO, and CH4 during the CTCZ experiment
along the cruise track. The percentage of time of air masses over continental
India is also shown (Fig. 4d), as estimated by the ratio of residence time
over land to the total trajectory time of 5 days. The hours of residence
have only been included in the analysis if the altitude along trajectory is
less than 1.5 km, as the surface emissions might not been directly influence
the air masses aloft. Red vertical bars depict the sharp reductions in
O3 mixing ratios associated with rainfall events (see Sect. 5.3).
O3, CO, and CH4 show correlated variability with the estimated
residence times over the Indian subcontinent with slightly higher
correlation in the case of primary species (R2= 0.16 in case of CO
and CH4), as compared to O3 (R2= 0.09). Similar variations
in mixing ratios of these trace gases and residence time over continental
India indicate the influences of transport from the Indian subcontinent on
the observed spatio-temporal variations over the BoB during the summer
monsoon season. The occasions on which such a one-to-one correspondence are
not observed can be attributed to varying source strengths, vertical mixing
or dilution, and en route photochemistry.
A comparison of averaged surface O3 mixing ratios measured at
various sites during summer monsoon period.
ObservationLongitudeLatitudeObservation periodSurfaceReferencesite(∘ E)(∘ N)daytime O3(mean ± standarddeviation)Arabian Sea Arabian Sea69–769–19July–August 20029Ali et al. (2009)Western coast of India Thiruvananthapuram76.98.5August 200923 ± 7Present studyThiruvananthapuram76.98.5June–August 200819 ± 6David and Nair (2011)Kannur75.411.9July 2010–201111 ± 4Nishanth et al. (2014)MtAbu (1.6 km a.m.s.l.)72.724.6August 1993–200025 ± 9Naja et al. (2003)Ahmedabad72.623July 1991–1995,22 ± 8,Lal et al. (2000);August 1991–1995,17 ± 4,Srivastava et al. (2012)July–August 2003–200725*Central India Anantapur77.6514.62July 200930 ± 2Reddy et al. (2011)Eastern coast of India Bhubaneswar86.420.5June–August 2011–201229 ± 6Mahapatra et al. (2014)Bay of Bengal Bay of Bengal80.3–90.111–21.1July–August 200930 ± 7Present study
* Boundary layer O3
over the Arabian Sea.
Generally, during the summer monsoon season, relatively cleaner marine
air masses from the Arabian Sea are transported to the Indian region. These
air masses are then exposed to regional emissions and subjected to
photochemistry depending upon the availability of solar insolation under the
cloudy conditions of monsoon. The air masses in which precursors have
accumulated, and to some extent photochemically processed, outflows into
the BoB. As a result, the air masses outflowing at the eastern coast of
India could have higher O3 mixing ratios than the background air coming
from the Arabian Sea into the western coast of India. The difference between
these two values is representative of the O3 build-up that can be
attributed to regional pollution; this difference would also reflect the
extent of photochemical processing that would have taken place.
As the observational site Thumba, Thiruvananthapuram, is situated just at
the Arabian Sea coast, the monsoon-time observations here could be
approximated to represent the background O3 mixing ratios entering from
the Arabian Sea. In August 2009, using only daytime monthly average O3,
the O3 at Thumba during the monsoon season was observed to be 23 ± 7 nmol mol-1. Since the objective of investigation is the additional
O3 over the BoB produced by en route photochemistry, daytime O3 values at Thiruvananthapuram are therefore compared with all the
observations over the BoB. The average mixing ratio observed over the BoB
during monsoon season for 16 July–17 August 2009 was 30 ± 7 nmol mol-1, which was ∼ 7 nmol mol-1 higher than the
Arabian Sea air mass. This additional amount of ∼ 7 nmol mol-1 could be attributed to the effects of regional and en route
photochemical O3 production. Net O3 production rate in the outflow
is estimated to be in the range of 1.5–4 nmol mol-1 day-1. Note
that the O3 mixing ratio is reported to be ∼ 30 ± 2 nmol mol-1 during July 2009 over Anantapur, a rural site in central
India, indicating the enhancement due to regional O3 production. As
shown in Table 2, while average O3 mixing ratios over the west coast of
India and the Arabian Sea are in the range of 9–25 nmol mol-1 during
the monsoon season, the average O3 mixing ratio is ∼ 30 nmol mol-1 over the central Indian station and the BoB.
