Atmospheric Pollution Research 4 (2013) 214–221

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Atmospheric particulate matter (PM2.5), EC, OC, WSOC and PAHs from NE–Himalaya: abundances and chemical characteristics

Prashant Rajput 1, Manmohan Sarin 1, Shyam Sundar Kundu 2

1 Physical Research Laboratory, Ahmedabad – 380 009, India2 North Eastern Space Applications Centre, Shillong – 793 103, India

ABSTRACTAtmospheric concentrations of elemental, organic and water–soluble organic carbon (EC, OC and WSOC) andpolycyclic aromatic hydrocarbons (PAHs) have been studied in PM2.5 (particulate matter of aerodynamic diameter2.5 m) from a site (Barapani: 25.7 °N; 91.9 °E; 1 064 m amsl) in the foot–hills of NE–Himalaya (NE–H). Underfavorable wind–regimes, during the wintertime (January–March), study region is influenced by the long–rangetransport of aerosols from the Indo–Gangetic Plain (IGP). For rest of the year, ambient atmosphere over the NE–H isrelatively clean due to frequent precipitation events associated with the SW– and NE–monsoon. The concentration ofPM2.5 over NE–H, during the wintertime, varied from 39–348 g m–3, with average contribution of OC and EC as 36±8%(AVG±SD) and 6±3%, respectively. For the OC/EC ratio as high as 10–15 (relatively high compared to fossil–fuel source)associated with WSOC/OC ratio exceeding 0.5 in NE–H, it can be inferred that dominant source of carbonaceousaerosols is attributable to biomass burning emissions and/or contributions from secondary organic aerosols (SOA). TheOC/PM2.5 ratio from NE–H is somewhat higher compared to upwind regions in the IGP (Range: 0.16–0.24). Theabundance of PAHs show large variability, ranging from 4–46 ng m–3, and the ratio of sum of 4– to 6–ring PAHs( (4– to 6–)PAHs) to EC is 2.4 mg g–1; similar to that in the upwind IGP and is about a factor of two higher than that fromthe fossil–fuel combustion sources. The cross–plot of PAH isomers [FLA/(FLA+PYR) vs. ANTH/(ANTH+PHEN),BaA/(BaA+CHRY+TRIPH), BaP/(BaP+B[b,j,k]FLA) and IcdP/(IcdP+BghiP)] reaffirms the dominant impact of biomassburning emissions. These results have implications to large temporal variability in aerosol radiative forcing andenvironmental change over the NE–Himalaya.

Keywords: Carbonaceous aerosol, PAH, biomass burning, air–mass transport, Northeast–Himalaya

Corresponding Author:Prashant Rajput

: +91 79 2631 4313: +91 79 2630 1502: prashant@prl.res.in

Article History:Received: 29 November 2012Revised: 11 February 2013Accepted: 17 March 2013

doi: 10.5094/APR.2013.022

1. Introduction

Carbonaceous aerosols, comprising of primary species(elemental carbon: EC and organic carbon: OC) and secondaryorganic compounds, contribute significantly to the total particulatematter in the lower atmosphere (Seinfeld and Pandis, 2006).Besides biomass burning emissions, the water–soluble organiccarbon (WSOC) has contributions from secondary organic aerosol(SOA) in the atmosphere, occurring via photochemical reactions ofvolatile organic compound (VOC) (Mayol–Bracero et al., 2002;Decesari et al., 2006; Kumagai et al., 2009). The significance ofthese water–soluble organic compounds has been well recognizedin influencing the number density of cloud condensation nuclei(CCN) and altering the radiation balance of the atmosphere(Rosenfeld et al., 2008; Kaiser et al., 2011). More recently, theatmospheric oxidation of particulate polycyclic aromatichydrocarbons (PAHs) with O3, NOX and OH radical has beensuggested to alter the aerosol surface characteristics (fromhydrophobic to hydrophilic), and thus, expected to enhance theirpotential to act as cloud condensation nuclei (Kaiser et al., 2011).Briefly, the carbonaceous aerosol composition change due toseveral factors including source variability, aerosol mixing, theirinteraction with other atmospheric constituents and SOAformation. This study, conducted from the NE–region, assesses thechemical characteristics of carbonaceous aerosols and highlightsthe utility of PAH isomer ratios to finger–printing its source region.

