Introduction
Biomass burning (BB) such as domestic biofuel combustion, agricultural residues
and wildfires contributes large amounts of pollutants in the atmosphere, which
include trace gases (e.g., greenhouse gases like CO2 and CH4 and
precursors of O3) and aerosols, especially organic carbon (OC) and black
carbon (BC) (Crutzen et al., 1979; Andreae and Merlet, 2001; van der Werf et
al., 2006). These pollutants can cause adverse health effects, deteriorate
air quality and affect earth's radiation budget and thus climate (Jacobson,
2014; Ramanathan and Carmichael, 2008). BC absorbs solar radiation and is
primarily responsible for net positive radiative forcing (Bond et al., 2013).
The assessment reports by the Intergovernmental Panel on Climate Change
(IPCC) have reported that the direct radiative forcing of BC and OC from
the BB emissions can offset each other to give an estimated
direct radiative forcing of +0.0 (-0.2 to +0.2) W m-2. However, there are
substantial uncertainties because of the limited information about their
sources, atmospheric loading and composition of organic aerosols which
include light-absorbing organics, known as brown carbon (BrC) (IPCC, 2013).
Due to the hygroscopic property of BB emissions, they also have
a pronounced indirect impact on climate by altering cloud microphysical
properties (Andreae, 2009; Kawamura and Bikkina, 2016). In addition, BB accounts for 4.4 % of total carbon loss in terrestrial ecosystems
and thereby plays an important role in the global carbon cycle (van der Werf
et al., 2006; Hu et al., 2013). Thus BB has drawn increasing
global attention and concern in the recent decades.
To track the BB emissions, organic molecular tracers such as
anhydrosugars (Engling et al., 2009; Fu et al., 2012), resin acids (Kawamura
et al., 2012; Fujii et al., 2015) and water-soluble potassium (K+)
(Cheng et al., 2013; Sullivan et al., 2011; Urban et al., 2012) are widely
exploited for their unique signatures. Levoglucosan (1,6-anhydro-β-D-glucopyranose), the most abundant component among anhydrosugars, is a
distinct and most reliable tracer for BB. It is formed by the
pyrolysis of cellulose (Simoneit, 2002; Simoneit et al., 1999) and can remain
stable in the atmosphere without degradation for at least 10 days (Fraser
and Lakshmanan, 2000). Mannosan and galactosan (isomers of levoglucosan),
generated from the thermal decomposition of hemicellulose, can also be used
as BB tracers (Simoneit et al., 1999; Sang et al., 2013; Urban
et al., 2014). Additionally, phenolic compounds such as p-hydroxybenzoic,
vanillic and syringic acids are released to the atmosphere during the
combustion of lignin (Kawamura et al., 2012; Fu et al., 2012; Fujii et al.,
2015). Dehydroabietic acid is produced during the burning process of
coniferous resins (Simoneit, 2002). Furthermore, ratios of individual tracers
can be also used as indicators for various BB types (Urban et
al., 2012; Engling et al., 2009; Sang et al., 2013). For example, the
levoglucosan-to-mannosan ratios (lev / man) derived from softwood
combustion are frequently lower than 10, but much higher for the burning of
hardwood and crop residues (Cheng et al., 2013). Potassium has also been used
as a conventional BB tracer, but it may suffer from the
interference from soil re-suspension, sea salts and fireworks (Cheng et al.,
2013; Urban et al., 2012).
Map showing the location and general setting of the sampling site of
Lumbini in the northern edge of the Indo-Gangetic Plain.
The Indo-Gangetic Plain (IGP) (Fig. 1) in South Asia is one of the most
densely populated and polluted regions in the world. The large-scale
urbanization, land use changes, industrial activities and regional emission
sources lead to high aerosol loadings over the entire IGP (Ram et al., 2010,
2012; Lawrence and Lelieveld, 2010). It results in formation of widespread
atmospheric brown clouds (ABCs) in IGP and surrounding regions from the
southern flank of the Himalayas to the northern Indian Ocean, especially
during the long dry season from November to May every year (Ramanathan et al.,
2005; Bonasoni et al., 2010). A previous study conducted in India has
demonstrated that residential biofuel combustion and open burning are the
largest sources of OC (87 %) and BC (75 %) emissions (Venkataraman et
al., 2005), much higher than fossil fuel combustion. Consistently, by using
radiocarbon, Gustafsson et al. (2009) confirmed that the biomass combustion
accounted for two-thirds of the bulk carbonaceous aerosols in India.
Recently, several studies have demonstrated that the atmospheric aerosols
from BB in the source region like IGP can be transported over a
long distance to the Himalaya and Tibetan Plateau region (Cong et al.,
2015a, b; Lüthi et al., 2015; Kaspari et al., 2011; Li et al., 2016).
After light-absorbing aerosols, particularly BC, get deposited on the snow
and glacier surface, they accelerate melting of snow fields and glaciers (Xu
et al., 2009). Some BB tracers have been detected in the ice
cores and snow samples from Tibetan Plateau (You et al., 2016; Gao et al.,
2015).
Considering the serious air pollution in South Asia, the SusKat project
(http://www.iass-potsdam.de/en/research/air-quality/suskat) was
launched in May 2012 by the Institute for Advanced Sustainability Studies
(IASS), Germany, with the aim comprehensively understanding air pollution
(emission, atmospheric loading, physical/chemical processes, seasonal
variation, their potential impacts) in northern South Asia, especially in
Nepal, and identifying effective solutions that are rooted in solid science
and carefully examined local conditions for reduction of air pollution
impacts in the region. IASS and the International Centre for Integrated
Mountain Development (ICIMOD) jointly coordinated and carried out the
SusKat-ABC international air pollution measurement campaign in Nepal during
December 2012–June 2013 in collaboration with 16 other research institutes.
Lumbini, a rural site in Nepal, which was one of the regional sites for the
SusKat-ABC campaign, was chosen as a representative of the northern IGP
region. The total suspended particles (TSP) sampling at Lumbini was started
during the SusKat-ABC campaign and continued, after the campaign, for a
period of 1 year.
Biomass is the most common source of primary energy consumption in Nepal
(WECS, 2010). In spite of the potential importance of emissions from regional
BB in the air quality, health, agriculture, glacier melting and
regional climate, the concentrations, chemical composition and impact of
BB aerosols in Lumbini and broader surrounding regions,
including the Nepalese part of the IGP and the foothills of the Himalaya, have not
been well characterized yet. Such studies are very critical to understand the
transport mechanism of aerosols and air quality dynamics in the region.
Therefore, in this study, we investigate for the first time the BB tracers in the TSP in Lumbini, as a representative site in the
northern edge of IGP, document their seasonal variations and evaluate the
contributions of BB to regional air quality. The characteristics
of organic aerosols revealed in this study may also be used as fingerprints
to identify the source regions of air pollutants found in the remote
Himalayas–Tibetan Plateau.