Backward air mass trajectories (black curves) 500 m above the
location of higher CO observations as marked by red arrows in Fig. 4b during
7 and 11 August 2009. The background colour map shows the spatial
distribution of anthropogenic CO emissions over the Indian region for the
year 2006 from INTEX-B inventory. The small circles in magenta represent the
points where observations were made, as well as the end point of
trajectories. The white circle over the hotspot region denotes an
observational site, Bhubaneswar.
O3 mixing ratios were 27 ± 3 and 28 ± 5 nmol mol-1 for
21 July 2009 and 15 August 2009, for which back trajectories (not shown
here) crossed Thiruvananthapuram on 20 July and 13 August 2009, with
daytime O3 values of 23 ± 6 and 25 ± 6 nmol mol-1,
respectively. The difference of 3–4 nmol mol-1 between O3 mixing
ratios over the BoB and Thiruvananthapuram represents the en route
photochemical production of O3 in the air masses toward the observation
points over the BoB. It is further found that the air masses were typically
below 700 m and generally within the marine boundary layer (e.g. mean
boundary layer height ∼ 897 m during winter over the BoB;
Subrahamanyam et al., 2012). The enhancements in O3 are attributed here
to in situ photochemical build-up while moving towards the BoB, which has
been noted in previous experiments and model simulations (e.g. Lal and
Lawrence, 2001; Ojha et al., 2012).
CO showed a sharp enhancement (denoted with red arrows in Fig. 4b) on 7 and 11 August
2009, coinciding with a longer residence time over the Indian
region. Figure 5 shows backward air mass trajectories above the measurement
locations, along with the distribution of anthropogenic CO emissions from
the INTEX-B inventory, representative of the year 2006. The air masses over
the BoB are found to be influenced by emission hotspots (corresponding
emission of 250–350 mol km-2 h-1). The air masses took about half
a day to be transported from the emission hotspot to the observation
location over the BoB. The CO mixing ratio measured at Bhubaneswar
(20.30∘ N; 85.83∘ E), a station within the hotspot
region, is ∼ 251 ± 58 nmol mol-1 during the monsoon
season (June–August 2011–2012; Mahapatra et al., 2014), with the elevated
CO emissions in the Bhubaneswar region being attributed to industrial
activities. The higher CO mixing ratio ∼ 200 nmol mol-1
is in line with the monsoonal values observed at Bhubaneswar. The CO mixing
ratios around 150 nmol mol-1 were sampled on 11 August 2009 near the
coastal source regions. Additionally, CO mixing ratios over central BoB (101 nmol mol-1) were only slightly higher
than those over northern BoB (95 nmol mol-1). It is suggested that this is partially due to higher
emissions over southern India against the shorter residence of air masses
over land and the relatively longer lifetime of CO.
A comparison of mean values from observations with model-simulated
parameters along with the mean bias. The squared correlation coefficients
correspond to the linear regression analysis between daily averaged in situ
and simulated parameters.
