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ACPD
14, 32133–32175, 2014
VOCs over Eastern
Himalaya, India
C. Sarkar et al.
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Atmos. Chem. Phys. Discuss., 14, 32133–32175, 2014
www.atmos-chem-phys-discuss.net/14/32133/2014/
doi:10.5194/acpd-14-32133-2014
© Author(s) 2014. CC Attribution 3.0 License.
This discussion paper is/has been under review for the journal Atmospheric Chemistry
and Physics (ACP). Please refer to the corresponding final paper in ACP if available.
Volatile organic compounds over Eastern
Himalaya, India: temporal variation and
source characterization using Positive
Matrix Factorization
C. Sarkar1, A. Chatterjee1,2,4, D. Majumdar3, S. K. Ghosh4, A. Srivastava3,5, and
S. Raha2,4
1Environmental Science Section, Bose Institute, P 1/12 CIT Scheme VII-M, Kolkata-700054,
India
2National Facility on Astroparticle Physics and Space Science, Bose institute, 16, A.J.C. Bose
Road, Darjeeling-734101, India
3National Environmental Engineering Research Institute, I-8 Sector-C, EKDP, Kolkata-700107,
India
4Center for Astroparticle Physics and Space Science, Block-EN, Sector-V, Salt Lake,
Kolkata-700091, India
5National Environmental Engineering Research Institute, Delhi, India
32133
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Received: 10 October 2014 – Accepted: 30 November 2014 – Published: 19 December 2014
Correspondence to: A. Chatterjee (abhijit.boseinst@gmail.com)
Published by Copernicus Publications on behalf of the European Geosciences Union.
32134
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Abstract
A first ever study on the characterization of volatile organic compounds (VOCs) has
been made over a Himalayan high altitude station in India. A total of 18 VOCs (mono
aromatics-BTEX (benzene, toluene, ethylbenzene, xylene), non-BTEX substituted aro-
matics and halocarbon) have been measured over Darjeeling (27.01◦N, 88.15◦E,5
2200 ma.s.l.) in the eastern Himalaya in India during the period of July 2011–June
2012. The annual average concentration of the sum of 18 target VOCs (TVOC) was
376.3 ±857.2 µg m−3. Monoaromatics had the highest contribution (72 %) followed by
other substituted aromatics (22 %) and halocarbon (6 %) compounds. Toluene was the
most abundant VOC in the atmosphere of Darjeeling with the contribution of ∼37 % to10
TVOC followed by benzene (∼21%), ethylbenzene (∼9%) and xylenes (∼6 %). TVOC
concentrations were highest during the postmonsoon season with minimum solar radi-
ation and lowest during the premonsoon season with maximum solar radiation. Anthro-
pogenic activities related mainly to tourists like diesel and gasoline emissions, biomass
and coal burning, use of solvent and solid waste emissions were almost equal in both15
the seasons. Seasonal variation in TVOCs over Darjeeling was mainly governed by
the incoming solar radiation rather than the emission sources. Source apportionment
study using Positive Matrix Factorization (PMF) model indicated that major fraction
of (∼60 %) TVOC were contributed by diesel and gasoline exhausts followed by sol-
vent evaporation (18 %) and other sources. Diesel exhaust was also found to have the20
maximum potential in tropospheric ozone formation. The atmospheric loading of BTEX
over Darjeeling was found to be comparable with several Indian metro cities and much
higher than other cities around the world.
1 Introduction
The studies on volatile organic compounds (VOCs) have gained much attention be-25
cause of their ability in modifying oxidizing capacity of the atmosphere as well as
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VOCs over Eastern
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health implications to humans. VOCs play an important role in the formation of pho-
tochemical smog and tropospheric ozone by reacting with hydroxyl radicals (OH) in the
presence of NOx(Atkinson, 2000). They also have the potential towards stratospheric
ozone depletion and enhancement of the global greenhouse effect (Guo et al., 2004a).
VOCs comprise a wide range of compounds including aliphatic and aromatic hydrocar-5
bons, alcohols, aldehydes, ketones, esters, and halogenated compounds. Many VOCs
react with hydroxyl radicals (OH) and/or nitrate (NO3) radicals to form secondary or-
ganic aerosol (SOA) by nucleation and condensation with a significant aerosol yield
and thus they influence gas phase pollutants directly and particle-phase pollutants in-
directly (Atkinson, 2000).10
There is as such no general source for VOCs as there are numerous compounds in
this group, which can be emitted from very different sources (Yurdakul et al., 2013). In
addition to the biogenic sources of VOCs (Williams and Koppmann, 2007), some well
documented anthropogenic sources are gasoline powered and diesel powered motor
vehicles (Demir et al., 2011), fuel storage (Lanz et al., 2008), biomass burning (Yokel-15
son et al., 2008), natural gas (Latella et al., 2005), LPG (Lai et al., 2005), industrial
processes and solvents (Lanz et al., 2008) etc.
High levels of VOCs have been observed in Asian countries and these have been
considered to be originating from vehicular emissions (Srivastava et al., 2005a). Among
the Asian countries, India is the second largest contributor to the emission of non-20
methane VOCs (Kurokawa et al., 2013). In spite of growing population and associated
increase in vehicular and industrial activities, the studies on VOCs in India are limited.
Some of those important studies have been conducted in the recent past mostly in
metro cities such as in Delhi, the capital city of India (Hoque et al., 2008; Khillare et al.,
2008; Srivastava, 2005; Srivastava and Singh, 2005; Srivastava et al., 2005b, c; Gurjar25
et al., 2004; Padhay and Varshney, 2000), in Mumbai, a metro city and financial capital
of India situated in western India (Srivastava and Som, 2007; Srivastava et al., 2004a,
2006a, b; Srivastava, 2004b), in Kolkata, a metro city in eastern India (Dutta et al.,
2009; Mujumdar et al., 2008; Som et al., 2007; Mukherjee et al., 2003), in Hyderabad,
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a metro city in southern India (Rekhadevi et al., 2010), in Agra in northern India, (Singla
et al., 2012), in Firozabad in northern India (Chaudhury and Kumar, 2012) etc. In India
there is no legislation of VOC as a whole except national ambient air quality standard
for Benzene by Central Pollution Control Board of India. Globally US Occupational
Safety and Health Administration (OSHA) and World Health Organization (WHO) have5
proposed some guidelines and recommendations for VOCs and not compulsory for
governments to follow (Han and Naeher, 2006).