Methodology
Sampling site
Lumbini (Fig. 1, 27.49∘ N, 83.28∘ E; 100 m a.s.l.) is
located in the Nepal's southern lowland plain (also Terai region), termed as
“bread basket of Nepal” due to the availability of very fertile land
suitable for crop production. It is also worth mentioning that Lumbini, the
birthplace of Buddha, is a UNESCO world heritage site
(http://whc.unesco.org/). The high Himalayas are about 140 km north of
Lumbini. The flat plains of southern Nepal and India surround the remaining
three sides of Lumbini (Rupakheti et al., 2016). The sampling site is only
about 8 km from the Nepal–India border in the south and within the
agricultural–residential setting. The paddy–wheat crop rotation system is the
main planting pattern. The aerosol loading is very high at Lumbini, as also
seen in data collected by ICIMOD and the government of Nepal in 2016
(www.pollution.gov.np). A previous study reported that daily average
PM2.5 (ranging from 6.1 to 272 µg m-3 with the average
of 53.1 ± 35.1 µg m-3) and PM10 (ranging from 10.5
to 604 µg m-3 with the average of
129 ± 91.9 µg m-3) levels frequently exceeded the WHO
guideline value (25 and 50 µg m-3 for daily PM2.5 and
PM10, respectively) during the pre-monsoon season (Rupakheti et al., 2016).
In terms of meteorological conditions, Lumbini exhibits the typical
characteristics of the IGP climate with wet monsoon season (June–September),
dry winter season (December–February), dry-to-wet transition period or
pre-monsoon season (March–May) and wet-to-dry transition period or
post-monsoon season (October–November). The sampling experiment was
performed on the roof of a tower (15 m above the ground) in the premises of
the Lumbini International Research Institute (LIRI) within the Lumbini master
plan area.
Sample collection
From April 2013 to March 2014, the TSP samples
were collected on a weekly basis using a medium-volume sampler (KC-120H:
Qingdao Laoshan Applied Technology Institute, Qingdao, China) at a calibrated
airflow rate of 100 L min-1. The sampling duration of each sample was
around 20 h each day. The samples in May were missed due to the equipment
breakdown. Overall, 68 samples were collected on the quartz fiber filters
(90 mm diameter; Whatman PLC, Maidstone, UK), which were prebaked at
550 ∘C for 6 h. Filters were weighed before and after sampling using a
microbalance with a sensitivity of ±0.01 mg. They were equilibrated at
constant temperature and humidity (25 ± 3 ∘C, 30 ± 5 %)
for 72 h before and after sampling. The volume of air passing through each
filter was converted into standard atmospheric conditions (25 ∘C,
101.3 kPa). The samples were stored at -20 ∘C prior to laboratory
analysis. To assess the potential contamination, field blank samples were
also collected once each month by placing the filters into the sampler with
no air drawn.
Extraction, derivatization and GC-MS determination
BB tracers including levoglucosan, mannosan, galactosan,
p-hydroxybenzoic acid, vanillic acid, syringic acid and dehydroabietic acid
were detected using the methods adopted from Fu et al. (2008) and Wang et
al. (2008). Briefly, filter aliquots (1.13–6.78 cm2) were extracted
with dichloromethane / methanol (v/v= 2 : 1) under ultrasonication for
30 min (20 mL × 3). The solvent extracts were passed through
quartz wool packed in a Pasteur pipette, concentrated by a rotary evaporator
under vacuum and blown down to dryness with pure nitrogen gas. For sample
derivatization, 50 µL of 99 %
N,O-bis-(trimethylsilyl)trifluoroacetamide with 1 % trimethylsilyl
chloride (BSTFA + 1 %TMCS) and pyridine (v/v= 2 : 1) was added
to the dried extracts and then reacted at 70 ∘C for 3 h.
During the sample pretreatment procedure, the samples were spiked with
appropriate amounts of internal recovery standards, i.e., 2000 ng
methyl-β-D-xylanopyranoside (MXP, 99 %, Sigma) and 200 ng
deuterated (D3) malic acid (D3-malic acid; DMA, CDN isotopes,
99 %). The derivatized fraction was further dissolved to 200 µL
with n-hexane and analyzed by a gas chromatograph–mass spectrometer (GC-MS,
TRACE GC coupled to PolarisQ MSD, Thermo Scientific, USA). The GC instrument
was equipped with a 30 m TG-5MS fused-silica capillary column (0.25 mm in
inner diameter and 0.25 µm film thickness). Splitless injection of
1 µL sample was performed. The GC oven temperature program was
initiated at 50 ∘C, maintained for 2 min, a gradient of
30 ∘C min-1 up to 120 ∘C, then 6 ∘C min-1 up to
the final temperature of 300 ∘C, maintained for 16 min. The MS was
operated in the electron impact mode at 70 eV and an ion source temperature
of 250 ∘C. Full scan mode was used in the range of 50–650 Da. The
total ion chromatogram of these tracers was presented in Fig. S1 in the
Supplement.
Recoveries for target compounds were better than 75 % as obtained by
spiking standards to pre-combusted quartz filters followed by extraction and
derivatization. The internal standard recoveries obtained by the same method
were
better than 90 % for MXP but much lower (70 %) for D3-malic
acid. Field blank filters were analyzed by the procedure used by the samples
above, but no target compounds were detected. Duplicate analyses showed
analytical errors were less than 15 %. The recovery ratios of target
compounds and internal standards are shown in Table S1. The method detection
limits of the target compounds were 0.07–0.11 ng m-3 for an average
total standard volume of 121 m3.
The following standards were obtained: levoglucosan (99 %,
Sigma-Aldrich), mannosan (98 %, TRC), galactosan (97 %, J&K),
p-hydroxybenzoic acid (98 %, AccuStandard), vanillic acid (98 %,
AccuStandard), syringic acid (99 %, Sigma-Aldrich) and dehydroabietic acid
(97 %, TRC). HPLC-grade dichloromethane (DCM), methanol (MEOH), n-hexane
and pyridine for sample derivation were obtained from J.T. Baker (USA).
Individual standard stock solutions were prepared in MEOH at a concentration
of 1000 µg mL-1. These composite standard solutions of three
sugars, four organic acids and two internal standards were prepared by
diluting individual standard stock solutions to 1 µg mL-1
accurately.
Time series of ambient temperature (T), atmospheric pressure (P),
wind speed (WS), relative humidity (RH), planetary boundary layer (PBL) and
visibility (V) at Lumbini from April 2013 to March 2014.
Determination of OC, EC and major ions
OC and EC were analyzed based on the thermal–optical reflectance method
using the thermal–optical carbon aerosol analyzer (DRI model 2001A, Desert
Research Institute, USA), following the Interagency Monitoring of Protected
Visual Environments (IMPROVE) protocol. The details on the method were
described in Wan et al. (2015).