The mixing ratios of surface CH4 were higher in the air masses from
central/northern Indian over northern BoB (1.86 ± 0.12 µmol mol-1) as compared to those in the air masses from southern India
(1.72 ± 0.14 µmol mol-1). As CH4 is a relatively well-mixed trace gas, the average values over the tropospheric column
approximates the uniform mixing ratio within the troposphere (Seinfeld and
Pandis, 2006). The monthly column-averaged tropospheric CH4, retrieved
from SCIAMACHY, for August 2009 shows (Fig. 6) higher values around 1.85 µmol mol-1 over central/northern India as compared to that of
southern India (∼ 1.80 µmol mol-1). The higher
tropospheric CH4 over the central/northern Indian landmass during the
summer monsoon season has been also reported by Kavitha and Nair (2016). The
observed higher CH4 over the northern BoB are attributed to the
influences of emissions from central/northern Indian regions as also
suggested by backward trajectories. Owing to the longer lifetime of
CH4, diffusion of CH4 from a hotspot region over the eastern IGP
to northern BoB might be the other source of higher CH4 levels over
northern BoB during summer monsoon season. An emission inventory analysis by
sector over the hotspot region (i.e. eastern IGP) indicates that these
higher CH4 emissions are associated with rice cultivation, waste
treatment, and livestock. The correlation between the in situ CH4
measurements and the retrievals from the satellite instrument
(AIRS – Atmospheric Infrared Sounder) was found to be statistically
insignificant (not shown), which highlights a need of more such in situ
measurements in this region to validate the satellite products, especially
during the summer monsoon.
Spatial distribution of column-averaged CH4 for the month of
August 2009 as obtained from SCIAMACHY.
WRF-Chem simulations
WRF-Chem simulations, as described in Sect. 4, are used to evaluate the
performance of the model in reproducing the measurements and to investigate
the underlying processes that caused the observed variabilities in O3
and CO. A comparison between model-simulated and measured meteorological
parameters shows only small mean biases, such as -1.9 hPa in pressure,
-0.6 ∘C in temperature, and -1.1 % in relative humidity (Table 3). Figure 4b–c compare WRF-Chem simulated O3 and CO with in situ
measurements taken along the cruise track. WRF-Chem is found to reproduce
the observed variations of O3 and CO over the BoB during the summer
monsoon season with an overestimation of absolute O3 levels by 1.9 nmol mol-1 (i.e. ∼ 6 %
of averaged O3 value, 29.7 nmol mol-1) and absolute CO levels by 18 nmol mol-1 (i.e.
∼ 16 % of averaged CO value, 96 nmol mol-1). It should
be noted that the average CO mixing ratio of 96 nmol mol-1 is slightly
higher than its actual value, as data points below the detection limit of
the instrument are discarded. Biases in the model simulations can be
attributed to the uncertainties in the simulated meteorology and in the
emission datasets; however, in the present study, the model fields are used
mainly to investigate temporal variations rather than absolute mixing
ratios. The squared correlation coefficients between the daily averaged in
situ measured and simulated O3 and CO are 0.58 and 0.19, respectively.
The higher value of the squared correlation coefficient for O3 demonstrates WRF-Chem's ability to reproduce the observed broad features
in surface O3 over the BoB. Note that the sharp reductions that caused
very low O3 during rainfall episodes are not captured by WRF-Chem,
except during the event of 10–11 August 2009. This will be discussed in
detail in Sect. 5.3. WRF-Chem simulated O3 has also been evaluated
against several surface observations in India previously (Kumar et al.,
2012b). Modelled O3 was found to be within 1σ standard
deviation of mean from observations at Gadanki in the southern India during
summer monsoon (Ojha et al., 2016). At Thumba also, model-simulated O3
variations correlated reasonably with measurements (R2= 0.6). More
information on evaluation of WRF-Chem simulations of O3 and CO over
India can be found elsewhere (e.g. Kumar et al., 2012b; Ojha et al., 2016).
(a) WRF-Chem simulated O3 along the air mass trajectories
ending over a few representative locations over the BoB. (b) Variation of
O3 mixing ratios with time along the trajectories as shown in (a). In
box plot, the black dots and lines inside the box represent the mean and
median of the data, respectively. While the lower and upper edges of boxes
represent the 25th and 75th percentiles, respectively, the whiskers
represent standard deviations.