Where almost all the studies were conducted over several cities in India, no such
study on VOCs have been ever made over Himalaya in India. Such studies over Hi-
malayan region are of paramount interest as the ecology of the Himalaya is under seri-10
ous threat from various forms of pollutants (Bostrom, 2002). The increase in the loading
of atmospheric pollutants over the Himalaya is a matter of concern, since most of the
glaciers in the region have been retreating since 1850 (Mayewski et al., 1979) with
increasing melting rates. The rising anthropogenic interferences for rapid urbanization
and development in the Himalaya not only affect the immediate landscape environ-15
ment, but also the atmospheric environment which is becoming an increasing concern
(Momin et al., 1999). The anthropogenic activities such as increasing vehicular traffic
due to increased tourism-related activities, biomass burning and fuel wood burning for
cooking and heating are the causes of concern for most of the Himalayan high alti-
tude hill stations in India which apparently look like pollution-free regions as situated20
far away from the Indian mega-cities.
The present study on the characterization of VOCs has been made over a high alti-
tude (2200 ma.s.l.) hill station, Darjeeling (27.01◦N, 88.15◦E) at eastern Himalaya and
the first ever study conducted over Indian Himalaya to the best of our knowledge. Our
earlier studies (Chatterjee et al., 2010, 2012; Adak et al., 2014; Sarkar et al., 2014) over25
the same region showed high aerosol loading during premonsoon (March–May) due to
vehicular emissions related to tourist activities and during winter (December–February)
due to massive biomass burning. In addition to the local sources, pollutants were also
found to be accumulated over this region transported from long distant regions like
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Indo–Gangetic Plain (IGP) and other Asian sub continents. Sarkar et al. (2014) found
enhancement of Black Carbon aerosols over Darjeeling during postmonsoon (October–
November) due to transported plumes of biomass burning from northern India. The
seasonal variation of aerosols associated to the variation in emission sources (local
and transported) as observed from earlier studies have prompted us to make a year-5
long study on VOCs over Darjeeling as major aerosol sources over this region are
generally the major sources of VOCs too.
The present study is thus mainly focused on (1) the identification of the major factors
governing seasonal variation of VOCs, (2) contribution of long distant source regions,
(3) source apportionment of VOCs using Positive Matrix Factorization (PMF) and their10
potential in tropospheric ozone formation.
2 Study site and synoptic meteorology
The study has been carried out at a high altitude hill station Darjeeling (27◦010N,
88◦150E, 2200 ma.s.l.) at eastern Himalaya in India. The map showing geographical
location of the measurement site and adjacent regions in Darjeeling has been given in15
detail in our earlier study (Adak et al., 2014).
The seasonal average along with minimum and maximum of surface meteorolog-
ical parameters; temperature (T) in ◦C, wind speed (WS) in ms−1, relative humidity
(RH) in % and rainfall (mm) are given in Fig. 1. The entire study period is divided
into four seasons; winter (December–February), premonsoon (March–May), monsoon20
(June–September) and postmonsoon (October–November). Figure 1 shows that the
temperature was highest during monsoon and lowest in winter whereas relative hu-
midity shows monsoon maximum and premonsoon minimum. Wind speed was found
to be maximum in premonsoon which was ∼2 times than that in other seasons. We
did not observe much variation between daytime and nighttime wind speed except in25
premonsoon when daytime wind speed was much higher (∼1.8 times) than night-time
wind speed. The surface reaching solar radiation was maximum during premonsoon
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and was much higher than postmonsoon, monsoon and winter. The total amount of
rainfall over the entire sampling days was 421.4mm. However, ∼95 % rain occurred
during monsoon (397 mm) only.
3 Methodology
3.1 Sampling and analysis of VOCs5
The study was carried out in the campus of National Facility on Astroparticle Physics
and Space Science, Bose Institute, Darjeeling. Samples were collected on a roof top
of the building of Bose Institute at a height of about 20 m from the ground level at
day (7a.m. to 7 p.m.) and night (7 p.m. to 7a.m.) basis for a year long period from 7
July 2011 to 25 June 2012. The samples were collected once a week. A total of 9010
samples were collected during the study period, using a custom made glass sampling
tube containing charcoal and chromosorb. The tubes were pre-conditioned by heating
over night at 200◦C temperature. The tubes were connected with a low flow air suction
pump (SKC, USA). The flow rate was maintained at ∼100 mL min−1. The flow was
measured before and after each sampling event using a flow meter. After sampling the15
ends of the tubes were sealed well with the Teflon tape and cap and kept at 4 ◦C for
analysis.
The analysis was done by thermal desorption followed by detection on GC-MS in
accordance with USEPA TO-17 compendium method for the determination of target
VOCs and described in details in the authors’ previous publications (CPCB, 2007,20
2010; Srivastava and Som, 2007; Majumdar et al., 2014). In short the thermal desorp-
tion of sorbent tube was done by heating at 180◦C for 25 min. 100 µL of desorbed gas
was injected into Varian Make GC-MS (Now Agilent; GC-MS model: (Model 450GC-
240MS)). Target VOCs were separated using DB 624 capillary column of 30 m length
and 0.32 mm internal diameter. Helium gas with flow rate of 1mL min−1was used as25
carrier gas with split ratio 1 : 20, GC oven was programmed for 35 ◦C hold for 4 min
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VOCs over Eastern
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and ramped to 210 ◦C. For estimation of the target compounds external five point cali-
bration curve was prepared in triplicate using VOC mix 20 by Dr. Ehrenstorfer GmbH,
Germany.
