IASTA-2010

H–O–1

Distribution of Trace Metals between Suspended and Free Fall Aerosol over Darjeeling

A. Adak, A. Chatterjee*, S. K. Ghosh, S. Raha and A. K. Singh

Bose Institute, Kolkata

(* Presently at National Atmospheric Research Laboratory, Gadanki, India – 517 112)

Introduction

Aparticular fraction of the particulate matter which is known to exert toxic effects is metals. Airborne particulate trace metals are considered to represent a health hazard since they can damage human lung tissues and cause cellular inflammation [Finlayson- Pitts and Pitts, 2000]. Heavy metals are present in the atmosphere in ever increasing levels as a result of anthropogenic and natural emissions [Suzuki, 2006]. In this study, we have discussed the seasonal variations of the trace element concentrations and deposition fluxes in suspended and free fall aerosol under different meteorological conditions over Darjeeling. The primary focus of this paper is to study the impact of micrometeorological parameters on the seasonal variations of concentrations and fluxes of suspended and free fall aerosol and fractionation of the trace metals between suspended and free fall aerosol with a feeddback from the estimated dry settling velocities of each of the metals.

Methodology

The free fall aerosol (FFA) and total suspended particulate (TSPM) samples were collected during the dry season from October’07 to June’08. The FFA sampling was divided into daytime and nighttime sampling. A total of 87 samples of TSPM and 48 samples of free fall aerosol samples were collected. All the samples were collected when there was no rain i.e. in dry periods only.

The use of surrogate surface is one approach that has been used to directly measure dry deposition or free fall aerosol. A greased, smooth surrogate surface was used to collect the dry deposited particles. The mylar strips were used as the substrates placed on deposition plate made of PVC. Apezion-L type grease was used for the impaction of particulates. The total suspended particulate matter (TSPM) was collected using a high-volume sampler of Envirotech Instrument Pvt. Ltd, India placed on a wooden platform at a height of 10 m from the ground level. Aerosol was collected using the standard glass fiber filter paper.

The strips were properly treated to extract the dry deposited particles which were then analysed for the trace elements using an Atomic Absorption Spectrophotometer

Results

During the entire dry season, the average TSPM concentration was found to be 72.14 ± 32.13 μg m-3 ranging between 37.5 μg m-3 and 112.5μg m-3. On the other hand, the daytime (Fd) and nighttime dry deposition flux (Fn) showed a marked seasonal variation

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during the entire dry season. The average value of Fd and Fn were found to be 275.8 ± 56 mg m-2 day-1 and 107.4 ± 64.5 mg m-2 day-1 respectively. Fig 1 shows the seasonal variations in TSPM concentrations and free fall aerosol fluxes. There was a gradual and steady increase in TSPM concentration from postmonsoon through winter and reached maxima during summer and then decreased during premonsoon season. The Fd showed a similar variation to TSPM showing minima during postmonsoon and premonsoon with a maxima in summer. The aerosol concentration was found to be strongly influenced by the meteorological conditions. The lowering of PBL height during winter resulted the higher accumulation of aerosol whereas the higher wind speed during summer favored the dispersion of aerosols resulting lower concentrations and fluxes.

Figure 1. Aerosol fluxes and concentrations during dry season’07-08

Fe, Al and Zn showed a clear seasonal variability both in suspended and free fall aerosol. The day-time deposition flux was found to be maximum for Al and minimum for Cd while the night-time deposition flux was found to be maximum for Fe and minimum for Cu. On an average, trace elements were found to be accumulated in free fall aerosol by 13 % during daytime and 6.7 % during the nighttime over the entire study period. The average trace element contribution in TSPM was 6.24 %. Cr, Mn and Fe in TSP and Mn, Fe in free fall aerosol represent the group “Non Enriched Elements” (NEE) with enrichment ratio <100 whereas the rest of the elements with higher enrichment ratio (>100) represent the group “Anomalously Enriched Elements” (AEE).

Fractionation factor (FF), was used as the measure of the fractionation of the elements between suspended and free fall aerosol and determined as:

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Figure 2. Fractionation of trace elements between suspended and free fall aerosol

Fig 2 shows the variations of FF with deposition velocities of the elements. Cr, Mn, Zn and Cd are strongly fractionated between TSPM and free fall aerosol and are mainly enriched in TSPM with higher FF and lower deposition velocities. On the other hand, Cu, Ni, Pb and Fe were found to be enriched in free fall aerosol with lower fractionation factor and higher deposition velocities.