An additional simulation was conducted by switching off the anthropogenic
emissions over the model domain (Fig. 4b–c; dotted blue curves). Mean
O3 (17.7 nmol mol-1) is found to be lower by 14
with smaller variability of 2.4 nmol mol-1 compared to standard
WRF-Chem simulation. Similarly, also the mean CO level is lower by 36 with smaller variability of 4.9 nmol mol-1. This shows that
enhanced levels and observed variability in O3 and CO mixing ratios
over BoB are attributable to the regional anthropogenic emissions.
Surface O3 (black dots) along with temperature (orange curve)
and 3 h rainfall (grey vertical bar) during the four events of sharp
decline in O3 (a–d) as marked in Fig. 4c. Colours indicate the
vertical wind as simulated by WRF-Chem.
The limited collocated measurements showed en route O3 production rate
of 1.5–4 nmol mol-1 day-1, as discussed in Sect. 5.1. Here, the
O3 production rate is estimated by analysing the model-simulated
O3 mixing ratios along the air mass trajectories ending at few
representative locations over the BoB (Fig. 7a). The model-simulated
chemical evolution of air parcels clearly shows an increase in the O3
mixing ratios towards the marine region of BoB. The temporal variations of
O3 mixing ratio averaged corresponding all the trajectories shown in
Fig. 7a is shown as a box plot in Fig. 7b. A linear regression analysis (blue
curve in Fig. 7b) is used to estimate the mean en route O3 production
rate of ∼ 4.6 nmol mol-1 day-1 in the outflow. The
enhancement in average O3 over the BoB as compared to the continental
Indian region is also shown in the Fig. 2d, averaged for the study period.
A comparison of average mixing ratios of surface trace gases
measured over northern BoB (81–91∘ E, 16–21.5∘ N) and
central BoB (80–91∘ E, 11–16∘ N) in different seasons as
measured during different experiments. The range of mixing ratios (i.e.
minima–maxima) is given in the brackets.
* CO mixing ratios below
the detection limit (i.e. 50 nmol mol-1) are not considered in the
analysis.
Ozone variations during rainfall events
An interesting phenomenon observed during the CTCZ experiment is the abrupt
reduction in O3 mixing ratios that accompanied the onset of heavy
rainfall, despite the low solubility of O3 in water. In this section
the possible causes of these low-O3 events during rainfall are
investigated.
Figure 8 shows variations in O3 (black circles) mixing ratios, surface
temperature (orange curve), TRMM retrieved rainfall (thick grey vertical
bars), and WRF-Chem simulated vertical winds at pressure levels ranging from
950 to 750 hPa (coloured bars) during four such events on 21, 26, and 28–29 July and on 10–11 August 2009. As high time resolution in situ
measurements of rainfall were not available aboard ship, Fig. 8 therefore
uses 3 h rainfall retrievals from the TRMM, co-located with O3
measurements. During these events, CO mixing ratios also show a reduction of
about ∼ 56 nmol mol-1, with observed values falling below
the detection limit of the instrument during the first event of 21 July
2009 (not shown). Although CO measurements are not available for the second
and third event, during the fourth event (10–11 August 2009) CO mixing
ratios showed an enhancement due to transport from strong source regions
(see Sect. 5.1). While the first three low-O3 events are not captured
by WRF-Chem (Fig. 4c), the fourth event is reproduced.
Wet scavenging does not directly reduce O3, as its water solubility is
low; as a result, some dynamic process could be responsible for the observed
reductions in O3 during rainfall. Air masses could undergo downdrafts
during heavy rainfall (Kishore Kumar et al., 2005) through air drag by the falling
rain drops and in mesoscale subsidence that compensates convective updrafts.
We suggest that, in the presence of O3-poor air mass aloft, a downdraft
would result in reductions in surface O3 mixing ratios. An opposite
scenario leading to O3 enhancement could take place if downdrafts bring
mid-tropospheric air, where typically O3 is higher than at surface. The
model-simulated meteorology shows occurrences of downdrafts at different
pressure levels during the first three events on 21, 26, and 28–29 July
(Fig. 8a–c), which is further corroborated with measurements of air
temperature aboard. Downdrafts of free-tropospheric air could lead to a
reduction in near-surface temperature by as much as 10 ∘C within
a few minutes (Ahrens, 2009). Air temperature measured aboard ship showed a
sharp decrease of 2–4 ∘C, coinciding with the first three
low-O3 events (Fig. 8a–c). The reductions in temperature caused by
downdrafts are generally short-lived (Ahrens, 2009), as is confirmed in the
case of these events (Fig. 8a–c).