4 Results and discussion
4.1 General characteristics of VOCs over Darjeeling5
All the 18 VOCs measured in this study denoted as TVOC (Total VOCs) have been
classified in to three groups; mono-aromatics BTEX, non-BTEX substituted aromat-
ics (iso-propylbenzene, n-propylbenzene, 1,3,5 trimethylbenzene, 1,2,4 trimethylben-
zene, sec-butylbenzene, 4-isopropyltoluene, 2-chlorotoluene, 1,4 dichlorobenzene, n-
butylbenzene, naphthalene), and halocarbons (1,1 dichloroethane, 1,2 dichloroethane,10
chloroform and carbon tetra chloride). The annual average concentrations of each VOC
for each group along with their minimum and maximum concentrations over the entire
period of study have been given in Table 1. The concentration of TVOC over Darjeeling
was found to vary widely from as low as 6.6 µgm−3to as high as 4707.5 µg m−3over
the entire period of study (July 2011–June 2012). The annual average concentration15
of TVOC was 376.3±857.2 µg m−3. BTEX was found to have the highest contribu-
tion (72 %) followed by non-BTEX substituted aromatics (22 %) and halocarbon (6 %)
compounds. BTEX varied over a wide range between 1.5 and 3975.6 µg m−3with an
average of 275.1 ±685.7 µg m−3. Toluene was found to be the most abundant VOC
in the atmosphere of Darjeeling with the contribution of ∼37 % to TVOC followed by20
benzene (∼21 %), ethylbenzene (∼9 %) and xylenes (∼6 %). The concentration of
non-BTEX aromatics, too, varied widely from a very low (0.3 µg m−3) to a very high
(912.1 µg m−3) value with an average of 88.6±220.1 µg m−3. On the other hand, halo-
carbon compounds, unlike other VOCs, did not show such large variability during the
study period. The concentration of halocarbons varied from 1.5 to 73.3 µg m−3with an25
average of 21.5±15.4 µg m−3. TVOC and most of its components showed their mini-
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mum concentrations during premonsoon (15 May 2012) and maximum concentrations
during postmonsoon (21 November 2012).
4.2 Factors affecting seasonal variations of VOCs
Figure 2 shows the seasonal variations of VOCs over Darjeeling. The concentration
of TVOC was maximum in postmonsoon (1649.9±875.4 µg m−3) followed by mon-5
soon (117.1 ±88.3 µg m−3), winter (60.4±28.2 µg m−3) and minimum during premon-
soon (35.9 ±9.7 µg m−3) BTEX and non-BTEX substituted aromatics showed similar
seasonal patterns. The high postmonsoon concentrations were found to be 1228.2±
534.1 µg m−3and 404.0 ±336.1 µg m−3and the low premonsoon concentrations were
found to be 12.9±3.3 µg m−3and 3.5 ±1.5 µg m−3for BTEX and non-BTEX substi-10
tuted aromatics respectively. Unlike BTEX and non-BTEX, halocarbons showed highest
abundance in winter (33.5 ±10.4 µg m−3) with small variabilities between premonsoon
(19.1±4.2 µg m−3), postmonsoon (17.6±4.5 µg m−3) and monsoon (14.5±5.2 µg m−3).
Postmonsoon and premonsoon are the tourist seasons over Darjeeling. Darjeeling
experiences huge emissions of fossil fuel burning from large numbers of tourist ve-15
hicles during these two seasons compared to other seasons. We had made rough
measurements on vehicle counts and consumption of fossil fuel over Darjeeling ear-
lier in the year of 2005 (Adak et al., 2010). We observed that the number of light and
medium duty vehicles was 6000–6700day−1during premonsoon and postmonsoon
whereas 3000–3600 day−1during winter and monsoon. The total consumption of fossil20
fuel (petrol and diesel) was 6500–7500 L day−1during premonsoon and postmonsoon
whereas it was 3500–4500 L day−1during winter and monsoon. In addition to the vehic-
ular emissions, various other anthropogenic activities get increased in premonsoon and
postmonsoon seasons. The tourist activities remained almost same in these two sea-
sons but VOCs showed significant variations with high level in postmonsoon and low25
level in premonsoon. The other factors related to the sinks of VOCs played major roles
dominating the emission sources of VOCs, leading to the significant variation between
postmonsoon and premonsoon. Observed seasonal trends can thus be addressed by
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the characteristics of the prevailing meteorology, and most importantly, the availability
of solar insolation in these two seasons. Darjeeling recorded maximum solar insolation
in premonsoon (360 ±140 W m−2; Fig. 1) which could help in the photolysis of ozone,
carbonyls, water vapour etc leading to the formation of OH radicals in the atmosphere
(Ho et al., 2004). This plays key role in atmospheric clean-up and degradation of VOCs5
during premonsoon. Another important meteorological factor is wind speed which was
observed to be maximum during premonsoon months (1.4 ±0.5 m s−1; Fig. 1). This
could favour the ventilation and dispersion of VOCs from the study site. On the other
hand, the solar insolation (220 ±100 W m−2) and wind speed (0.65±0.2 m s−1) during
postmonsoon were much lower than premonsoon. Thus, although the VOC emissions10
remained comparable, VOC degradation was maximum in premonsoon than postmon-
soon leading to premonsoon low and postmonsoon high VOC concentrations. In addi-
tion to the local emissions, transported carbonaceous compounds could also contribute
significantly in enhancing carbonaceous compounds over eastern part of Himalaya dur-
ing postmonsoon. Bonasoni et al. (2010), Marinoni et al. (2010), Dumka et al. (2010)15
and Kaskaoutis et al. (2014) have shown the influence of carbonaceous compounds
(mainly Black Carbon) over Himalayas due to transported plumes associated to crop
residue burning over Punjab and adjacent Indo Gangetic Plain regions during post-
monsoon seasons. Our recent study (Sarkar et al., 2014) showed the impact of this
transported biomass burning plumes on Black Carbon aerosols over Darjeeling in the20
same study period. These biomass burning plumes could also bring significant amount
of VOCs over Darjeeling enhancing their concentrations during postmonsoon.
The tourist activities remained low both during monsoon and winter months over
Darjeeling. The solar insolation during monsoon and winter was comparable in mag-
nitude (180 ±80 W m−2). Darjeeling recorded maximum temperature during monsoon25
(15.8 ±0.9 ◦C) which may lead to increased evaporative emissions for certain VOC
species with higher vapour pressure from vehicular service stations, and also from
waste decomposition in the hotter months (Talapatra and Srivastava, 2011). VOC emis-
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sion from solvent evaporation is less significant at very low temperature (5.3±2.1 ◦C)
during winter.