K+, Mg2+ and Ca2+ were determined by using an ion
chromatograph (Dionex, Sunnyvale, CA, USA). In brief, an aliquot of filter
(1.6 cm2) was extracted with 10 mL ultrapure water (Millipore,
18.2 MΩ) with sonication for 30 min. The extracted solutions were
filtrated with syringe-driven filters (MillexGV PVDF, 0.22 µm;
Millipore, Ireland) to remove the impurities. Finally, K+, Mg2+ and
Ca2+ were determined using Dionex ICS-320. The sample flow rate was
1.0 mL min-1. The uncertainty was less than 5 %. The detection
limits were less than 0.01 µg m-3 (Tripathee et al., 2016).
The mass concentrations of OC, EC, K+, Mg2+ and Ca2+ in this
study were corrected from the field blank values, which were 0.40, 0.01,
0.04, 0.02 and 0.37 µg m-3, respectively.
Meteorological parameters
Daily average time series of various meteorological parameters during the
sampling period are shown in Fig. 2. Wind speed was obtained with the
sensor (model 05103-5, R.M. Young, USA) at 12 m above the ground (Rupakheti
et al., 2016). Planetary boundary layer data were obtained from the
ECMWF (European Centre for Medium Range Weather Forecasts) database
(www.ecmwf.int/en/forecasts). Ambient temperature, pressure, relative humidity and visibility data, which were reported
for the Bhairahawa Airport, ca. 14 km to the east from Lumbini, were
obtained from the website of Weather Underground
(www.wunderground.com).
Summary of the mass concentration of TSP, OC, EC (µg m-3)
and biomass burning tracers (ng m-3) and OC / EC ratio in Lumbini across
pre-monsoon (April 2013, March 2014), monsoon (June, July, August
and September 2013), post-monsoon (October, November 2013) and winter
(December 2013, January and February 2014) during April 2013 to March 2014.
Annual (n= 68)
Pre-monsoon (n= 18)
Monsoon (n= 32)
Post-monsoon (n= 8)
Winter (n= 10)
Compounds
Mean ± SD
Range
Mean ± SD
Range
Mean ± SD
Range
Mean ± SD
Range
Mean ± SD
Range
TSP (µg m-3)
196 ± 132
44.6–631
291 ± 60.7
210–440
82.6 ± 28.7
44.6–143
354 ± 150
114–631
260 ± 112
121–451
OC (µg m-3)
32.8 ± 21.5
5.78–81.6
45.9 ± 17.8
21.3–81.6
16.6 ± 8.15
5.78–37.4
56.7 ± 19.5
18.9–76.2
42.2 ± 20.6
8.29–65.8
EC (µg m-3)
5.95 ± 2.70
1.91–12.9
7.39 ± 1.85
4.79–10.9
4.04 ± 1.30
1.91–7.50
10.00 ± 2.66
4.72–12.9
6.24 ± 1.64
2.24–8.86
OC / EC ratio
5.16 ± 2.09
2.41–10.3
6.39 ± 2.38
3.00–10.3
3.96 ± 1.05
2.41–7.05
5.50 ± 0.87
4.01–6.43
6.54 ± 2.68
3.48–10.2
Levoglucosan
734 ± 1043
1.31–5083
771 ± 524
162–1829
212 ± 279
1.31–889
2206 ± 1753
6.03–5083
1161 ± 1347
3.96–3181
Mannosan
33.2 ± 32.2
0.73–124
38.5 ± 24.8
7.16–89.3
16.4 ± 13.9
0.73–45.7
63.8 ± 37.4
7.89–111
52.9 ± 50.0
1.32–124
Galactosan
31.7 ± 35.0
1.24–142
34.5 ± 25.1
6.38–86.8
14.2 ± 12.9
1.24–45.1
66.5 ± 48.6
4.21–133
55.0 ± 52.3
3.47–142
p-Hydroxybenzoic acid
9.36 ± 10.8
0.23–39.7
16.6 ± 10.5
3.95–39.7
2.05 ± 2.07
0.23–7.08
20.9 ± 13.5
0.92–33.1
10.5 ± 9.55
0.93–26.3
Vanillic acid
7.59 ± 8.87
0.28–37.1
10.2 ± 6.89
2.57–25.8
2.26 ± 2.06
0.28–7.85
17.5 ± 11.4
0.62–33.9
12.0 ± 12.5
1.29–37.1
Syringic acid
5.81 ± 6.02
0.20–25.0
6.81 ± 4.66
1.42–17.6
3.06 ± 3.03
0.20–10.6
12.1 ± 8.20
0.42–22.8
7.72 ± 8.72
0.86–25.0
Dehydroabietic acid
1.75 ± 0.96
0.60–4.85
2.13 ± 1.00
0.64–3.85
1.17 ± 0.37
0.60–1.97
3.00 ± 0.71
1.82–3.82
1.94 ± 1.12
0.65–4.85
Anhydrosugars
799 ± 1105
3.53–5327
843 ± 574
175–2005
243 ± 302
3.53–972
2336 ± 1834
18.1–5327
1269 ± 1447
8.74–3447
Total lignin and resin products
24.5 ± 25.5
1.58–93.3
35.7 ± 22.4
8.88–86.9
8.54 ± 7.11
1.58–25.2
53.6 ± 31.3
3.78–93.3
32.2 ± 31.2
5.02–90.8
Total biomass burning tracers
824 ± 1128
5.32–5421
879 ± 596
184–2091
252 ± 309
5.32–995
2390 ± 1861
21.9–5421
1301 ± 1477
13.8–3538
Annual and seasonal means of lev / man and syr / van ratios
and contributions of OC and EC to TSP, of lev to OC, EC and TSP, of total
anhydrosugars to OC and TSP, of total BB tracers to OC and TSP and of BB–OC
to OC and TSP.