Model-simulated vertical winds and variations in air temperature suggest
that downdrafts did occur during the first three rainfall events. As in situ
measurements of O3 vertical profiles are not available over the BoB
during the summer monsoon season, the observations taken at Thumba,
Thiruvananthapuram, in the southern Indian region are used as a case study
to investigate this hypothesis. For general details of the typical diurnal
and seasonal variations of O3 at Thumba, please see Nair et al. (2002),
David and Nair (2011), and Girach et al. (2012). Figure 9a shows the
temporal variation in surface O3 on 15 July 2011 at Thumba, along with
5 min accumulated rainfall. Here, surface O3 is observed to decline
from 25 to 13 nmol mol-1 within 15–20 min, coinciding with
the occurrence of intense rainfall (3.5–0.5 mm rain over a period of 5 min). Measurements of the O3 vertical profile are not available for
this day due to the rainy conditions; a profile measured on 28 July 2011 is
therefore shown in Fig. 9b. This profile has lower O3 mixing ratios
aloft (∼ 22 nmol mol-1 at ∼ 1 km) than near the
surface (∼ 42 nmol mol-1). The observed mixed layer
height is about 0.15–0.6 km over Thumba, Thiruvananthapuram (Anurose et
al., 2016), during July 2011; above this height, O3 mixing ratios
sharply decrease with altitude. The present case study suggests the presence
of O3-poor air masses aloft than those near the surface over the south
Indian region during summer monsoon. With an O3 distribution as
observed in the present case study at Thumba, the downdraft during intense
rainfall could lead to the mixing of free-tropospheric air with near-surface
air or to the replacement of surface air with free-tropospheric
O3-poor air.
(a) Temporal variation in surface O3 mixing ratio (black
dots) along with 5 min accumulated rainfall (grey vertical bars) over
Thumba, Thiruvananthapuram (location of the site shown in Fig. 1), on 15 July
2011. (b) Vertical profile of O3 mixing ratio over Thumba,
Thiruvananthapuram, as measured on 28 July 2011.
Time series of surface O3(a) and various tendency terms
(b and c) over the event location during the fourth low-O3 event, as
obtained from WRF-Chem simulations. (d)–(f) are the same as (a)–(c), but for
another location during the same event. These two event locations are also
marked by triangles in Fig. 11. Vertical dotted line shows the time of the
event in the in situ observations of surface O3 over the indicated
locations.
Although air temperature measurements could not be made during the fourth
event (10–11 August 2009) due to a technical problem, model meteorology
does not indicate a downdraft during this event (Fig. 8d), indicating the
dominance of a different process. As WRF-Chem simulated O3 variability
is in good agreement with observations during this event, various tendency
terms (Barth et al., 2012) from WRF-Chem are used to investigate the
relative influences of different processes. The variations in instantaneous
values for horizontal advection tendency, vertical advection tendency, and
net tendency (i.e. the sum of chemical, vertical mixing, convective,
vertical advection, and horizontal advection), along with modelled O3 over the two locations during the event, are shown in Fig. 10. The
tendency values shown here are derived by subtracting the accumulated
tendencies at (n-1)th hour from the accumulated tendency at nth
hour. The vertical dotted lines show the time of a low-O3 event.
Spatial distribution of surface O3 (top panel) and CO
(bottom panel) at 16:00 and 19:00 UT on 10 August 2009, both prior to
and during the fourth event, which took place 22:00 UT on 10 August 2009.
White triangles show two locations (85.40∘ E, 19.00∘ N;
84.95∘ E, 19.00∘ N) corresponding to the event.