Earlier studies on the chemical composition of aerosols overthe Indo–Gangetic Plain (IGP) have suggested biomass burning

emissions as the dominant source of carbonaceous species duringthe wintertime (Rengarajan et al., 2007; Ram and Sarin, 2010; Ramet al., 2010; Rajput et al., 2011a; Ram et al., 2012a). Underfavorable meteorological conditions, during the winter months(January–March), long–range downwind transport of emissionproducts along the Himalayan range is a conspicuous feature (Ramet al., 2012b). The hot–spots of pollutants over the IGP have beenwell documented through MODIS (Moderate Resolution ImagingSpectroradiometer) imageries (Ramanathan et al., 2007a). Thus,downwind atmospheric transport of fine–mode aerosols from theIndo–Gangetic Plain can have profound impact on the atmosphericradiative forcing due to aerosols and regional environment(Ramanathan et al., 2001; Ramanathan et al., 2007b; Rajput et al.,2011a). In this manuscript, we report the first data set onatmospheric concentrations of particulate matter (PM2.5), EC, OC,WSOC and PAHs from a sampling site located at the foot–hills ofNE–Himalaya. The sampling site is suitably located to assess theatmospheric impact of long–range transport of carbonaceousaerosols from the IGP. For rest of the year (April–December), theatmosphere over NE–Himalaya is relatively clean due to widespread rains associated with the SW– and NE–monsoon.

2. Methodology

2.1. Sampling site description

The sampling site at Barapani (25.7 °N; 91.9 °E; 1 064 m amsl)in the foot–hills of NE–Himalaya (NE–H) is 50 km north–east ofthe Cherrapunji–Maysynram, one of the most heavy rainfall

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(>1 200 cm annually) regions in the world. The site is upwind of thenearest Shillong town ( 20 km) with respect to NW–winds prevailing during the study period (January–March). Therefore, influencefrom local sources is expected to be insignificant. The total annualrainfall in this region is 1 100 cm, spread over June–September(SW–monsoon) and October–December (NE–monsoon). In addition, pre–monsoon rain activity begins by early April. This facilitates the removal of ambient aerosols by wet–scavenging duringrest of the year from April–December. In this context, transport ofpollutants from the Indo–Gangetic Plain (IGP), during wintermonths (January–March), is a conspicuous feature over the NE–Himalayan region (Figure 1). In this respect, sampling site atBarapani is representative of the NE–region of India.

2.2. PM2.5 sampling

Ambient particulate matter (aerodynamic diameter 2.5 m,referred as PM2.5) samples (n=51) were collected during January–March in three campaigns; March 2009 (n=12), January 2010(n=19) and March 2010 (n=20). A high–volume sampler (flow rate:1.2 m3 min–1; Thermo Scientific) was set up at 10 m above groundlevel inside the premises of Space Applications Centre in Barapani(Shillong). In order to collect adequate aerosol mass on pre–combusted (at 450 °C for 6 h) tissuquartz filter (PALLFLEX™,2500QAT–UP, 20 cm x 25 cm), each sample was collected continuously for 18–20 h. After sample collection, filters were wrapped inAl–foils, sealed in zip–lock plastic bags and retrieved to thelaboratory for chemical analysis as per the standard protocoldescribed in our earlier publications (Rengarajan et al., 2007; Ramet al., 2010; Rajput et al., 2011a; Ram et al., 2012a).

2.3. Air–mass back trajectories

Seven–day air–mass back trajectories are computed at 12:00 h(local time) using NOAA–Air Resource Laboratory HYSPLIT–Model(GADS data set) at arrival heights of 100 m, 500 m and 1 000 m(above ground level; AGL) (Draxler and Rolph, 2003). Air–massback trajectories on a particular day at these heights point to thesame direction. For the sake of brevity, wind–regimes arriving atthe site are represented in Figure 1 for an intermediate height of500 m AGL for all the sampling days (n=51) during January–March.Furthermore, air–masses arriving at the sampling site (Figures 1a,1b, and 1c) are classified into two categories, air–masses from the

Indo–Gangetic Plain (referred to as TYPE–I) and from the north–east of the site (referred to as TYPE–II). The air–masses showdominant influence from the IGP (TYPE–I: 80%), with discerniblecontribution from north–east of the site (TYPE–II: 20%). These, air–masses transport aerosols from the IGP and north–east of the site;thus, increasing the atmospheric particulate load over NE–H ascompared to the rest of the year (April–December). Thus, underfavorable meteorological conditions and wind–regimes samplingsite is representative of the NE–region for the long–rangetransport of pollutants (mainly from the Indo–Gangetic Plain). Inthis context, our study presents the first data set on carbonaceousaerosols from the NE–region. The north–westerly winds ( 5 m s–1)were dominant during the sampling period. The daily temperaturevaried from 6–28 °C with relative humidity from 10–99%. Duringthe entire sampling period, wet precipitation event (<15 mm)occurred on 16 March 2010.