In general, variation in VOC concentrations between hotter and colder months over
plain land cities is addressed with the help of vertical advection through boundary layer
dynamics in addition to other meteorological factors. The low VOC concentration dur-5
ing summer is generally associated to favourable vertical mixing due to high boundary
layer/mixing height whereas comparatively higher VOC concentration during winter is
associated to calm and stable atmospheric condition with low boundary layer/mixing
height restricting vertical dissipation. The boundary layer dynamics has been used for
addressing seasonal variation of VOCs for most of the studies conducted over several10
Indian cities (Talapatra and Srivastava, 2011 and several references therein). But the
case of Darjeeling is unique, unlike plain land cities, the seasonal variation in VOC
concentration could not be addressed through boundary layer dynamics as the sta-
tion itself is situated at a height of 2.2 km, well above the boundary layer. But there
is a probability that boundary layer could reach the altitude of Darjeeling during pre-15
monsoon under high convective activities. Thus, VOCs emitted from plain land regions
could reach Darjeeling after their vertical advection and could contribute and enhance
VOC concentrations over Darjeeling. But, photochemical degradation under high solar
insolation over Darjeeling could have hindered the development in VOC concentrations
during premonsoon.20
4.3 Day and night time VOCs: role of anthropogenic and meteorological factors
VOC concentrations over Darjeeling were compared between day and night time for
different seasons in order to investigate the potential impact of the variability in emis-
sion sources and/or meteorological factors between day and night time. The night to
day ratio was greater than 1.0 in each season. We infer that although the emissions25
were high, the photochemical degradation could decrease the day-time VOC concen-
trations. Thus, night-time VOCs could be attributed to the VOCs generated during night
(which could not degrade by photolysis) plus residual VOCs generated during day-time.
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Another important factor is higher wind speed during daytime which could favour the
dispersion of VOCs more than night. The ratio for TVOC was highest during premon-
soon (1.9) followed by postmonsoon (1.4), monsoon (1.2) and minimum during winter
(1.1). The highest ratio in premonsoon could be due to the removal of VOCs by ef-
ficient and faster photo-degradation by very high solar insolation favoured by much5
higher dispersion due to higher wind speed during day time in premonsoon leading to
high level of VOCs compared to the other seasons. However, the minimum value of
the ratio in winter could be due to massive biomass burning during winter nights which
could enhance night-time VOC concentrations.
4.4 Contribution of long distant source regions to VOCs over Darjeeling10
The transport of air masses from distant sources could affect the pollutant concen-
trations at the study site in conjunction with the local sources. In order to investigate
the transport of VOCs from long distances, we have computed 36 h air-mass back
trajectories, arriving at an altitude of 500 ma.g.l. over Darjeeling for all the days on
which VOCs were measured, using Hybrid Single Particle Lagrangian Integrated Tra-15
jectory (HYSPLIT) model (http://www.arl.noaa.gov/ready/hysplit4.html). Over the entire
period of study, we have identified three major source regions for long range trans-
port as shown in Fig. 3. The frequency of transport from each of the source regions
has also been shown in the figure. Region 1 corresponds to the transport from SE
directions and the air masses originated from southern part of West Bengal, India20
and Bangladesh with the frequency of 32 %. The average TVOC concentration as-
sociated to Region 1 was found to be 117.2±86.1 µg m−3. Region 2 corresponds to
the transport from W/NW directions and the air masses originated from eastern and
central part of Nepal with the frequency of 42 %. The associated TVOC concentra-
tion was found to be 831.5±955.2 µg m−3. Region 3 corresponds to local/regional25
sources and the air masses originated mainly from the E/SE directions with the fre-
quency of 26 %. The major regions were northern part of West Bengal and the av-
erage TVOC concentration was found to be 620.1±535.4 µg m−3. Thus, the contri-
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bution from Nepal (Region 2) was found to be ∼7 and 1.5 times higher than West
Bengal/Bangladesh (Region 1) and local/regional sources (Region 3) respectively. The
contributions from each source regions were also investigated for different seasons.
The average TVOC concentrations associated to respective source regions along with
their frequencies have been given in Table 2 season-wise. It was observed that during5
monsoon, all the air masses originated from Region 1 with 100 % frequency with the
average TVOC concentration of 117.2±86.1 µg m−3. Similarly, during winter, 100 % air
masses originated from Nepal with the TVOC concentration of 60.9±28.0 µg m−3. Dur-
ing postmonsoon, 60 % air masses originated from local/regional sources (Region 3)
and 40 % originated from Nepal (Region 2) with the average TVOC concentrations of10
1206.8 ±628.3 µg m−3and 2978.1 ±1538.1 µgm−3respectively. It was observed that
50 % air masses originated from local/regional and 50 % originated from Nepal during
premonsoon and the TVOC concentration associated to Nepal was found to be slightly
higher (46.2 ±12.5 µg m−3) than local/regional sources (34.2 ±11.3 µg m−3). This re-
sult indicates that the air masses coming from Nepal carried more VOCs and thus15
more polluted compared to other source regions. It is important to mention over here
that the altitudes of the air masses were below 1000 m a.s.l. throughout their trajec-
tories/pathways originating from their source regions. Thus the air masses could pick
up the boundary layer pollutants of the regions they passed over before reaching our
observational site.20
As Nepal was found to be most polluted source regions, an attempt was made to
roughly estimate the contribution of TVOC from Nepal in postmonsoon and premon-
soon seasons. During these two seasons, air masses originated both from Nepal and
local/regional source regions and thus contribution from Nepal was estimated in terms
of the relative concentrations associated to these two regions. The estimation has been25
made by the following equation:
% contribution from Nepal =(ECNepal/MCTotal)×100 =((MCTotal −MCLocal)/MCTotal)×
100, where ECNepal is the estimated concentrations of TVOC coming only from Nepal
i.e. additional amount of TVOC coming from Nepal. MCTotal is the measured concentra-
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tion of TVOC on respective days when air masses generated from Nepal i.e. with the
total contribution of both Nepal and local air masses. MCLocal is the average measured
concentration of TVOC on all the days when air masses originated from local sources
i.e. contribution from local sources only. It was observed that VOCs from Nepal con-
tributed to the TVOC concentration over Darjeeling by 38–54% with the average of5
∼53 % during postmonsoon and 32–65 % with the average of ∼50 % during premon-
soon.