References

Finlayson-Pitts, B.J. and Pitts Jr., J.N., (2000), Chemistry of the Upper and Lower Atmosphere: Theory, Experiments, and Applications, first ed. Academic Press, San Diego.

Suzuki, K., (2006), Characterization of airborne particulates and associated trace metals deposited on tree bark by ICP-OES, ICP-MS, SEM-EDX and laser ablation ICP-MS, Atmos Environ., 40, 2626–2634.

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H–O–2

A Study on Aerosol Precipitation Chemistry during SW Monsoon

A. Chatterjee and A. Jayaraman

National Atmospheric Research Laboratory, Gadanki, India

Introduction

Atmospheric aerosols significantly influence the regional and global climate (IPCC, 2007) as well as adversely affect the human health. Also, when aerosols are removed from the atmosphere via wet and dry deposition, they can adversely affect the terrestrial and aquatic environments, ranging from acidification of soils and inland waters to the damage of buildings and monuments (Galloway et al. 2004). Precipitation chemistry is an intricate result of a complex interaction between cloud dynamics and microphysical processes as well as a series of in-cloud and below-cloud atmospheric chemical reactions. Studies on precipitation chemistry on regional scales help us to assess the natural and anthropogenic influence on the atmospheric composition, understanding various physico- chemical processes related to atmospheric transport and deposition of pollutants (IGAC 2003), provides information on the exchange of chemical components of aerosol between the atmosphere and the land/ocean and in understanding various biogeochemical cycles of important chemical elements.

In the present study, wet precipitation samples were collected over Gadanki (13.45 N latitude; 79.18 E longitude), a rural region in southern peninsular India. The samples were collected during south-west (July-Sep) and north-east (Oct-Dec) monsoon 2009. Temporal variation in ionic species was also studied within the rain events. The primary focus of this study is to identify the natural and anthropogenic influence on aerosol chemical composition and to estimate the relative contributions from “below the cloud” and “within the cloud” to the total deposition of aerosol ionic species.

Experiment

Rainwater samples were collected using a polythene funnel of 20 cm diameter fitted onto a two litre capacity polythene bottle. The collection gadgets were placed at ~10 m above ground level. Collected samples were stored in polythene bottles after adding Thymol (~5 mg) for preventing any biological degradation. All samples were refrigerated at 40C in the laboratory till the analyses were over.

Dry deposited aerosol (free fall aerosol) samples were also collected during the dry phase occur in between the rain events exposing the same funnels to the air. The funnels were exposed for more than 24 hrs for sufficient collection of dry deposited aerosol required for the detection of various components. The aerosols deposited on the funnels were extracted using a known volume of triple distilled water. The extracts were treated same as the rainwater samples prior to the analysis.

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The concentrations of major water soluble ions; Na+, NH4+, Ca2+, Mg2+, NO3- and SO42- in rainwater samples were determined by ion chromatograph (Metrohm 861 Advance Compact IC) using separator columns (Metrosep C2 250 and Metrosep A Supp 5) and guard column (Metrosep C2 Guard and Metrosep A Supp4/5 S Guard) for cation and anion analyses respectively. The effluents were a mixture of 1.8 mmol L-1 Na2CO3 and 1.7 mmol L-1 NaHCO3 for anion and a mixture of 0.75 mmol L-1 pyridine dicarboxylic acid and 4 mmol L-1 L (+) tartaric acid for cation analysis and were passed at a flow rate of 1 ml min-1.

Results and discussion

The average concentrations of ionic species in rainwater and their abundances are shown in Fig 1. The alkaline species were found to dominate over Gadanki. A significant correlation in rainwater is observed between non-sea-Ca2+ and non-sea-Mg2+ (R2 = 0.94) and between non-sea-Ca2+ and HCO3- (R2= 0.81). This indicates that calcium and magnesium over Gadanki are enriched as soil dust in the form of CaCO3 and/or CaCO3.MgCO3.