Annual (n= 68)
Pre-monsoon (n= 18)
Monsoon (n= 32)
Post-monsoon (n= 8)
Winter (n= 10)
Contributions
Mean ± SD
Range
Mean ± SD
Range
Mean ± SD
Range
Mean ± SD
Range
Mean ± SD
Range
OC / TSP (%)
18.6 ± 9.36
6.86–62.1
15.9 ± 5.69
7.76–25.1
21.5 ± 12.0
7.66–62.1
16.7 ± 3.88
10.3–21.9
16.0 ± 5.43
6.86–26.6
EC / TSP (%)
3.93 ± 2.00
1.60–10.4
2.61 ± 0.77
1.64–4.95
5.29 ± 2.06
2.50–10.4
3.09 ± 0.77
1.60–4.13
2.64 ± 0.95
1.82–4.32
Lev / OC (%)
1.61 ± 1.58
0.004–6.67
1.53 ± 0.57
0.72–2.87
0.98 ± 1.05
0.00–3.57
3.34 ± 2.53
0.03–6.67
2.40 ± 2.10
0.02–4.83
Lev / EC (%)
9.85 ± 11.9
0.03–47.9
10.5 ± 6.55
2.86–23.2
4.36 ± 5.02
0.03–17.7
19.9 ± 15.7
0.13–41.7
18.3 ± 20.3
0.07–47.9
Lev / TSP (%)
0.31 ± 0.33
0.003–1.30
0.27 ± 0.18
0.06–0.68
0.23 ± 0.28
0.00–0.99
0.58 ± 0.48
0.01–1.30
0.42 ± 0.45
0.00–1.13
Anhydrosugars / OC (%)
1.79 ± 1.66
0.01–6.99
1.68 ± 0.62
0.81–3.14
1.16 ± 1.12
0.01-3.92
3.55 ± 2.63
0.10–6.99
2.63 ± 2.26
0.04–5.24
Anhydrosugars / TSP (%)
0.34 ± 0.35
0.01–1.36
0.29 ± 0.20
0.06–0.75
0.26 ± 0.30
0.01–1.08
0.62 ± 0.51
0.02–1.36
0.46 ± 0.48
0.01–1.23
Total BB / OC (%)
1.86 ± 1.69
0.01–7.11
1.75 ± 0.64
0.85–3.24
1.21 ± 1.14
0.01–4.03
3.63 ± 2.67
0.12–7.11
2.70 ± 2.31
0.07–5.37
Total BB / TSP (%)
0.35 ± 0.36
0.01–1.38
0.31 ± 0.20
0.07–0.77
0.27 ± 0.30
0.01–1.11
0.64 ± 0.52
0.02–1.38
0.47 ± 0.49
0.01–1.25
Lev / Man
15.1 ± 11.2
0.33–45.7
19.7 ± 2.58
15.0–23.6
9.19 ± 7.99
0.42–22.0
27.2 ± 17.2
0.76–45.7
16.1 ± 13.1
0.33–31.4
Syr / van
0.94 ± 0.46
0.39–2.58
0.67 ± 0.15
0.43–0.93
1.27 ± 0.47
0.48–2.58
0.67 ± 0.08
0.56–0.82
0.58 ± 0.12
0.39–0.74
BB / OC (%)
9.02 ± 12.8
0.02–62.4
9.47 ± 6.44
1.99–22.5
2.61 ± 3.43
0.02–10.9
27.1 ± 21.5
0.07–62.4
14.3 ± 16.5
0.05–39.1
BB–OC / OC (%)
19.8 ± 19.4
0.05–81.9
18.8 ± 6.95
8.85–35.2
12.0 ± 12.8
0.05–43.9
41.0 ± 31.1
0.39–81.9
29.5 ± 26.1
0.22–59.4
BB–OC / TSP (%)
3.79 ± 4.06
0.03–15.9
3.29 ± 2.20
0.69–8.41
2.80 ± 3.40
0.03–12.2
7.17 ± 5.95
0.06–15.9
5.13 ± 5.49
0.04–13.8
Seasonal variations in concentrations of TSP, OC, EC and organic
tracers in aerosols collected in Lumbini from April 2013 to March 2014. The
data of May 2013 are missing due to equipment breakdown.
Backward trajectories and fire spots
In order to investigate the possible regional influence of air pollution
outside of Lumbini, 5-day backward air-mass trajectories starting at
500 m above ground level were calculated for every day at 00:00, 06:00,
12:00 and 18:00 UTC from April 2013 to March 2014 using the NOAA HYSPLIT
model (version 4). The Global Data Assimilation System (1∘×1∘) data from the National Center for Environmental Prediction
(http://ready.arl.noaa.gov/gdas1.php) were used in this study. Cluster
analyses were applied to elucidate the characteristic of air-mass origins, in
which three seed clusters were generated for each season. To illustrate the
BB activities in South Asia, the fire spots were obtained from
Fire Information for Resource Management System (FIRMS) operated by the
National Aeronautics and Space Administration (NASA) of the United States
(https://earthdata.nasa.gov/earth-observation-data/near-real-time/firms).
Results and discussion
TSP, OC and EC
The summary of the TSP, OC and EC mass concentrations as well as BB tracers observed at Lumbini are provided in Table 1. Their seasonal
variations are shown in Fig. 3 while the temporal variations are shown in
Fig. S2. The TSP mass concentrations at Lumbini ranged from 44.6 to
631 µg m-3 with the annual mean of
196 ± 132 µg m-3 (arithmetic mean ± standard
deviation) during the sampling period (April 2013 to March 2014) (Table 1).
The TSP concentrations were high during post-monsoon (seasonal average:
354 ± 150 µg m-3), pre-monsoon
(291 ± 60.7 µg m-3) and winter
(260 ± 112 µg m-3) while much lower loadings were
obtained during monsoon season (82.6 ± 28.7 µg m-3)
(Table 1, Fig. 3a). The meteorological parameters indicated that the lower
wind speed (Fig. 2c) and shallow planetary boundary layer (Fig. 2e) during
the post-monsoon and winter could easily form the stagnant weather
conditions, which is favorable for the accumulation of air pollutants. The
visibility (Fig. 2f) was much lower in these seasons, confirming the poor air
quality in the region. Meanwhile, the abundant precipitation during the
monsoon led to the lower TSP concentrations through washout and scavenging.
The annual average mass concentrations of OC and EC in Lumbini were
32.8 ± 21.5 and 5.95 ± 2.66 µg m-3, accounting
for 18.6 ± 9.36 and 3.93 ± 2.00 % of TSP mass, respectively
(Table 2). OC and EC exhibited a large seasonal variability during the
sampling period (Table 1, Fig. 3b and c). The highest seasonally averaged OC
concentration (56.7 ± 19.5 µg m-3) occurred during the
post-monsoon season and the lowest during the monsoon season
(16.6 ± 8.15 µg m-3). Similar seasonal variations were
also reported for other sites in the IGP, such as Delhi (Mandal et al., 2014)
and Kanpur (Ram et al., 2012); i.e., maximum OC occurred in post-monsoon.
However, it was different in Kathmandu, the capital of Nepal. Using a
regional chemical transport model (WRF-STEM), Adhikary et al. (2007)
reported the highest OC and EC concentrations in Kathmandu occurred in March
and April (pre-monsoon season). For the seasonal variations of EC, it also
clearly shared the similar seasonal pattern with OC. In addition, a strong
correlation (R2=0.67, P<0.001) was observed between OC and EC
(Fig. 4a), indicating that they may be derived from common sources.
The OC / EC ratios in TSP of our study were relatively high, ranging from
2.41 to 10.3 with an average of 5.16 ± 2.09. It has been reported that
OC / EC ratios from biomass and biofuel burning emissions and secondary
organic aerosols (SOA) are usually higher than those from fossil fuel sources
(Cong et al., 2015a; Cao et al., 2013; Ram et al., 2012). Watson et
al. (2001) have documented OC / EC ratios of 1.1 for motor vehicle
emissions and 2.7 for coal combustion emissions in the PM2.5 samples.