4.5 Effect of local and long distant sources on the variability–lifetime relation-
ship for VOCs
The relationship between the variability in concentrations and the life time of VOCs can10
be used to estimate the distance of their source regions regardless the influence of
the regional transport. The following empirical equation was first proposed by Jobson
et al. (1998).
Slnx =Aτ−b
Where Slnx is the SD of the natural logarithm of the concentration Xof VOC, τis the15
atmospheric lifetime of VOC, Aand bare the fit parameters.
The value of exponent blies between 0 and 1 and describes the influence of the
source contribution. The value of bwill approach zero when sampling site is closed
to a source and the variability–lifetime relation will be “weaker”. In the extreme case,
when b=0, the variability will not depend on the atmospheric lifetime but will depend20
on the variability of the emission sources. In remote areas bwill approach 1 (Jobson
et al., 1998; Ehhalt et al., 1998; Wang et al., 2005) where the distance of sampling
site is longer from the potential sources. The variability concept is based on the as-
sumption that the chosen compounds have more or less the same source distribution.
The compounds reported in this paper, are mostly of anthropogenic origin (aromatic25
hydrocarbons and halocarbons). We have used their concentrations for premonsoon
and postmonsoon as the sources of VOCs are same in both the seasons. We have
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calculated the back trajectory analysis for each sampling day and based on the tra-
jectories we have separated the transported air masses from the local emissions (as
discussed above). Figure 4 shows the relationship of variability with lifetime for different
VOC species separately for long range transport and local emissions. It can be seen
that the value of bwas higher for long range transport (b=0.19, R2=0.79) than for5
local emission (b=0.09, R2=0.64). The value of bfor long distant sources (0.19) as
obtained in the present study was found to be slightly lower than 0.22 as observed
over Mount Tai, China (Ting et al., 2009) and 0.23 as obtained in the Mediterranean
Intensive Oxidant Study (MINOS) in August 2001 on Crete (Gros et al., 2003). But, it
was much lower than 0.44 as observed over the remote NARE locations (Jobson et al.,10
1999) and 0.41 on a cruise through the western Indian Ocean during the INDOEX
field study (Karl et al., 2001). Thus, Darjeeling does not represent a remote site where
the variability is strongly dependent on the lifetime of VOC but represent a typical ur-
ban site in the vicinity of sources where the sources dictate the variability and not the
chemistry. The longest source regions (Central part of Nepal or southern part of West15
Bengal/Bangladesh) for VOCs over Darjeeling as estimated from HYSPLIT trajectory
models were within 200 km from Darjeeling.
4.6 Characterization of sources of VOCs by Positive Matrix Factorization
receptor model
In recent years, an advanced receptor model, Positive Matrix Factorization (PMF),20
has been applied extensively in identifying VOC contributing sources at different lo-
cations in the world (e.g., Jorquera and Rappengluck, 2004; Latella et al., 2005; Xie
and Berkowitz, 2006; Brown et al., 2007; Song et al., 2007; Yuan et al., 2009). PMF
does not require any priori knowledge on the exact VOC emission profiles, and it can
be used to apportion source contributions solely based on observations at the recep-25
tor site, thus avoiding VOC decay adjustment problem. More details about the PMF
method were described by several studies (Paatero and Tapper, 1994; Paatero, 1997;
Reffet al., 2007).
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In this study, the PMF method has been applied to identify the possible sources of
VOCs over Darjeeling. Table 3 shows the source profiles derived by the PMF model.
Eight factors were selected according to the resulted stable Qvalues. Figure 5 shows
the percentage contribution of each VOC associated to each of eight sources.
Table 3 shows that Factor 1 is dominated by high values of BTEX with much higher5
concentrations of benzene and toluene followed by ethylbenzene and xylene. Toluene
to benzene ratio was found to be 0.9 in this factor. Thus factor 1 could be associ-
ated to the gasoline-related emissions. VOC emissions from gasoline may occur along
many pathways like, evaporative emission from gas stations and bulk terminals and ex-
haust released from the gasoline-powered vehicles during gasoline combustion (Wat-10
son et al., 2001; Choi and Ehrman, 2004). BTEX are the major components of vehicular
exhaust, as shown by many studies (Watson et al., 2001; Guo et al., 2006, 2007; Som
et al., 2007). High VOC emissions from tourist vehicles during premonsoon and post-
monsoon seasons and the gasoline vapours from the frequent use of the gas stations
are the most important contributors to this source over Darjeeling.15
Factor 2 is also dominated by BTEX. Toluene was found to have the maximum contri-
bution followed by benzene, ethylbenzene and xylene. The toluene to benzene ratio is
2.5 in this factor. Previous study of the authors (Som et al., 2007) reported the same ra-
tio in a study made over Kolkata, India for the VOCs emitted from diesel-driven vehicles.
This factor is associated to diesel exhaust. It is interesting to observe that the number20
of petrol and diesel driven vehicles are nearly same over Darjeeling and PMF result
indicates the percentage contribution of TVOCs from Diesel and gasoline sources are
also comparable (discussed later in details).
Factor 3 is characterized by the high values of TEX. TEX being the primary con-
stituents of solvents (Guo et al., 2004b; Choi et al., 2011), often used as a solvent in25
paints, coatings, synthetic fragrances, adhesives, inks and cleaning agents, in addition
to its use in fossil fuel (Borbon et al., 2002; Chan et al., 2006). This factor can therefore
be assigned to the solvent usage and related emission. The rapid growth in tourism
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related infrastructure like hotels, resorts, restaurants etc over Darjeeling could be the
reason for high VOC emission from solvent usage.
Factor 4 is characterized by the high values of n-propyl benzene, 2-chloro toluene
and BTEX and could be assigned to solid waste disposal. Majumdar et al. (2014) re-
ported the high values of these compounds in municipal waste dumping stations in5
Kolkata, India. With the dramatic increase in tourists and changing consumption pat-
terns, Darjeeling is facing immense problems of waste management. The existing sys-
tems of waste management are technically unscientific and the infrastructure is insuffi-
cient to manage the waste.
Factor 5 is dominated mainly by chloroform and carbon tetrachloride and thus the10
factor could be associated to chlorine bleach containing house hold products. Odabasi
et al. (2008) showed that house hold cleaning agents and fresheners produce these
two VOCs significantly. Chloroform and carbon tetrachloride are the major compounds
along with several halogenated compounds in chlorinated bleach products.