Figure 1. Average concentrations of ionic species in rain water collected over Gadanki during July-Dec’09

Significant correlations of non-sea-calcium with NO3- and non-sea-SO42- indicate that a part of nitrate and sulphate are also associated with the soil dust aerosol over the region. The enrichment of nitrate and sulphate in soil dust is due to the uptake of mineral acids (HNO3 or H2SO4) on the surface of soil dust. NH4+ shows strong correlations with NO3- and non-sea-SO42- in rainwater samples indicating their common anthropogenic source like agricultural activities, animal manure, human activities etc. The poor correlations of ammonium with nitrate and non-sea-sulphate in dry deposited aerosol samples indicate the existence of ammonia as fine mode particulates and/or gas phase. Na+ and Cl- showed strong correlation with each other indicating their common marine source.

Ca2+, Mg2+, Na+, K+, Cl-, NO3- show a sharp fall in their concentrations at the earlier stage of the precipitation whereas NH4+ and non-sea-SO42- show significant concentrations

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even at the later stage of the precipitation. A strong indication is found towards the in cloud scavenging of ammonium and non-sea-sulphate.

The atmospheric removals of Ca2+, Mg2+ and SO42- through wet deposition are found to be maximum at rain rate of ~ 2 mm hr-1 whereas the removal of NH4+, NO3- and SO42- is found to increase with the increase in rain rate.

Figure 2. Removal rate of ionic species through wet and dry depositions over Gadanki

Fig 2 shows the average removal rate of ionic species through dry and wet depositions. It is observed that removal of NH4+, K+, NO3- and SO42- from the atmosphere through wet deposition is several times higher than dry deposition.

Conclusions

The major findings of the study are summarized as follows:

1.The collected rainwater at Gadanki was found to be alkaline in nature.

2.In-cloud scavenging of ammonium and sulphate were observed over Gadanki.

3.The atmospheric removal of ammonium, nitrate and sulphate were found to increase with increase in rain rate whereas a moderate rain rate (~2 mm hr-1) favored the removal of sodium, calcium and magnesium.

5.On an average the removal of ammonium and potassium through wet deposition were found to be several times higher than those through dry deposition.

References

Galloway, J.N., Dentener, F.J., Capone, D.G., Boyer, E.W., Howarth, R.W., Seitzinger, S.P., Asner, G.P.,Cleveland, C., Green, P., Holland, E., Karl, D.M., Michaels, A.F., Porter, J.H., Townsend, A.,Vorosmarty, C.: Nitrogen cycles: Past, present and future. Biogeochemistry 70, 153–226, 2004.

IGACtivities Newsletter no. 27, DEBITS special issue, 2003.

IPCC: Intergovernmental Panel on Climae Change, Third Assessment Report. Cambridge University Press,Cambridge, 2007.

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H–O–3

Observations of Enhanced Aerosol Absorption over an Urban Coastal Zone

A. Saha1,2, M. Mallet3, S. Despiau2 and J. Piazzola2

1CARTEL, Université de Sherbrooke, Sherbrooke, Canada

2LSEET-LEPI, Université du Sud Toulon-Var, La Garde,France

3Laboratoire d’Aerologie, Université Paul Sabatier,Toulouse,France

Spectral dependence of aerosol light absorption and PM10 mass concentrations were measured at the surface over an urban coastal (Mediterranean) region of south France for one complete seasonal cycle during 2005-2006. Average monthly BC concentrations varied between 0.3 and 1.0 g m-3 [Saha and Despiau, 2009], and this contributed ~1.5 - 4.6% to the PM10 mass (Fig. 1). It can be seen from Fig.1 that the BC concentration and its fraction to PM10 showed strong seasonal variations, with higher values in winter (November through February) and lower values during rest of the year (March to October). The high BC concentration in winter was attributed to meteorology and boundary layer dynamics.

Figure 1. Annual variations of BC mass concentration and its mass fraction

Angstrom absorption exponent (AAE) estimated from the absorption coefficient spectra (in the wavelength range 370 - 950 nm) was found to vary between ~1.1 and ~1.4 respectively during the entire study period and also showed strong seasonal dependence. AAE is ~1 for pure BC particles emitted from fossil fuels (coal, petroleum, natural gas). Values of AAE > 1 indicates contribution of absorbing particles from non-fossil fuel sources (such as biomass burning, mineral dust). Our results show very high excess absorption at shorter wavelengths during winter (~33% at 370 nm in December) and negligible excess absorption during summer months (Fig.2).