The high OC / EC ratios in Lumbini might be an indication of biomass
combustion emissions. Similarly, Ram and Sarin (2010) have determined the
OC / EC ratios of 7.87 ± 2.4 in the TSP from three urban sites
(i.e., Allahabad, Kanpur and Hisar) in northern India, where were also under
substantial impacts of BB. Our finding of high OC / EC ratio
at Lumbini in the northern edge of IGP indicates that it is a regional
characteristic of the OC / EC ratio. As both OC and EC play important
roles in radiative forcing and cloud microphysics and consequently on
regional climate change and precipitation, knowledge of the OC / EC ratio
for the IGP and surrounding regions is of particular significance for
reducing uncertainties in quantification of the OC and EC regional radiative
forcing. It should be noted that OC may also originate from non-combustion
sources such as vegetative detritus and fungal spores in the coarse mode,
leading to a high OC / EC ratio in the TSP samples (Yu et al., 2010).
Therefore, those bioaerosols and dust may interfere the OC / EC ratio
somewhat and deserve further study.
Correlations between (a) OC and EC, (b) K+ and
Mg2+, and
(c) K+ and Ca2+ during the entire sampling period of a year (April 2013 to March 2014).
Biomass burning tracers
Biopolymers, including cellulose, hemicellulose, lignin, suberin,
sporopollenin and chitin, are essential components of biomass. When they
are subjected to combustion, varieties of organic molecules are emitted to
the atmosphere. Some of them can be used as specific tracers or markers of
BB sources, such as anhydrosugars, p-hydroxybenzoic acid,
vanillic acid and dehydroabietic acid (Simoneit, 2002).
Comparison of levoglucosan concentrations in Lumbini with other
sites in different locations worldwide.
Correlations between (a) levoglucosan and OC, (b) levoglucosan and
EC and (c) levoglucosan and K+ during the whole year.
Anhydrosugars (pyrolysis products of cellulose and
hemicellulose)
Anhydrosugars such as levoglucosan and its two isomers (mannosan and
galactosan) are specifically formed during the pyrolysis of cellulose and
hemicellulose and are widely used as tracers for BB source
(Simoneit et al., 1999; Engling et al., 2009; Sang et al., 2013; Ho et al.,
2014; Zhu et al., 2015; Zhang et al., 2015). In our ambient aerosols (i.e.,
TSP) over Lumbini, levoglucosan was found as the most abundant BB tracer throughout the year (Table 1 and Fig. 3d), comprising
71.1 % of the total BB tracers detected (Fig. S3). The
annual average concentration of levoglucosan in the aerosols was
734 ± 1043 ng m-3, followed by mannosan
(33.2 ± 32.2 ng m-3) and galactosan
(31.7 ± 35.0 ng m-3) (Table 1). The levoglucosan concentrations
were at least 1 order of magnitude higher than mannosan and galactosan.
Levoglucosan represented 75.5 ± 24.6 % of the total anhydrosugar
concentration (sum of levoglucosan, mannosan and galactosan), while mannosan
and galactosan only accounted for 12.3 ± 12.9 and
12.2 ± 12.9 %, respectively.
Since 90 % of anhydrosugars exist in the particles with aerodynamic
diameters less than 2 µm (Giannoni et al., 2012; Yttri et al.,
2005), it is possible to compare levoglucosan concentrations in our study
with those reported in PM2.5, PM10 and TSP (Fig. 5). When compared
with the areas that are significantly affected by biomass combustion such as
Mt. Tai, China (391 ng m-3) (Fu et al., 2008), Beijing, China
(221 ng m-3) (Yan et al., 2015), K-puszta, Hungary (309 ng m-3)
(Puxbaum et al., 2007), Gent, Belgium (477 ng m-3) (Zdrahal et al.,
2002), and Morogoro, Tanzania (253 ng m-3) (Mkoma et al., 2013), the
concentration levels of levoglucosan in Lumbini were relatively high (annual
average: 734 ± 1040 ng m-3). The concentrations in Lumbini were
even 3 orders of magnitude higher than those from the background site
like Cape Hedo, Okinawa, Japan (3.09 ng m-3) (Zhu et al., 2015).
Therefore, Lumbini ranked among the highest BB-influenced sites
in the world, whose level was comparable with New Delhi (1977 ng m-3)
(Li et al., 2014), Raipur (2180 ng m-3) (Deshmukh et al., 2016) and Rajim
(2258 ng m-3) (Nirmalkar et al., 2015) in India.
We further investigated the correlations of levoglucosan with OC, EC and
K+ (Fig. 6). Throughout the whole year, significant correlations were
found for levoglucosan and OC (Fig. 6a, R2=0.61, P<0.001), as well as
levoglucosan and EC (Fig. 6b, R2=0.42, P<0.001), suggesting their
common sources from the combustion of biomass. It is noteworthy that no
evident correlation was found between levoglucosan and K+ (Fig. 6c),
hinting that there might be other sources of K+ in Lumbini. The strong
correlations between K+ and Mg2+ (R2=0.84, P<0.001) and
between
K+ and Ca2+ (R2=0.78, P<0.001) suggested that dust could be
the major source of K+ (Fig. 4b and c).
Correlations between (a) levoglucosan and p-hydroxybenzoic acid,
(b) levoglucosan and vanillic acid, (c) levoglucosan and syringic acid,
and (d) levoglucosan and dehydroabietic acid in the Lumbini aerosols during the
whole year.
To understand the relative contribution of levoglucosan to OC, the ratio of
lev / OC was calculated (Table 2). The maximum lev / OC ratio was
obtained during post-monsoon season with an average of
3.34 ± 2.53 %, followed by winter (2.40 ± 2.10 %) and
pre-monsoon season (1.53 ± 0.57 %), while the minimum value was
obtained during monsoon with an average of 0.98 ± 1.05 % (Table 2).
The lev / OC ratio in the post-monsoon season was comparable with that of
New Delhi (3.1 ± 0.8 %), where the carbonaceous aerosols were also
attributed to BB (Li et al., 2014). The ratio between
levoglucosan and EC (lev / EC) in Lumbini was also investigated, which
showed the same descending order as lev / OC ratio, i.e.,
post-monsoon > winter > pre-monsoon > monsoon season. Taken
together, the BB emissions have a predominant influence on the
aerosol composition in Lumbini, especially during post-monsoon and winter
seasons. Based on the radiocarbon measurement (14C) of carbon in the
TSP, Li et al. (2016) found that the contribution of BB to EC in
Lumbini aerosols during these seasons was about 51.4 %.