2.4. Analysis of elemental and organic carbon (EC, OC)

The mass concentration of PM2.5 was determinedgravimetrically after equilibrating the filters at relative humidity of37±3% and 24±2 °C for 8–10 hours. Subsequently, concentrationsof particulate OC and EC have been measured on carbon analyzer(Sunset Laboratory, USA) using NIOSH (National Institute forOccupational Safety and Health) thermal–optical transmittance(TOT) protocol (Birch and Cary, 1996). For details on analyticalprotocol reference is made to Rengarajan et al. (2007). Theinorganic carbonate carbon (CC) was determined by integrating thearea under carbonate peak, also ascertained after de–carbonation(in HCl fumes for 6–8 h) on separate filter aliquot (Rengarajan etal., 2007). The CC is a minor component in the samples collectedfrom NE–H, and contributes always less than 5% of total particulate carbon (OC+EC+CC).

2.5. Analysis of water–soluble organic carbon (WSOC)

Determination of WSOC include sonication of 1–2 punches(3.14 cm2 each) of sample with 30/40 mL Milli–Q water for30 minutes, followed by extract filtration using glass–syringe

through a glass–fiber filter (25 mm diameter) into a pre–cleanedamber colored glass vials, and subsequent analysis on a TOCanalyzer (Shimadzu model TOC 5000A) (Rengarajan et al., 2007;Ram and Sarin 2010; Ram et al., 2012a).

Figure 1. Air mass back trajectories (at 500 m above ground level) arriving at the sampling site (Barapani; 25.7 °N; 91.9 °E; 1 064 m asl) in the NE Himalaya(shown by a red square) during (a)March 2009, (b) January 2010 and (c)March 2010, indicate majority of air masses from the Indo Gangetic Plain (solidlines; referred as TYPE I) and relatively few trajectories from north east of the site (dashed lines; referred as TYPE II). Also shown are study locations in theIndo Gangetic Plain (Patiala, Hisar, Kanpur and Allahabad), Manora Peak (Central Himalaya) and Nepal Climate observatory Pyramid (NCO P; Higher

Himalaya). Data from these sites have been used for comparison in this study (from the NE H).

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2.6. Analysis of polycyclic aromatic hydrocarbons (PAHs)

The analytical protocol adopted for PAHs (MW=128–278 u,Table 1) determination include accelerated solvent extraction (ASE200, Dionex Corporation) with DCM, followed by evaporation usingan evaporator (Turbo Vap LV® II, USA), matrix purification on apre–cleaned silica solid–phase extraction cartridge (SPE:WAT020810, Waters Sep–Pak®, 3 cc/500 mg) and analysis on a gaschromatograph coupled to mass spectrometer (GC–MS; HP7890A/5975C, Agilent) equipped with a capillary column (AgilentHP–5MS: 30 m x 0.25 mm x 0.25 μm). Pyrene–D10 (MW=212 u)was used as an internal standard for the PAHs quantification inselected ion monitoring (SIM) mode (Rajput et al., 2011a; Rajput etal., 2011b).

2.7. Detection limit, analytical uncertainty and accuracy of thechemical analysis

The routine data quality was ascertained from the analysis offilter blanks (n=10); detection limit: 0.23 g m–3 for OC, 0.07 g m–3

for EC, 0.01 g m–3 for WSOC and <6 pg m–3 for an individual PAH.Duplicate analysis of samples (n=6–8 for each constituent) provideuncertainty of 3% for OC, 6% for EC, 8% for WSOC and <15% forindividual PAH. In addition, the mass recovery of an individual PAHwas monitored based on the analysis of a standard referencematerial (SRM 1649b, urban dust; n=7); analytical accuracy of themeasurements are similar to those reported earlier (Rajput et al.,2011a; Rajput et al., 2011b).