Factor 6 is dominated by m-xylene and ethylbenzene followed by n-butylbenzene and15
toluene and could be assigned to industrial sources (Yuan et al., 2010). Although there
is no industry in Darjeeling, but the VOCs could be transported from low land townships
and cities. The m-xylene to ethylbenzene ratio in this factor was found to be 1.8. The
ratio of m,p-xylene to ethylbenzene (X/E ratio) is used as indicator for the age of the
VOCs in the atmosphere (Elbir et al., 2007; Guo et al., 2004b, c). The ratio becomes20
smaller as the VOCs get older in the atmosphere, because m,p-xylene is more reactive
than ethylbenzene. Kuntasal (2005) found X/E ratio to be varied between 3.8–4.4 in
fresh emissions at various environments. The low ratio in this study (1.8) suggests that
the species were not emitted in situ but aged/transported.
Factor 7 is dominated by chloroalkanes, benzene and toluene and could be asso-25
ciated to coal and biomass burning (Fernandez-Martinez et al., 2001; Barletta et al.,
2009). Coal burning is a significant anthropogenic source in Darjeeling as it is used for
the domestic cooking purpose and it is also used in a large scale for coal engines in
the toy trains. In addition to that, massive biomass burning during winter to get warmth
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against cold and probable transportation of biomass burning species from northern In-
dian states (as discussed earlier) during postmonsoon could enhance those VOCs in
the atmosphere of Darjeeling.
Factor 8 is characterized by high values of aromatics with high molecular weight like
1,2,3-tri methyl benzene, 1,2,4-trimethyl benzene, o-xylene. Liu et al. (2005) reported5
high emissions of these VOCs from asphalt related road construction works. Road
construction works were in progress in and around Darjeeling during few sampling
events. Thus the factor 8 could be assigned to the asphalt related emission.
Figure 6 shows the percentage contributions of each source to the total VOC loading
over Darjeeling during the entire study period. It can be seen that the major sources10
are diesel exhaust (32%) and gasoline exhaust (29 %) followed by solvent evaporation
(18 %). Chlorine bleach containing house hold products and solid wastes contributed
equally (6 %) whereas industrial sources situated at the regions far from Darjeeling,
coal/biomass burning and asphalt related constructional works contributed nominally
by 4, 3 and 2 % respectively. Thus it can be concluded that the major source of VOCs15
over Darjeeling is gasoline and diesel driven vehicular activities which contributed by
more than 60 %.
4.7 Ozone formation potential of VOC sources
In order to investigate the potential of various VOC sources (as derived from PMF
model) to the tropospheric ozone formation over the study area we have computed20
the ozone formation potential (OFP) of each source using the Maximum Incremental
Reactivity (MIR) values derived by Carter (2008). To do this, we have used the equation
derived by Na and Kim, (2007).
OFPi=Si×
n
X
j=1
(αji ×MIRj)
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Where, OFPiis the estimated contribution of ith source to OFP, Siis the total mass
contribution of the source i,αji is the mass fraction of species jin source iand MIRjis
MIR value of species j. Figure 7 shows the relative contribution of each source to OFP.
It can be seen from the figure that diesel exhaust has the maximum potential (45%)
followed by solvent (24%) and gasoline exhaust (18 %). Although, Gasoline exhaust5
contributes more (29 %) towards TVOC concentration than solvent usage (18%), the
later source is contributing more towards tropospheric ozone generation. The MIR val-
ues of the individual species are also responsible for the total OFP of a source along
with the corresponding source strength. Thus, vehicular emissions and solvents could
play the key role in the formation of tropospheric ozone and have the potentials to10
modify the tropospheric ozone budget.
4.8 Comparison with other studies
The concentration of BTEX over Darjeeling (present study) has been compared with
that over several metro cities in India and also with other cities in Asian, European,
African, Arabian and American countries (Table 4). We have taken the sum of BTEX15
(not TVOC) for comparison as the data of BTEX is more available in the literature.
Table 4 shows that BTEX over Darjeeling is lower than the commercial, industrial
and the areas with high traffic density (traffic intersection) over Delhi, the capital city
of India; traffic intersection and petrol pumps over Mumbai, a metro city in western
India and Hyderabad, a metro city in south-eastern India. This is quite expected as20
the vehicular and industrial activities over those metro cities are much higher than
Darjeeling. But the most interesting fact is that BTEX over Darjeeling shows ∼3, ∼2
and ∼5 times higher concentrations than residential areas over Kolkata (a mega city
in eastern India), Delhi and Mumbai respectively. Even, Darjeeling shows higher BTEX
concentrations than commercial areas of Mumbai and much higher than roadside (∼1025
times) and petrol pump (∼7 times) areas in Agra, a city in northern India with much
less vehicular activities compared to other Indian metro cities.
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BTEX over Darjeeling was found to be much higher (10–25 times) than the residen-
tial/industrial/commercial areas of Turkey, Houston, Rome and Paris; 2–6 times higher
than residential/commercial areas of Bangkok, Yokohama, Kuwait and Hongkong; 1.5–
2 times higher than roadside/industrial/commercial areas of Kaohsiung, Sanghai and
Beijing. Darjeeling shows much higher (∼8 times) BTEX concentration than Gongga5
Mountain, a high altitude (1640 ma.s.l.) remote station in southwestern China. How-
ever, BTEX over a commercial area with heavy traffic density in Cairo, Egypt shows 1.7
times higher concentration than that over Darjeeling.
In our earlier study (Sarkar et al., 2014), we also reported much higher concentra-
tion of black carbon aerosols over Darjeeling compared to other high altitude Himalayan10
stations in India and Nepal and some of the metro cities in India like Ahmedabad, Ban-
galore, Trivandrum and Chandigarh. The present study corroborate with that findings.