Mannosan and galactosan, which are mainly formed from the pyrolysis of
hemicellulose, showed the similar seasonal variations (Table 1, Fig. 3e
and f) and significant correlations with levoglucosan (Fig. S4). Previous
studies have used the mass concentration ratio of levoglucosan to mannosan
(lev / man) to differentiate the type of BB. Based on the
previous BB studies, Cheng et al. (2013) showed that high
lev / man ratio from hardwood burning is more than 10 whereas it is less
than 10 from softwood combustion. Engling et al. (2009) reported higher
ratios (more than 10) for emissions from burning hardwood and crop residues.
Much higher lev / man ratios of more than 40 were obtained from chamber
experiment burning of rice straw, wheat straw and maize stalks (Zhang et al.,
2007; Engling et al., 2009). In this study, the seasonal average
lev / man ratios were 19.7 ± 2.58 (15.0–23.6), 27.2 ± 17.2
(0.76–45.7) and 16.1 ± 13.1 (0.33–31.4) during pre-monsoon,
post-monsoon and winter, respectively (Table 2 and Fig. S5a). The ratios from
our study during these non-monsoon seasons were close to the reported ratios
of lev / man for hardwood and crop residues. Interestingly, dramatically
high lev / man ratios of 44.3 and 45.7 were observed on 10 and 13
November (during the post-monsoon season), which were more likely associated
with the crop residue combustion (Zhang et al., 2007; Engling et al., 2009).
During the monsoon season (Fig. S5a), lev / man ratios varied over a wide
range (0.42–22.0). The possible reason is due to the different biomass types
burning such as the burning of softwood and hardwood. Nevertheless, the
mechanism is still unclear in Lumbini and more detailed studies are needed in
the future.
p-Hydroxybenzoic, vanillic and syringic acids (lignin pyrolysis
products)
The phenolic compounds such as p-hydroxybenzoic acid, vanillic acid and
syringic acid are major tracers for burning of lignin and have been used as
specific tracers for different biomass types (Simoneit et al., 1993;
Simoneit, 2002). Specifically, p-hydroxybenzoic acid is indicative of
emission from combustion of herbaceous plants (e.g., grass and crop). However, previous studies have reported that vanillic acid is mainly
emitted from burning softwood (gymnosperms) with less contribution from
burning hardwood and grasses, whereas syringic acid is dominantly produced
from burning hardwood (angiosperms) and grasses (Simoneit, 2002; Myers-Pigg
et al., 2016).
These three phenolic compounds were detected in all of the TSP samples at
Lumbini, although their contents were about 1 order of magnitude lower than
levoglucosan (Table 1). To our knowledge, this study presents for the first
time the phenolic compounds in aerosols collected in Nepal. The
concentrations of p-hydroxybenzoic acid ranged from 0.23 to
39.7 ng m-3 in the entire sampling with an average of
9.36 ± 10.8 ng m-3 (Table 1). Vanillic and syringic acids had
the annual mean values of 7.59 ± 8.87 and
5.81 ± 6.02 ng m-3, respectively, which were at a similar level
to p-hydroxybenzoic acid. The seasonal variations of these organic acids were
coincident with levoglucosan (Fig. 3), and they exhibited significant
correlations with levoglucosan (Fig. 7a, levoglucosan and p-hydroxybenzoic
acid (R2=0.64, P<0.001); Fig. 7b, levoglucosan and vanillic acid
(R2=0.85, P<0.001); Fig. 7c, levoglucosan and syringic acid
(R2=0.81, P<0.001)). This implies that these four tracers are emitted
from the common sources, i.e., biomass combustion. These BB
tracers and diagnostic ratios suggest that the burning of herbaceous plants
(grass, dung, agricultural waste, etc.), hardwood and softwood made a mixed
contribution to the organic aerosols in Lumbini.
Recently, the mass ratio of syringic acid to vanillic acid (syr / van)
has been suggested as an indicator to further distinguish the relative
importance of different vegetation burned (Myers-Pigg et al., 2016).
According to the previous studies, the syr / van ratios for burning woody
angiosperm (hardwood) and non-woody angiosperm varied from 0.1 to 2.44, while
it was much lower (i.e., 0.01–0.24) for burning gymnosperm (softwood) (Shakya
et al., 2011; Myers-Pigg et al., 2016). Regarding the ambient aerosol samples
of Lumbini, syr / van ratios varied in the range from 0.39 to 2.58 with
an average of 0.94 ± 0.46 during the sampling period (Table 2),
suggesting that hardwood and grass (including crop residue) are more likely
sources for the BB aerosols in Lumbini. This finding is in
agreement with the results derived from anhydrosugar pyrolysis products
(lev / man), as discussed in Sect. 3.2.1.
Dehydroabietic acid (pyrolysis product of conifer resin)
Dehydroabietic acid is produced by direct emission from the pyrolytic
dehydration of resins that are present in the bark surfaces, needle leaves
and the woody tissues of conifers (Simoneit et al., 1993). Its emission may
be different from those of burning lignin and cellulose (Simoneit et al.,
1993). Hence, dehydroabietic acid can be used as a more specific tracer for
the burning of conifer trees (softwood). In this study, concentrations of
dehydroabietic acid fluctuated from 0.60 to 4.85 ng m-3 with annual
average concentration of 1.75 ng m-3 (Table 1). It was about 2
orders of magnitude lower than that of levoglucosan and 1 order of
magnitude lower than lignin pyrolysis products (i.e., p-hydroxybenzoic,
vanillic and syringic acids). Obviously, dehydroabietic acid showed the
lowest levels among the BB tracers, which demonstrated that the
burning of conifer trees in Lumbini was scarce. Stockwell et al. (2016) also
reported that hardwoods (Sal (Shorea robusta), Bakaino
(Melia azedarach), etc.) are widely used in residential cooking and
heating activities in the Lumbini area. In Nepal, especially in rural areas,
BB is still a major domestic energy source for cooking and
heating. Moreover, open field burning of agriculture residues (specifically,
wheat and paddy straws) is a common way to clean up the croplands after
harvesting.
Contribution of BB to OC
As mentioned above, anhydrosugars (levoglucosan, mannosan and galactosan)
from the pyrolysis of cellulose and hemicellulose can be considered as
indicators of BB emission. In this study, anhydrosugars account
for 1.79 ± 1.66 % of OC annually, with the highest seasonally
averaged value in post-monsoon (6.67 %), which is a major crop residue
burning season in the IGP region. The contribution of anhydrosugars to OC in
Lumbini is comparable with that of the Amazon rainforest sites (2–7 %),
where the burning of forests happened intensively (Graham et al.,
2002).
These values were higher than those of found in the Pearl River Delta sites
in China (0.59–3.12 %) that were directly affected by biomass combustion
in southern China (Ho et al., 2014).