Seasonal variation in average O3, CO, and CH4 mixing
ratios over (a, c, e) northern BoB and (b, d, f) central BoB. Except for
July–August 2009 (present study period), all average values are obtained
from the literature (David et al., 2011; Lal et al., 2007, 2006;
Nair et al., 2011; Srivastava et al., 2012; Sahu et al., 2006; and Mallik et
al., 2013). Error bars show standard deviations for respective study
periods. For any points for which high-resolution measurements are not
available, standard deviations are not shown.
Both the horizontal and net tendencies (Fig. 10b–c, e–f) show negative
values, indicating that they are contributing towards a reduction in O3
mixing ratios (Fig. 10a, d). However, as the time of the event approaches, it
is the horizontal advection tendency term that is significantly negative
(Fig. 10c, f), while other terms are small and close to zero. Horizontal
advection is therefore suggested to dominate during the low-O3 event of
10–11 August 2009. The influence of horizontal advection on O3 during
this event is shown more clearly in Fig. 11, which shows the spatial
distribution of O3 and CO from WRF-Chem before the event (16:00 and
19:00 UT) and during the event (22:00 UT) on 10 August 2009. The white
triangles show the two locations where the event was observed. During 16:00
and 19:00 UT, a patch of high O3 mixing ratios (35 nmol mol-1 and
higher) is seen to be distributed over a large region surrounding the
measurement location. This large patch of elevated O3 mixing ratios is
horizontally advected eastward from 16:00 to 19:00 and then towards 22:00 UT
(event time). As a result of this rapid advection, the high-O3
air masses are transported from the coastal regions to deeper into the BoB;
by the time they reached the location of observation, O3 mixing ratios
are observed to be lower (25–35 nmol mol-1) during the event time
(22:00 UT). A patch of higher levels of CO (∼ 300 nmol mol-1) was also found to be distributed across the east coast of the
Indian region. Transport and dilution of this CO patch is, however, less
pronounced than the high-O3 air masses, possibly due to the relatively
longer lifetime of CO. Thus, in a nutshell, the horizontal advection played a
key role in transporting O3-rich air masses deeper into the BoB region,
while it diluted O3 levels near the coastal regions in southern India
during the fourth event.
Seasonal variation in trace gases over the BoB
In this section, the monsoon-time measurements of O3 taken in the
present study are combined with data from previous campaigns (see Table 4)
to investigate the seasonal variation in O3 over the BoB (Fig. 12).
O3, CO, and CH4 mixing ratios are averaged over northern
(81–91∘ E, 16–21.5∘ N) and central (80–91∘ E,
11–16∘ N) BoB regions.
Overall, higher O3 mixing ratios are present over both northern and
central BoB during the winter, while lower O3 levels are observed
during the spring–summer (with more scatter in the data over central BoB).
The O3 seasonal amplitude (i.e. the range from maxima to minima) is
estimated to be ∼ 39 over northern BoB and
∼ 27 nmol mol-1 over central BoB. The monsoonal surface
O3 mixing ratios (∼ 30 ± 7 nmol mol-1) are
nearly half those observed during winter (63 ± 5 nmol mol-1) over
northern BoB. During December 2008–January 2009, February 2003, March 2006,
and November 2010, the O3 mixing ratios were higher (by ∼ 3–22 nmol mol-1) over northern BoB than over central BoB.
However, over the course of February 2001, O3 mixing ratios were higher
over central BoB (∼ 38 nmol mol-1) than over
northern BoB (∼ 14 nmol mol-1). In contrast, during
summer monsoon season, average O3 mixing ratios are comparable or only
slightly higher over northern BoB (30 ± 7 nmol mol-1) as compared
to over central BoB (27 ± 5 nmol mol-1).