3. Results and Discussion

The average mass concentrations of PM2.5, EC, OC, WSOC andPAHs from NE–H (remote location) are summarized in Table 1. The

chemical data set from an upwind site at Patiala (30.2 °N, 76.3 °E,250 m amsl) (Rajput et al., 2011a), for the wintertime (December–March), has been used to represent carbonaceous species fromsource region in the IGP. In addition, published data oncarbonaceous species (during wintertime) from other sites [Hisar(29.2 °N; 75.7 °E; 219 m), Kanpur (26.5 °N, 80.3 °E, 142 m),Allahabad (25.4 °N, 81.9 °E, 123 m) in the IGP (Rengarajan et al.,2007; Ram and Sarin, 2010), Manora Peak (29.4 °N, 79.5 °E,1 950 m) from the Central Himalaya (Ram et al., 2010) and NepalClimate Observatory Pyramid (NCO–P; 27.95 °N, 86.82 °E, 5 079 m)from the Higher Himalaya (Decesari et al., 2010)] have also beenused for comparison.

3.1. Carbonaceous species associated with TYPE–I (from IGP) andTYPE–II (from north–east of the site) air–masses

The temporal variability in the atmospheric concentrations ofOC, EC and WSOC assessed in PM2.5 from foot–hills of NE–H isshown in Figure 2. The mass concentration of PM2.5 associated withTYPE–I air–masses varied from 39–211 μg m–3 (Figure 2a). Theconcentrations of OC, EC and WSOC also exhibit large variability(Figures 2b, c, d): 10.1–80.5 μg m–3; 2.6–11.0 μg m–3 and 7.0–51.6 μg m–3, respectively. The contributions of OC and EC to PM2.5in NE–H (TYPE–I; n=41) ranged from 9–48% (Av: 35±8%) and 2–14%(Av: 6±3%), respectively. The OC/EC ratio varied from 2–15(4.6±1.3; R2=0.24, p<0.01) and WSOC/OC from 0.50–0.97(0.63±0.02; R2=0.83, p<0.0001).

The mass concentration of PM2.5 over NE–H (for TYPE–II air–masses) varied from 62–348 μg m–3 (Figure 2a). The concentrationsof OC, EC and WSOC exhibit large variability (Figure 2): 14.8–137.7 μg m–3; 3.4–18.5 μg m–3 and 11.2–78.3 μg m–3, respectively.

Table 1. Average concentrations of OC, EC, WSOC and PAHs in PM2.5 from NE Himalaya and upwind Indo Gangetic Plain

AerosolsNE Himalaya

Upwind Sitea

(n=28)Air mass (TYPE I)(n=41)

Air mass (TYPE II)(n=10)

PM2.5 ( g m 3) 91±37 120±84 122±54

OC 33±17 45±35 29±12

EC 5.0±1.8 6.9±4.4 5.3±1.6

WSOC 22±9 29±19 17±7

PAHs (mg g 1 OC)Naphthalene (NAPH) 0.007±0.005 0.011±0.013 0.015±0.019

Acenaphthylene (ACY) 0.003±0.002 0.003±0.003 0.002±0.002

2 Bromonaphthalene (2 BrNAPH) 0.003±0.003 0.001±0.001 0.000±0.000

Acenaphthene (ACE) 0.001±0.001 0.001±0.002 0.001±0.001

Fluorene (FLU) 0.002±0.001 0.003±0.003 0.002±0.001

Phenanthrene (PHEN) 0.012±0.008 0.016±0.012 0.014±0.006

Anthracene (ANTH) 0.003±0.002 0.004±0.004 0.002±0.001

Fluoranthene (FLA) 0.028±0.022 0.045±0.038 0.029±0.011

Pyrene (PYR) 0.031±0.024 0.048±0.039 0.033±0.011

Benzo[a]anthracene (BaA) 0.020±0.010 0.025±0.015 0.019±0.011

Chrysene/Triphenylene (CHRY+TRIPH) 0.039±0.017 0.050±0.033 0.054±0.028

Benzo[b+j+k]fluoranthene (B[b,j,k]FLA) 0.128±0.052 0.155±0.092 0.201±0.097

Benzo[a]yrene (BaP) 0.055±0.028 0.063±0.035 0.074±0.033

Indeno[1,2,3 cd]pyrene (IcdP) 0.058±0.032 0.077±0.055 0.115±0.041

Dibenzo[a,h+a,c]anthracene (D[ah,ac]ANTH) 0.008±0.004 0.008±0.005 0.012±0.008

Benzo[ghi]perylene (BghiP) 0.053±0.027 0.069±0.048 0.110±0.039

PAHs 0.450±0.222 0.580±0.375 0.683±0.243a Data for the upwind Indo Gangetic Plain is adopted from Patiala (Rajput et al., 2011a). TYPE I: refersto air masses arriving at NE Himalaya (NE H) from the Indo Gangetic Plain and those from north eastof the site are referred to as TYPE II (reference is made to Figure 1 for further description).