(a) Monthly and (b) temporal variations in the
contributions of biomass burning organic carbon (BB–OC) to organic carbon
(OC) calculated from the diagnostic tracer ratio of lev / OC. The data of
May 2013 are missing due to equipment breakdown.
Since levoglucosan is the most abundant anhydrosugar, the ratio of
levoglucosan to OC measured in source samples of BB has been
widely used to quantitatively estimate the BB contribution to OC
(Zdrahal et al., 2002; Puxbaum et al., 2007; Sang et al., 2011). Andreae and Merlet (2001) have reported
that the lev / OC ratios ranged from 8.0 to 8.2 % (average of
8.14 %) in the burning of savanna, grassland, tropical and extratropical
forests, biofuel and agricultural residues. Sullivan et al. (2008) reported
that levoglucosan in OC was 7.6 % for rice straw burning. Moreover, Zhang
et al. (2007) reported an average of 8.27 % (with a range of
5.4 %–11.8 %) of levoglucosan in OC during the burning of cereal
straw (corn, wheat and rice). The contributions of BB to OC
(based on enrichment factor reception modeling approach) can be inferred as
follows:
Contributions of biomass burning to OC(%)=[lev][OC]ambient[lev][OC]source×100%.
Although the lev / OC ratios in the BB source emissions vary
among different types of biomass fuels and burning conditions (e.g., Mochida
et al., 2010), the average value of 8.14 % has been commonly chosen to
estimate the contributions of BB-derived OC (i.e., BB–OC) to OC (Fu et al.,
2014; Mkoma et al., 2013; Sang et al., 2011; Ho et al., 2014). In this study,
we also use the ratio of 8.14 %. Table 2 shows the seasonal contributions
of BB–OC to OC. Figure 8 presents monthly (a) and temporal (b) variations of
contributions of BB–OC to OC. The calculation showed that BB–OC contributed
19.8 ± 19.4 % (ranging between 0.05 and 81.9 %) of OC in
Lumbini aerosols on an annual basis. This was higher than the contribution of
BB–OC in the Pearl River Delta in China (13.1 %) (Ho et al., 2014) and Hong
Kong (6.5–11 %) (Sang et al., 2011). Moreover, maximum contributions of
BB–OC to OC in our study were observed during post-monsoon
(41.0 ± 31.1 %), which was as high as 58.7 ± 21.7 % in
November.
These results indicated that BB in Lumbini, especially in
post-monsoon season, significantly contributed to ambient organic aerosols
and can significantly affect the regional air quality. Intriguingly, in
Godavari, a rural site at the southeastern edge of the Kathmandu Valley in
Nepal, Stone et al. (2010) reported that primary BB sources
contributed 21 ± 2 % to OC in PM2.5 mass concentrations. It
should be noted that our estimation was based on the empirical values.
Therefore, to restrict the uncertainty of this estimation, the direct
determination of those critical ratios from major emission sources (local and
regional) is needed in the future.
Estimation of secondary organic carbon (SOC)
In addition to the contribution of primary biomass burning to OC, SOA
formation from biomass burning (BB–SOA) should also be taken into
consideration, since BB–SOA (such as some phenol compounds and
methoxyphenols)
can account for a significant fraction of particulate matter derived from
wood combustion: 21 and 45 % of total aerosol masses
(Hawthorne et al., 1989; Yee et al., 2013; Zhang et al., 2015).
EC can be considered a good tracer of primary combustion-generated
carbonaceous aerosols. Therefore, according to the EC-tracer method
(OCpri = EC × (OC / EC)min, OCsoc = OCtot - OCpri; Turpin and Huntzicker, 1995), we roughly calculated that the annual average
concentration of SOC was
14.5 ± 14.0 µg m-3, accounting for
37.2 ± 20.0 % of OC in Lumbini aerosols. Obviously, it was also a
major contributor to OC. Compared with the previous studies, the averaged SOC
based on the EC-tracer in suburban Dayalbagh, IGP, was
13.2 ± 10.8 µg m-3 (Satsangi et al., 2012), which was
similar with our study, but much higher contribution to OC with
49.0–55.0 %. Using the same method, Shakya et al. (2010) estimated
31 % of the SOC to OC in the urban area of Kathmandu during the
wintertime due to the BB influences. Ram and Sarin (2010) also
evaluated ∼ 30 % of SOC to OC at sampling locations in northern
India during wintertime, attributing to the relative dominance of OC derived
from wood fuel and agriculture waste. Additionally, a close relationship was
observed between BB–OC and SOC (Fig. S6a, R2=0.40, P<0.001) but not
between SO42- and SOC (Fig. S6b, R2=0.10, P<0.05), indicating
the predominant role of BB-derived volatile organic compounds in SOC
formation in Lumbini.
Spatial distributions of fire spots observed by MODIS and air-mass
trajectories of Lumbini, northern IGP, shown by clusters of 5-day backward
trajectories arriving at 500 m above ground level during April 2013–March 2014.
The numbers in each panel indicate the percentages of daily
trajectories with the origins.
Sources and regional transport
Besides local emissions, the regional transport of air pollutants also
appears to have an impact on the Lumbini region. To better understand the
source areas, we analyzed 5-day air-mass backward trajectories using
HYSPLIT model along with fire spots acquired with MODIS during different
seasons, and the results are shown in Fig. 9. Five days were chosen because the
atmospheric residence times of carbonaceous aerosols are about a week (Reddy
and Boucher, 2004). It should be noted that the fire spots of MODIS could
reliably represent the occurrence and distribution of active open BB, like the burning of crop residue in the farmland or the forest
fires. However, residential BB for cooking and heating cannot be
detected by the satellite observation.
During the pre-monsoon season, the influence of BB on
carbonaceous aerosols observed in Lumbini was high as seen in Table 2,
Figs. 3 and 5, but it was somewhat less than in post-monsoon and winter. The
concentration levels of OC and EC in pre-monsoon were about 3 times higher
than those in the monsoon season. According to the MODIS active fire
observation in this period (Fig. 9a), there were substantial active fire
spots detected in the area surrounding Lumbini, especially in the areas to
the east and south of Lumbini, which was due to the burning of crop residues
(mainly wheat) by the local farmers after the harvest (Ram and Sarin, 2010).
Although the air-mass trajectories originated in Pakistan and India in the
west and moved eastward towards the site (Lumbini), few fire spots were
detected along the trajectories of the air-mass parcels while passing over
eastern Pakistan and western India. Fire spots are seen to be more
concentrated in areas in India and Nepal surrounding Lumbini (Fig. 9a).
Therefore, the high burden of BB aerosols found in Lumbini in
pre-monsoon season could be attributed to the local agricultural burning.
MODIS image from 1 November 2013 showing the smoke plume over the
IGP and active fire spots (https://worldview.earthdata.nasa.gov/). The blue
square represents the location of Lumbini.