As compared with the summer monsoon season, when CO mixing ratios were
lower over northern BoB, CO mixing ratios were higher during the winter,
while over central BoB CO mixing ratios were higher during the pre-monsoon
season. For O3, spring–summer had the lower mixing ratios in both
regions. The seasonal amplitude in CO mixing ratios is estimated to be
∼ 205 over northern BoB and ∼ 124 nmol mol-1 over central BoB. The monsoonal CO mixing ratio
(∼ 95 nmol mol-1) is about one-third that of the winter
season (302 nmol mol-1) over northern BoB. During the present study,
average CO mixing ratios were comparable over northern (95 ± 25 nmol mol-1) and central BoB (101 ± 27 nmol mol-1).
A clear inference about seasonal patterns is difficult in the case of
CH4, but a tendency of lower levels towards winter can be seen.
Higher mixing ratios ∼ 1.95 (∼ 1.91) µmol mol-1 were observed during November 2010 over northern BoB, and during
February–March 2001 over central BoB, as compared to those from other
studies. The surface CH4 observations obtained during the present study
show the highest variability (i.e. the difference between maxima and minima)
when compared to earlier studies: 0.53 over northern
BoB and 0.39 µmol mol-1 over central BoB. This high variability
is attributed to the relative source strengths over central and northern
India as compared to southern India, highlighting the regional differences
in CH4 variability across India (Kavitha and Nair, 2016).
Seasonal variations in trace gases over the BoB are attributed to seasonal
changes in the meteorological conditions, emissions, and photochemistry over
the South Asian region, as well as to synoptic-scale transport patterns.
Wintertime stronger westerly winds transport the pollution from South Asia,
including that of the Indo-Gangetic basin, to the BoB region. Monsoonal
circulation, in contrast, carries cleaner marine air masses to the BoB from
the oceanic regions. However, as observed during the CTCZ, polluted
continental or coastal air masses can also occasionally be transported deeper
over the BoB. Intense monsoonal rainfall generally leads to wet removal of
O3 precursors, while cloudy and rainy meteorological conditions
suppress O3 formation. Along with the importance of monsoonal
convection in cloud formation, rainfall, and uplifting the boundary layer
pollution, rapid horizontal advection is also an important process during
the summer monsoon, especially affecting the near-surface variability of
trace gases over the oceanic regions adjacent to India.
Conclusions
In this paper, we presented shipborne in situ measurements of O3, CO,
and CH4 that were carried out as a part of the CTCZ experiment over the
BoB during the summer monsoon season, July–August 2009. We analysed the
spatial and temporal variations in the observations and compared them with
results from simulations performed with a regional chemistry transport model
(WRF-Chem), as well as with observations from previous campaigns over the
BoB. The main conclusions are as follows.
These first monsoonal observations of O3, CO, and CH4 show large
spatio-temporal variability over the BoB, with mixing ratios varying in the
range of 8–54 (mean: 29.7 ± 6.8) nmol mol-1, 50–200 (mean:
96 ± 25) nmol mol-1, and 1.57–2.15 (mean: 1.83 ± 0.14) µmol mol-1, respectively. The O3 and CO mixing ratios in
air masses from central/northern India are slightly higher or comparable
(O3: 30 ± 7, CO: 95 ± 25 nmol mol-1) to
those in air masses from southern India (O3: 27 ± 5, CO: 101 ± 27 nmol mol-1). The CH4 mixing ratios
in air masses from central/northern (1.86 ± 0.12 µmol mol-1)
are higher (∼ 0.14 µmol mol-1) compared to those
in air masses from southern India (1.72 ± 0.14 µmol mol-1).
This could be due to higher CH4 levels over central/northern India,
also found in SCIAMACHY data.
Back-trajectory analysis shows effects of long-range transport from northern
or central India to northern BoB and from southern India to central BoB.
The correlated variations of these trace gases and percentage residence time
of air parcels over the Indian regions suggest that the enrichment of
O3 and precursors in air parcels over the BoB is associated with both
emissions and photochemistry over the Indian region. The trajectory analysis
shows that the observed variation in surface O3 is primarily due to
transport and en route photochemistry over the BoB during monsoon season. An
analysis of modelled O3 along air mass trajectories show mean en route
O3 production rate of about 4.6 nmol mol-1 day-1 in the
outflow towards the BoB.