The major source for black carbon aerosol and VOCs over Darjeeling is same, vehic-
ular emissions. Thus, Darjeeling represents a typical urban atmosphere at eastern Hi-
malaya with high loading of carbonaceous pollutants. This could be due to high anthro-15
pogenic emissions related to tourist activities, high population density and moreover it’s
unique orography and land use pattern with narrow roads, unplanned township, poor
administrative control on solid waste disposal and burning of these wastes, unplanned
constructions of buildings/hotels/resorts which reducing open space/area which in turn
prevents ventilation and dispersion of pollutants.20
5 Conclusion
The major findings of the study on VOCs conducted over Darjeeling, a high altitude hill
station over eastern Himalaya in India are as follows:
1. The annual average concentrations of TVOC, BTEX, non-BTEX aromatics and
halocarbons were 376.3±857.2, 275.1±685.7, 88.6±220.1 and 21.5±15.4 µg m−3
25
respectively with the maximum contribution from BTEX (72%), non-BTEX aromat-
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ics (22 %) and halocarbons (6 %). Toluene was found to be the most abundant
VOC over Darjeeling which contributed 37 % to the TVOC.
2. Concentration of TVOC showed well defined seasonal variations with maximum in
postmonsoon (1649.9±875.4 µg m−3) followed by monsoon (117.1±88.3 µg m−3),
winter (60.4 ±28.2 µg m−3) and minimum during premonsoon (35.9±9.7 µg m−3).5
The seasonal variation in VOC concentration was mainly governed by the photo-
chemical degradation process rather than the emission source strength. Although,
the anthropogenic activities related to massive tourist influxes during premonsoon
and postmonsoon were comparable, the solar radiation made the difference be-
tween premonsoon and postmonsoon VOC concentrations.10
3. Other than local sources, two major regions were identified for VOCs over Darjeel-
ing; Nepal and southern part of West Bengal, India/Bangladesh. It was observed
that VOC concentration over Darjeeling was higher when air masses arrived from
Nepal than West Bengal, India/Bangladesh and local/regional source regions. The
relationship between variability and lifetime of VOC was discussed and it was ob-15
served that Darjeeling represents the site in the vicinity of sources as compared
with other studies.
4. Positive matrix facorization receptor model was used to characterize the sources
of VOCs over Darjeeling. It was observed that the major source of VOC over
Darjeeling was emission from petrol and diesel driven vehicles which contributed20
by more than 60 % followed by solvent evaporation (18%) and other sources.
5. Diesel exhaust was found to have the maximum potential (45 %) in the forma-
tion of tropospheric ozone followed by solvent evaporation (24 %) and gasoline
exhaust (18 %).
6. The atmospheric loading of BTEX over Darjeeling was comparable with Indian25
metro cities and much higher than other Asian, American, African, Arabian and
European countries.
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Thus we found that Darjeeling represents a typical urban atmosphere over eastern
Himalaya in India from the point of view of VOC pollution. The high VOC pollution over
Darjeeling draws a serious attention as it could significantly affect human health as well
as the sensitive ecosystem over this part of Indian Himalaya. Study result emphasis the
need for better pollution control system for the vehicles plying on the road of Darjeeling.5
Imposing regulations on uncontrolled solvent usage is also necessary. Better Solid
waste management system is also called for. This year long data set of VOC can be
used to make further studies on the modification of the budget of tropospheric ozone,
NOxand other gaseous and particulate pollutants. This would, in turn, help us to make
studies on the implications of VOCs for regional atmospheric chemistry over eastern10
Himalaya.
Author contributions. C. Sarkar, A. Chatterjee, D. Majumdar, S. K. Ghosh, A. Srivastava and
S. Raha conceived and designed the experiment. C. Sarkar and A. Chatterjee performed the
experiment. C. Sarkar and D. Majumdar analyzed the samples. D. Majumdar and A. Srivastava
supplied the materials/chemicals and instruments for chemical analysis. C. Sarkar, A. Chatter-15
jee and D. Majumdar analyzed the data. A. Chatterjee, C. Sarkar and D. Majumdar prepared
the manuscript with the contribution of rest of authors.
Acknowledgements. Authors would like to thank Science and Engineering Council, Department
of Science and Technology, Government of India for supporting the study under IRHPA (Intensi-
fication of Research in High Priority Areas) scheme. Authors also like to thank University Grant20
Commision, Govt of India for providing fellowship to C. Sarkar (first author). The study was un-
dertaken by Bose Institute in collaboration with CSIR-NEERI. Field study conducted by Bose
Institute and sample analysis performed by CSIR-NEERI, Kolkata Zonal Laboratory. Thanks
are due to Sabyasachi Majee, Bose Institute for his consistent support in sampling and De-
basish Sengupta and Pamela Chowdhury, NEERI for their assistance during sample analysis.25
Authors would also like to thank D. K. Roy, Bose Institute for his overall logistic support.
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Table 1. Statistical summary of the concentration of each VOC component over the entire
period of study (all the concentrations are in µgm−3).
Mean SD Max Min
1,1-Dichloroethane 2.80 4.58 19.75 BDL
1,2-Dichloroethane 0.44 0.79 6.82 BDL
Chloroform 17.89 17.03 86.81 1.62
Carbon Tetrachloride 0.18 0.27 1.65 BDL
Benzene 81.19 212.16 1166.20 2.01
Toluene 140.67 430.03 2304.38 2.67
Ethylbenzene 32.69 93.35 563.50 1.06
m-Xylene 19.93 38.59 216.68 0.91
o-Xylene 0.87 1.47 7.60 BDL
Isopropylbenzene 12.07 44.88 267.06 0.66
n-Propylbenzene 4.82 9.66 48.48 BDL
2-Chlorotoluene 5.79 13.33 75.42 BDL
1,3,5-Trimethylbenzene 24.56 99.44 647.09 0.87
1,2,4-Trimethylbenzene 3.21 6.14 45.16 BDL
sec-Butylbenzene 3.72 12.20 104.61 0.05
4-Isopropyltoluene 28.45 125.05 752.62 0.72
1,4-Dichlorobenzene 0.38 0.98 6.87 BDL
n-Butylbenzene 3.85 7.86 58.23 0.04
Naphthalene 1.12 3.84 36.46 BDL
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Table 2. TVOC concentrations for various source regions over different seasons and entire
study period.