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Figure 2. Temporal variability of (a) PM2.5 and the associated carbonaceous species: (b) organic carbon (OC); (c) elemental carbon (EC); (d)water soluble organic carbon (WSOC) and (e) sum of 16 PAHs ( PAHs),for the TYPE I and TYPE II air masses over the NE Himalaya (NE H).

The contributions of OC and EC to PM2.5 in NE–H (TYPE–II; n=10)ranged from 24–43% (Av: 36±7%) and 3–11% (Av: 6±2%), respectively. Thus, relatively high concentrations of PM2.5, OC and EC areassociated with TYPE–II air–mass. This is also reflected in relativelyhigh OC/EC ratio for TYPE–II air–mass, varying from 4–15 (6.9±1.5;R2=0.72, p<0.01), as compared to that with TYPE–I air–mass. TheWSOC/OC ratio varied from 0.50–0.93 (0.60±0.02; R2=0.93,p<0.0001) for TYPE–II air–mass.

Based on relatively high OC/EC ratio (compared to fossil–fuelsource), as high as high as 10–15 associated with WSOC/OC ratioexceeding 0.5, it can be inferred that dominant source of carbonaceous aerosols is attributable to biomass burning emissionsand/or contributions from secondary organic aerosols (SOA). HighWSOC/OC ratios (>0.6) have been earlier observed duringphotochemical haze in suburban and rural atmospheric environments and also for the dominant impact from biomass burningemissions (Decesari et al., 2006; Kumagai et al., 2009). Thisobservation is consistent with the recent studies assessing theorganic aerosols from biomass burning emissions and their long–range transport from source regions in the IGP (Rengarajan et al.,2007; Ram and Sarin, 2010; Ram et al., 2010; Rajput et al., 2011a).

3.2. Temporal variability of PAHs

PAHs are a suit of organic compounds, produced during theincomplete combustion of fossil–fuel vis–à–vis biomass burning.Owing to their utility as a tracer of its source it is essential todocument their atmospheric abundance record from differentenvironmental regions. In this context, the temporal variability inPM2.5–bound PAHs concentration (ng m–3) from NE–H is shown inFigure 2e. The PAHs concentration varied from 4.1–27.7 (AVG±SD:13.5±5.4) ng m–3 in the TYPE–I air–masses. Furthermore, the corresponding PAHs/EC ratio varied from 1.1–5.9 (2.9±1.1) mg g–1.

The PAHs concentration associated with the TYPE–II air–masses exhibit variability from 7.3–45.9 (16.5±11.1) ng m–3

(Figure 2e). Furthermore, the PAHs/EC ratio for TYPE–II air–masses varied from 1.5–4.6 (2.4±0.8) mg g–1. The average concentration (in mg g–1 OC) of an individual PAH associated with theTYPE–I and TYPE–II air–masses, along with the major constituents(EC, OC, WSOC in PM2.5), is given in Table 1. In view of the dominant transport from the IGP (Figure 1), the reported data on PAHsprofiles (mg g–1 OC) from Patiala (referred as the upwind IGP)(Rajput et al., 2011a), is also listed in Table 1. One of the noticeablefeatures of the data relates to the lower mass fraction of PAHs(mg g–1 of OC) over NE–H as compared to that in the upwind IGP(Table 1).

3.3. Statistical analysis of the data for TYPE–I and TYPE–II air–masses

A two–tailed t–test (at significance level of 5%) is performedwith the data set to assess the similarity/differences in the aerosolcharacteristics associated with TYPE–I and TYPE–II air–masses(Table 2). Furthermore, the results on statistical analysis forOC/PM2.5, OC/EC, WSOC/OC, (4– to 6–)PAHs/EC and PAH isomerratios are listed in Table 2. The OC/EC ratio (for TYPE–I: 4.6±1.3 andfor TYPE–II: 6.9±1.5) is statistically different (t=4.8; p<0.05) for theTYPE–I and TYPE–II air–masses (Table 2). Furthermore, the WSOC/OC ratio also exhibits statistical differences (for TYPE–I: 0.63±0.02and for TYPE–II: 0.60±0.02; t=4.2; p<0.05). However, the otherparameters i.e., OC/PM2.5, (4– to 6–)PAHs/EC and PAH isomer ratioslook statistically similar for the TYPE–I and TYPE–II air–masses overthe foot–hills of NE–H.