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Since carbon monoxide (CO) is an excellent tracer of biomass burning (which emits lots of organic carbon in addition to BC), we have examined the regional distribution of surface CO mixing ratio (not shown here) over Europe derived from Measurements Of Pollution In The Troposphere (MOPITT) instrument onboard NASA’s Terra satellite. The

Figure 2. Annual variation of excess absorption at 370 nm

seasonal maps indicates high CO concentration (>200 ppbv) in winter and lower concentrations (~100 ppbv) during summer. Furthermore, it is to be noted that there were no major impacts of mineral dust transport (local and long-range) at the study region during winter months [Saha et al., 2008]. Dust intrusion at this Mediterranean site generally occurs in summer months as reported by Saha et al. [2008]. In the absence of mineral dust sources in winter, we attribute the enhanced excess absorption due to biomass burning (as evidenced by high CO concentrations during winter), as well due to local particulate emissions due to residential wood burning for domestic heating in winter [Faveza et al., 2009]. The presence of highly absorbing aerosols in the lower atmosphere during winter could possibly cause a positive climate forcing and a local warming of the boundary layer in the region.

Acknowledgements

The present work is supported by French CNRS, INSU, and PNTS Projects. Major part of the work was done when one of the authors (AS) was on research fellowship at the Université du Sud Toulon-Var (USTV). AS would like to acknowledge the French Ministry for Education & Research and USTV for the financial support.

References

Faveza, O., H. Cachier, J. Sciarea, R. Sarda-Estèvea and L. Martinonb, Evidence for a significant contribution of wood burning aerosols to PM2.5 during the winter season in Paris, France, Atmos. Environ., 43, 22- 23, 2009.

Saha, A., and S. Despiau, Seasonal and diurnal variations of black carbon aerosols over a Mediterranean coastal zone, Atmos. Res., 92, 27-41, 2009.

Saha, A., M. Mallet, J.C. Roger, P. Dubuisson, J. Piazzola and S. Despiau, One year measurements of aerosol optical properties over an urban coastal site: Effect on local direct radiative forcing, Atmos. Res., 90, 195-202, 2008.

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H–O–4

Transport of Aerosols and Trace Gases over Bay of Bengal During Pre-monsoon and Winter

Girach Imran Asatar, Susan George K1, Liji Mary David and Prabha R Nair

Space Physics Laboratory

Vikram Sarabhai Space Centre,Trivandrum 695 022, India

1 National Physical Laboratory,NewDelhi 110012

Introduction

The aerosols and trace gases, two highly variable species in the atmosphere play vital roles in the radiative forcing and cloud formation. All the atmospheric effects of these constituents depend on the concentration level of the individual species as well as their physical and chemical nature. By scattering the incoming solar radiation, the accumulation mode sulfate contribute to negative radiative forcing resulting in atmospheric cooling, where as black carbon contribute to positive radiative forcing by absorbing the radiation. In addition, aerosols and trace gases can produce serious environmental/health impacts when their concentration levels exceed limits. Aerosols are produced from a variety of natural or anthropogenic sources [Seinfeld and Pandis (1998)]. Oceans are the single largest source of natural aerosols. Through the mechanism of bubble bursting at the surface of the ocean, large amounts of sea-salt aerosols are injected into the atmosphere [Blanchard and Woodcock, 1980; Fairall et al., 1983; Exton et al. 1985]. Another source of aerosols over the ocean is the marine biogenic activity. In addition, oceans are also weak source of trace gases like carbon monoxide, methane, etc [Swinnerton et al., 1970; Bates et al., 1996]. Besides these natural sources, large amount of aerosols and trace gases are transported over the oceanic environment from nearby/far-off landmass depending on the prevailing circulation system. The Integrated Campaign for Aerosols, gases and Radiation Budget (ICARB) conducted under the Geosphere Biosphere Programme of Indian Space Research Organisation (ISRO-GBP) focused on the mapping of aerosols and trace gases over the Indian landmass and adjoining oceanic region. As part of ICARB, cruise-based measurements of aerosols and trace gases have been carried out over Bay of Bengal (BoB) during pre-monsoon months of March-April 2006 and winter months of December 2008 to January 2009.