Period Regions Direction Source region Frequency [TVOC] µgm−3
Region 1 S/SE Bangladesh and West Bengal 32 117.2 ±86.1
Annual Region 2 W/NW Nepal 42 831.5 ±955.2
Region 3 E/SE Local/Regional 26 620.1 ±535.4
Monsoon Region 1 S/SE Bangladesh and West Bengal 100 117.3 ±86.5
Postmonsoon Region 3 E/SE Local/Regional 60 1206.8 ±628.3
Region 2 W/NW Nepal 40 2978.1 ±1538.1
Winter Region 2 W/NW Nepal 100 60.9 ±28.0
Premonsoon Region 2 W/NW Nepal 50 46.2 ±12.5
Region 3 E/SE Local/Regional 50 34.1 ±11.3
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Table 3. Source profiles of several factors estimated from PMF model.
Gasoline Diesel Solvent, Solid Chlorine Industrial Coal Asphalt
Exhaust Exhaust Paint Waste Bleach Source Burning Related
Disposal Products Emission
Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor 7 Factor 8
1,1-Dichloroethane 0.00 0.01 0.00 0.03 0.16 0.00 2.14 0.00
1,2-Dichloroethane 0.01 0.04 0.01 0.00 0.01 0.01 0.16 0.03
Chloroform 0.69 0.21 0.00 0.45 13.03 0.55 2.62 0.26
Carbon Tetrachloride 0.00 0.00 0.00 0.00 0.08 0.00 0.06 0.00
Benzene 43.35 22.49 0.00 2.43 1.90 0.00 2.49 0.00
Toluene 37.82 55.35 18.36 2.70 1.23 0.99 1.59 1.25
Ethylbenzene 3.15 15.09 0.36 3.09 0.00 2.97 0.19 0.24
m-Xylene 2.29 5.15 1.50 3.36 0.13 5.43 0.00 0.00
o-Xylene 0.00 0.00 0.00 0.00 0.02 0.14 0.00 0.48
Isopropylbenzene 0.42 0.50 8.71 0.37 0.34 0.10 0.00 0.18
n-Propylbenzene 0.00 0.41 0.09 3.09 0.06 0.25 0.07 0.26
2-Chlorotoluene 0.41 0.00 0.00 3.89 0.07 0.09 0.11 0.46
1,3,5-Trimethylbenzene 0.00 0.11 0.14 0.01 0.00 0.00 0.09 0.34
1,2,4-Trimethylbenzene 0.00 1.15 0.00 0.00 0.03 0.02 0.21 1.41
sec-Butylbenzene 0.00 0.00 1.17 0.03 0.00 0.06 0.36 0.00
4-Isopropyltoluene 0.00 0.00 26.18 0.75 1.01 0.32 0.00 0.53
1,4-Dichlorobenzene 0.13 0.01 0.02 0.00 0.01 0.00 0.06 0.01
n-Butylbenzene 0.95 0.00 0.00 0.00 0.00 1.99 0.00 0.00
Naphthalene 0.14 0.00 0.03 0.00 0.01 0.00 0.06 0.17
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Table 4. Comparison of BTEX concentration over Darjeeling with other cities in India and other
countries
Location Nature of Site Sum of
BTEX
(µgm−3)
Study Period Reference
Darjeeling High altitude tourist station 331.0 Jun 2011–Jul 2012 Present Study
Indian Metro Cities
Delhi Residential area
Commercial area
Industrial area
Traffic intersection
186.0
421.0
411.0
456.0
Oct 2001–Sep 2002 Hoquea et al. (2008)
Kolkata Commercial-cum-residential
area
132.5 Dec 2003–Feb 2005 Majumdar et al. (2011)
Mumbai Residential
Commercial
Industrial
Traffic intersection
Petrol pump
75.8
256.6
281.7
655.6
587.6
May 2001–Apr 2002 Srivastava et al. (2006)
Hyderabad Road side
petrol pump
370.2
2978.8
NA Rekhadevi et al. (2010)
Agra Roadside
Petrol pump
30.0
47.1
Apr 2010–Mar 2011 Singla et al. (2011)
Other cities in Asian, European, African, Arabian and American countries
Beijing, China Road Side, High traffic density 173.7 Aug 2005 Song et al. (2007)
Gongga Mountain, China High altitude remote station 40.3 Jan 2008–Dec 2011 Zhang et al. (2013)
Hong Kong, China Residential area 91.7 Sep–Nov 2010 Lam et al. (2013)
Sanghai, China Commercial 191.7 Jan 2007–Mar 2010 Cai et al. (2010)
Yokohama, Japan Residential-cum-commercial-
cum-industrial
115.9 Jun 2007–Nov 2008 Tiwari et al. (2010)
Ulsan, Korea Residential 23.8 Mar 2010–Feb 2011 Lee et al. (2012)
Kaohsiung, Taiwan High traffic density 202.8 Jul and Oct 2003 Liu et al. (2008)
Bangkok, Thailand Commercial 61.6 Jan–Dec 2009 Ongwandee et al. (2011)
Paris, France Residential-cum-Industrial- 17.9 Jan–Feb 2010 Ait-Helal et al. (2014)
Rome High traffic density 15.9 Dec 2010–Dec 2011 Fanizza et al. (2014)
Cairo, Egypt Commercial 558.9 Jun–Aug 2004 Khoder et al. (2007)
Ankara, Turkey Residential area 13.5 Jan–Jun 2008 Yurdakul et al. (2013)
Kuwait, UAE Residential-cum-commercial 127 Aug 2010–Nov 2011 Al Khulaifi et al. (2014)
Houston, USA Highly industrialized 14.7 Aug–Sep 2006 Leuchner et al. (2010)
32168
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Figure 1. Seasonal variation of micro-meteorological parameters over Darjeeling during the
study period.
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Figure 2. Seasonal variation of (a) TVOC, (b) mono aromatics-BTEX, (c) non-BTEX substituted
aromatics and (d) halocarbons shown in box-whisker plot. The lower boundary of the box,
the horizontal line inside the box and upper boundary of the box represent 25th percentile,
median and 75th percentile respectively. The whiskers below and above represent minimum
and maximum respectively.
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Figure 3. Source regions of VOCs obtained from air mass trajectories of HYSPLIT model.
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Figure 4. Variability–lifetime relationship of different VOCs for local/regional and long distant
source regions.
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Figure 5. VOC source profiles estimated from PMF model.
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Figure 6. Percentage contribution of various sources for VOCs over Darjeeling.
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Figure 7. Ozone formation potential of each source of VOCs.
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