3.4. Relationship between (4– to 6–)PAHs and EC

The particulate (PM2.5) bound (4– to 6–)PAHs (sum of 4– to 6–ring PAHs) concentration (ng m–3) over NE–H varied from 4–27(AVG±SD: 13±5) ng m–3 and from 7–45 (15±11) ng m–3 for theTYPE–I and TYPE–II air–masses, respectively. The (4– to 6–)PAHs/ECratio (mg g–1) varied from 1.0–5.4 (2.44±0.36; R2=0.24, p<0.0001;Figure 3) for TYPE–I air–masses. A comparable (4– to 6–)PAHs/ECratio, varying from 1.4–4.3 (2.35±0.30) mg g–1 is noteworthy forTYPE–II air–masses. Furthermore, during the wintertime, the(4– to 6–)PAHs concentration varying from 2–47 (19±11) ng m–3 and(4– to 6–)PAHs/EC ratio varying from 1.2–9.3 (3.36±1.19; R2=0.23,p<0.0001) mg g–1 in PM2.5 has been reported for the dominance ofbiomass burning emissions from an upwind site (Patiala) in the IGP(Rajput et al., 2011a). The linear regression analysis among highmolecular weight (4– to 6–ring) PAHs and EC concentration overthe NE–H and the IGP (upwind at Patiala) yield R2 0.25. In contrast,high molecular weight PAHs and EC from fossil–fuel combustion(vehicular emissions) show significant correlation (R2=0.75), withPAHs/EC ratio of 1.2 (Arnott et al., 2005). Thus, specific biomass(post–harvest agricultural–waste and bio–fuels) burning emissionsin the IGP are associated with the characteristic higher abundancesof PAHs (normalized to EC) as compared to that from the fossil–fuel combustion sources. Furthermore, a study over the northernIndian Ocean during the Indian Ocean Experiment (INDOEX)campaign, attributed the dominant impact from fossil–fuelcombustion sources also reports a significant correlation (R2=0.42)(Crimmins et al., 2004). In contrast, a recent study from Atlanta(US) reporting dominant impact of regional biomass burningemission during wintertime, also provide a good correlation(R2=0.78) (Li et al., 2009). A significantly high correlation betweenPAHs and EC from fossil–fuel combustion sources and also fromthe biomass burning is reported in the literature (Crimmins et al.,2004; Arnott et al., 2005; Li et al., 2009). However, our studysuggests significantly lower correlation coefficient (R2=0.24) fromthe NE–H (similar to that in the IGP); and highlights thecharacteristic impact of different types of biomass (agricultural–waste and bio–fuels) burning emissions.

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Table 2. Statistical two tailed t test for the characteristic ratios in aerosols over the NE Himalaya (NE H) forthe TYPE I (from IGP) and TYPE II (from north east) air masses

ParametersNE H

t test Difference(TYPE I and TYPE II) P value

TYPE I (n=41)a TYPE II (n=10)a

OC/PM2.5 0.35±0.08 0.36±0.07 0.4 Not Significant >0.05

OC/EC b 4.6±1.3 6.9±1.5 4.8 Significant <0.05

WSOC/OC b 0.63±0.02 0.60±0.02 4.2 Significant <0.05

(4 to 6 )PAHs/EC (mg g 1) b 2.44±0.36 2.35±0.30 0.7 Not Significant >0.05

ANTH/(ANTH+PHEN) 0.21±0.12 0.20±0.05 0.3 Not Significant >0.05

FLA/(FLA+PYR) 0.48±0.01 0.47±0.01 1.8 Not Significant >0.05

BaA/(BaA+CHRY+TRIPH) 0.34±0.04 0.34±0.03 0.0 Not Significant >0.05

BaP/(BaP+B[b,j,k]FLA) 0.29±0.04 0.30±0.05 0.6 Not Significant >0.05

IcdP/(IcdP+BghiP) 0.52±0.02 0.52±0.03 0.0 Not Significant >0.05a Geometric mean and standard deviation of the data.b Ratio based on linear correlation analysis.