During the monsoon season, there were fewer fire spots detected by MODIS
(Fig. 9b). During the summer, the arrival of southwest monsoon brings
moisture from the Arabian Sea and Bay of Bengal, leading to frequent and
heavy precipitation events and thereby causing the wet season
(June–September) in South Asia. Therefore, the BB emission was
observed to be the least in the monsoon season, which were reflected by not
only in the concentrations of OC, EC and BB tracers but also in
the ratios like lev / OC.
For the seasonality of the composition of aerosols in Lumbini, the most
striking feature drawn in this study was that the air quality (TSP and its
chemical composition) of post-monsoon season received the most significant
influence from BB, especially in November (Figs. 3, 5 and 8).
The aerosol loadings, i.e., TSP, OC, EC, levoglucosan, lev / OC and
BB–OC / OC ratios, together pointed out the importance of BB emissions to atmospheric aerosols in Lumbini region. As shown in
Fig. 9c, intensive fire spots (likely farm fires) were observed during
post-monsoon in northwest India and eastern Pakistan (i.e., Punjab) while
fire spots were scarce around Lumbini. The burning of rice straw residues in
Punjab has been well documented previously (Singh and Kaskaoutis, 2014; Jain
et al., 2014). Extensive agricultural burning in this area lasts for more
than 3 weeks during every post-monsoon season, causing the smoke to
spread widely like a blanket over nearly the whole IGP (Fig. 10), with very high
O3 and CO loadings (Kumar et al., 2016) and particulate matter
concentrations (Rastogi et al., 2016). Concerning the situation in Lumbini,
the flow of air mass is dominated by westerlies in post-monsoon season.
Fifty-three percent of the air-mass trajectories to Lumbini originated around
the most polluted northwestern India and eastern Pakistan (Fig. 9c).
Therefore, it could be reasonably deduced that the serious BB
emissions from agricultural practice in this area could be transported over
long distances to Lumbini in Nepal. The corresponding satellite image from
MODIS (Terra) also showed the intensive air pollution plumes that flowed
toward the east over the IGP, reaching the Bay of Bengal (Fig. 10).
Relatively few fire spots were observed during winter around Lumbini
(Fig. 9d), but the contribution of BB was the second highest in
the whole year (details were presented in Sect. 3.1 and 3.2). This phenomenon
may be caused by the large amounts of indoor burning of mainly biomass fuel
as well as small but numerous fires outside the houses to keep warm from the
cold during intensive cold waves and winter fogs that shroud much of IGP,
including Lumbini, every winter, which could not be detected (especially
indoor fires) by the satellites. In addition, the majority of the air-mass
backward trajectories to Lumbini during this season were local. The
temperature (15.8 ± 3.8 ∘C) during this season was the lowest of
the whole year (Fig. 2a), and therefore local BB for household
heating has enhanced. In addition, the weak wind speed
(1.1 ± 0.4 m s-1) shown in Fig. 2c and low planetary boundary
layer (267.8 ± 63.2 m) shown in Fig. 2e in winter were conducive to
trap the air pollutants near the ground in Lumbini.
Summary and environmental implication
Organic carbon, elemental carbon and biomass burning tracers (levoglucosan,
mannosan, galactosan, p-hydroxybenzoic acid, vanillic acid, syringic acid and
dehydroabietic acid) were studied in the aerosols collected at Lumbini in the
northern edge of the Indo-Gangetic Plain. We analyzed their
abundances, seasonal variations and possible sources. We found that
levoglucosan was the predominant biomass burning tracer among the measured
biomass burning emission tracers, which showed a clear seasonal cycle with
the post-monsoon maximum and monsoon minimum. Levoglucosan showed significant
correlations with OC and EC, highlighting the biomass burning as a
significant contributor to the particulate air pollution in Lumbini. High
levoglucosan / mannosan and syringic acid / vanillic acid ratios were observed
during non-monsoon seasons, indicating that the main burning materials were
mixed crop residues and hardwood with a minor contribution of softwood. Based
on a diagnostic tracer ratio (i.e., levoglucosan / OC), the OC derived
from biomass burning constitutes a large fraction of total OC in ambient
aerosols, accounting for nearly 20 % on annual average and as high as
40 % in the post-monsoon season.
Besides the chemical composition of aerosols, the fire spots observed by
MODIS and air-mass backward trajectories further suggested that the sources
of biomass burning aerosols in Lumbini were dynamic in different seasons. In
the pre-monsoon season, a high burden of biomass burning aerosols appeared
to be due to the burning of wheat residues by the local farmers in the
region, while in the summer monsoon season it exhibited the least influence
of biomass burning. The peak loading of biomass burning aerosols in the
post-monsoon was most likely due to long distance transport of emissions
from agro-residue burning regions in the northwestern India and eastern
Pakistan (e.g., Punjab). In winter, the local usage of biofuel for domestic
heating may contribute to concentrations of organic aerosols under the
favorable meteorological conditions (i.e., shallow planetary boundary layer
and calm winds).
Through the comprehensive analysis of aerosol composition, this study
demonstrated that the biomass burning plays an important role in atmospheric
carbonaceous aerosols and air quality in Lumbini and surrounding regions in
the northern IGP. Given the adverse effects of biomass burning aerosols on
air quality, public health, sensitive ecosystems and regional climate, our
study indicates need for (i) simultaneous investigation of characteristics of
carbonaceous aerosols at multiple site in relatively poorly studied regions
in northern IGP, the Himalayan foothills and the remote sites in the
Himalayas and Tibetan Plateau, which is critical for understanding transport
of air pollutants from South Asia to Tibetan and their impacts;
and (ii) adaptation of appropriate mitigation measures to reduce emissions of
particulate and gaseous air pollutants, notably from biomass burning. Besides
changing agricultural practices, switching to clean fuels or to more advanced
cook stoves that burn the biofuels for cooking and heating more completely
and efficiently will be needed to reduce emissions. Our work clearly revealed
that air pollution observed at Lumbini has both local and regional origin.
Therefore, local actions to reduce air pollution in South Asia are essential
but not sufficient because reduction of regional emissions requires
involvement of different regions and nations. As Lumbini is a World Heritage
Site of universal value as the birthplace of Buddha, reduction of air
pollution at this important site requires local, regional and global
attention.
Recently, the light-absorbing organic carbon, i.e., BrC, in
the aerosols has been a frontline research topic because BrC is
reported to act in the climate system as a warming factor like black carbon.
Biomass burning has been suggested to be the predominant source of BrC (Pokhrel et al., 2017). Our
understanding of organic carbon and brown carbon in this region is far from
adequate and hence large uncertainties remain in quantifying their radiative
forcing (Stockwell et al., 2016).
Therefore, considering the strong influence of biomass burning to
atmospheric OC and BrC over the IGP and surrounding regions, especially
regions to its north, the OC, EC and BrC in this region deserve more
research in the future.