The observed spatio-temporal variations of surface O3 and CO during
summer monsoon season are generally reproduced by WRF-Chem,
although the absolute mixing ratios of O3 and CO are typically
overestimated by about 6 and 16 %, respectively.
The four low-O3 events coinciding with intense rainfall were observed
over the BoB. After analysing the observed variability in air temperature,
model simulations of vertical winds, and an O3-profile case study from
southern India, we suggest that first three low-O3 events were due to
strong downdrafts of O3-poor air masses. Analysis of the fourth event,
which is successfully reproduced by the model, shows the pivotal role of
horizontal advection in transporting O3-rich air masses deeper over the
BoB.
Finally, the measurements during the monsoon are combined with previous
campaigns over the BoB during other seasons to investigate the seasonal
variability in trace gases over the BoB. O3 and CO are shown to have
pronounced seasonality, O3 having amplitudes of about 39 and 27 nmol mol-1 and CO having amplitudes of about 207 and 124 nmol mol-1
over northern and central BoB, respectively.
Our study data fill a gap of observations during the summer monsoon over the
BoB, providing information on the extent of seasonal variability. We
recommend supplementing these findings with shipborne experiments featuring
collocated vertical profile observations from balloon-borne and
aircraft-based platforms over the oceanic regions surrounding India to
better understand the role of both large-scale dynamics (e.g. Ojha et al.,
2016) and of regional influences due to South Asian outflow (see Lawrence
and Lelieveld, 2010, and references therein). Such a future study would also
improve our understanding of the changes that take place in the atmospheric
oxidation capacity during the summer monsoon season.
Data availability
The observational data used in the paper can be obtained by contacting the corresponding author (imran.girach@gmail.com).
The metadata are available on the website of Space Physics Laboratory (http://spl.gov.in/index.php?option=com_content&view=article&id=394&Itemid=695&lang=en).
Acknowledgements
We thank the CTCZ and ICRP organisers for the opportunity to participate in
the 2009 CTCZ experiment. We are thankful to the Director of the National
Centre for Antarctic and Ocean Research (NCAOR), Goa, for providing
shipboard facilities. We gratefully acknowledge G. S. Bhatt (Indian
Institute of Science, Bengaluru, India) and his team for providing the
measurements of meteorological parameters. We also thank the chief scientist
on board Sagar Kanya for providing necessary support during the
cruise. The authors gratefully acknowledge the NOAA Air Resources Laboratory
(ARL) for the providing the HYSPLIT transport and dispersion model and READY
website (http://www.arl.noaa.gov/ready.php) used in this publication. The
rainfall estimations (3B42) from the TRMM satellite were obtained from the
NASA/GSFC via their website http://mirador.gsfc.nasa.gov/. The monthly
CH4 retrievals (IMAP-DOAS) of SCIAMACHY were obtained from their
website, http://www.temis.nl/climate/methane.html. Use of
INTEX-B and HTAP (http://edgar.jrc.ec.europa.eu/htap_v2/index.php?SECURE=123) anthropogenic emissions is gratefully
acknowledged. Initial and boundary condition data for meteorological fields
were used from the ERA-Interim of ECMWF. Use of MOZART-4/GEOS5 initial and
boundary condition data for chemical fields is acknowledged.
Data and processors for anthropogenic emissions, biogenic emissions, and biomass
burning obtained from NCAR ACD website are gratefully acknowledged. The
authors acknowledge the use of MPG supercomputer HYDRA
(http://www.mpcdf.mpg.de/services/computing/hydra) for model simulations.
Constructive comments and suggestions from anonymous reviewers are
gratefully acknowledged.
The article processing charges for this open-access publication were covered by the Max Planck Society.
Edited by: N. Harris
Reviewed by: two anonymous referees
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