Figure 3. Scatter plot between (4 to 6 )PAHs and EC at NE H (TYPE I). Asimilar regression plot with (4 to 6 )PAHs/EC ratio of 3.36±1.19 mg g 1

(R2=0.23, p<0.0001) is adopted based on data from an upwind site(Patiala) located in the IGP (Rajput et al., 2011a).

3.5. PAH isomer ratios for finger–printing

The isomer ratios of PAHs with 3–, 4–, 5– and 6–ring, FLA/(FLA+PYR) versus (a) ANTH/(ANTH+PHEN), (b) BaA/(BaA+CHRY+TRIPH) referred to as BaA/228, (c) BaP/(BaP+B[b,j,k]FLA)referred to as BaP/252 and, (d) IcdP/(IcdP+BghiP) from the NE–Hhave been compared with the available literature–based datafrom an upwind site (Patiala) in the IGP (Figures 5a, 5b) (Rajputet al., 2011a). It is relevant to state that the data on PAHs forother locations in the IGP is not available in the literature.Furthermore, the literature based PAH isomer ratios for paddy–residue burning, vehicular (gasoline and diesel) emissions, coalcombustion and bio–fuels (Cowdung cake and eucalyptus)burning is also shown in Figure 4 (with reference to the data).Investigating the information from cross plots with multiple PAHisomer ratios, it appears that in NE–H they have dominantcontributions from biomass burning emissions that includepost–harvest agricultural–waste of paddy–residue (AG–waste)and bio–fuels. Furthermore, PAH isomer ratios overlap withthose from upwind IGP, suggesting that dominance of biomassburning emissions in the IGP have a profound impact in the NE–H during January–March.

3.6. Comparison of the data set with other studies

Figures 5a and 5b show the spatial variability during wintertime (December–March) in OC/EC ratio and OC/PM2.5 ratio from

the Indo–Gangetic Plain and over the foot–hills of NE–Himalaya(NE–H; this study). Furthermore, the scenario from high–altitudelocations in Himalaya (Central: Manora Peak and southern slope:Nepal Climate Observatory–Pyramid, NCO–P) has also beenpresented in Figures 5a and 5b. In view of the dominant transportfrom the IGP, it is considered relevant to discuss and compare theOC/EC and OC/PM2.5 ratios from NE–H with those reported from theIGP, and subsequently to assess and compare with high–altitudelocations in the Himalaya. The dominance of fine–mode aerosols(PM2.5) during wintertime in the IGP has been documented earlier(Jethva et al., 2005). Furthermore, a study from the IGP suggests forthe similar mass fraction of OC in PM2.5 and PM10(OC/PM2.5 OC/PM10), and attributes dominant impact from thebiomass burning emission (Ram and Sarin, 2011). Owing to theseobservations, for the comparison made herein for wintertime, wehave assumed that the mass concentration of chemical constituentsin PM10 is similar to that in PM2.5. The OC/PM2.5 and OC/EC ratios inNE–H, associated with TYPE–I air–masses (From IGP), are found tobe 0.35±0.08 and 4.6±1.3 (R2=0.24, p<0.0001), respectively(Figures 5a and 5b). The OC/PM2.5 and OC/EC ratios for an upwindlocation in the IGP at Patiala are 0.24±0.04 and 3.8±1.3 (R2=0.23,p<0.0001; for data set from December 2008 – March 2009),respectively (Rajput et al., 2011a). From another upwind location inthe IGP at Hisar, the OC/PM10 and OC/EC ratios of 0.17±0.03 and9.8±1.4 (R2=0.55; December 2004) have been reported, respectively(Rengarajan et al., 2007). Furthermore, a study from Central IGP hasreported OC/PM10 ratio of 0.19±0.05 and OC/EC ratio of 6.2±3.7 atKanpur (January–March, 2007) and OC/PM10 ratio of 0.16±0.06 andOC/EC ratio of 6.7 (R2=0.72) at Allahabad (December 2004) (Ramand Sarin, 2010). Thus, despite large spatial variability in OC/PM2.5and OC/EC ratios within the IGP, it is obvious from our study that ascompared to various locations in the IGP, the OC/PM2.5 ratio isrelatively high in the foot–hills of NE–H. However, the OC/EC ratio inNE–H lies within its variability reported from the IGP. One of themost plausible explanations for this is attributable to the fasterremoval/dry deposition of certain chemical constituents in PM ascompared to the OC, during the course of transport from IGP(<500 m amsl) to the NE–H (1 064 m amsl). So, the altitude effect isseen very clearly for the transport process in this study.

Furthermore, based on all data set (n=51), the OC/PM2.5 andOC/EC ratios in NE–H are found to be 0.36±0.08 and 5.9±0.9(R2=0.49, p<0.0001), respectively (Figures 5a and 5b). A studyassessing the atmospheric abundances and impact of carbonaceousspecies over the Central Himalaya from Manora Peak has reportedsignificantly lower mass fraction of OC in PM10 (0.12±0.08) duringwinter, but similar OC/EC ratio (6.0; R2=0.80, p<0.0001) (Ram et al.,2010). From a further high–altitude location in Higher Himalaya(Nepal Climate Observatory–Pyramid; Figures 5a and 5b), a studyhas documented the OC/PM10 and OC/EC average ratios of

Rajput et al. – Atmospheric Pollution Research (APR) 219

0.12±0.02 and 10.8±1.7, respectively during winter (Decesari etal., 2010). It would be relevant to state that the data sets onOC/EC ratio from IGP location, Central Himalaya and NE–H areconstrained from linear regression analysis, in contrast to the

available average ratio from Higher Himalaya (NCO–P). Thus,relatively high OC/EC average ratio from Higher Himalaya ascompared to the other locations (discussed above) could be due tohigh ratios in a few aerosol samples.

Figure 4. Cross plots of FLA/(FLA+PYR) versus: (a) ANTH/(ANTH+PHEN); (b) BaA/(BaA+CHRY+TRIPH) referred as BaA/228;(c) BaP/(BaP+B[b,j,k]FLA) referred as BaP/252 and; (d) IcdP/(IcdP+BghiP) indicate dominant impact of biomass burning

emissions over NE H from the IGP. Other data source for: Upwind IGP (Rajput et al., 2011a), Gasoline (Khillare et al., 2005a),Paddy residue referred as AG waste (Rajput et al., 2011a), Diesel (Khillare et al., 2005b), Eucalyptus as wood fuel (Schauer et

al., 2001), Cowdung cake (Sheesley et al., 2003), Coal (Kirton et al., 1991; Khalili et al., 1995; Li et al., 2010).

Rajput et al. – Atmospheric Pollution Research (APR) 220

Figure 5. Spatial variability in: (a) OC/EC and; (b) OC/PM2.5 ratio. Data for Patiala, Hisar, Kanpur, Allahabad,Manora Peak and Higher Himalaya (Nepal Climate Observatory Pyramid; NCO P) is adopted from literature(Rengarajan et al., 2007; Decesari et al., 2010; Ram and Sarin, 2010; Ram et al., 2010; Rajput et al., 2011a).

Star (*) over the sampling locations demarcate for PM10 data.

4. Summary and Implications

The atmospheric concentrations of PM2.5, EC, OC, WSOC andPAHs over NE–Himalaya are 97, 5.3, 35.4, 23.3 g m–3 and14.1 ng m–3, respectively. The total carbonaceous aerosols[TCA=2.0×WSOC+1.2×(OC WSOC)+EC] accounts for 68±12% ofPM2.5 (Decesari et al., 2010). Based on relatively high OC/EC ratio(compared to fossil–fuel source), as high as 10–15 associated withWSOC/OC ratio exceeding 0.5 and PAH isomer ratios, it can beinferred that dominant source of carbonaceous aerosols isattributable to biomass burning. The transport of carbonaceousspecies (EC, OC and PAHs) with a high content of WSOC hasimplications related to the direct radiative forcing and cloudcondensation nuclei (CCN) activity of organic aerosols. Our studyon the chemical composition of carbonaceous aerosols from foot–hills of NE–H re–emphasizes the importance of ground–basedmeasurements, information which is not achievable throughretrieval of satellite data for physical and optical properties ofaerosols.

Acknowledgments

This study was supported by the fund received from the ISRO–Geosphere Biosphere Programme office (Bangaluru, INDIA). Weare thankful to Dr. Timmy Francis (PRL) and Dr. Arup Borgohain(NE–SAC) for assistance in aerosol sampling.

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