Cruise tracks, Meteorological conditions and Experiments

The Figure 1a and b show the track of pre-monsoon cruise (named as ICARB_2006) SK 223A and winter cruise (named as W_ICARB) SK 254 of ORV Sagar Kanya respectively. Both the cruises started from Chennai and ended at Cochin. ICARB_2006 and W_ICARB campaign were conducted from 18 March to 13 April 2006 and from 27 December 2008 to 30 January 2009 respectively. Earlier campaigns over BoB like Indian Ocean Experiment (INDOEX), Bay of Bengal Experiment (BOBEX), Bay of Bengal Processes Studies (BOBPS),

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etc have limited spatial and temporal resolution whereas W_ICARB brought out the winter pattern with wider coverage both in space and time. The cruise W_ICARB covered the eastern BoB which was unexplored during earlier cruises. During pre-monsoon cruise (ICARB_2006), winds were strong and westerly/north-westerly over the northern- BoB as compared to those over southern-BoB. During W_ICARB (winter), winds were weak and northerlies over northern-BoB whereas winds were strong and north-easterlies over southern-BoB. Temperature found to be lower over northern-BoB as compared to southern- BoB during both the cruises.

During ICARB_2006 , aerosol samples were collected using a single stage high volume sampler (Model GH2000 of Thermo, USA) and near-surface ozone measurements by using a UV photometric O3 analyzer (Model 49C of Thermoelectron Corporation, USA and O3 42 of Environnement S.A, France). During W_ICARB, in addition to these measurements, near-surface NOx and CO were also measured using a chemiluminescence NOx analyzer and a gas filter correlation CO analyzer respectively. The aerosol samples collected from this marine environment are subjected to gravimetric analysis to obtain the mass loading (in g m-3) and chemical analysis to quantify the various chemical species viz Na, NH4, K, Mg, Ca, F, Cl, NO2, Br, NO3, SO4, Cu, Zn, Pb, etc. Ion-chromatography has been used for quantifying the anions and the water soluble cations. For metallic species, AAS and ICP-MS are used. This paper presents the observed spatial pattern of aerosol mass loading over BoB along with that of ozone and its precursor gases. The spatial inhomogeneity in mass loading and concentration of trace gases could be explained by meteorological conditions and back-trajectory analysis.

Figure 1. Cruise tracks of ICARB (a) pre-monsoon cruise and (b) winter cruise

Results and Discussions

Figure 2 shows the spatial variation in aerosols mass loadings during the two cruises. It can be seen that mass loading is significantly high over head-BoB compared to that over southern BoB irrespective of seasons. Also mass loading showed substantial increase during winter. Lowest loading was observed over mid-BoB. Similar features are observed for near-surface ozone also. The spatial inhomogeneity is explained by analyzing the airmass back-trajectories reaching the measurement location and the synoptic wind pattern. The back trajectories reaching head BoB originated from the northern/north-eastern land mass. The highest mass loading/mixing ratios were measured over head-BoB during

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winter when the synoptic wind was northeasterly favoring strong outflow of continental airmass over to BoB. Chemical nature of aerosols in this region also showed signature of continental influence. Anthropogenic species like SO4, NO3 etc and crustal species like Al, Fe etc were found to be abundant in this region. During winter cruise, aerosol mass

Figure 2. Mass loading over BoB during pre-monsoon and winter ICARB

loading near-surface ozone and CO showed a hot spot region over the southeast-BoB. Near-surface NO2 mixing ratios are found to be high and comparable over head-BoB and eastern-BoB. On the other hand, during winter period highest near-surface CO mixing ratios are observed over southeast-BoB with the lowest values in southern BoB. The back trajectory analysis using HYSPLIT (Hybrid Single particle Lagrangian Integrated Trajectory) model shows the transport of trace gases from south-eastern region of Asia. Different pathways for the transport of aerosols and trace gases were identified.

References

Bates, T. S., K. C. Kelly, J. E. Johnson, and R. H. Gammon (1996), A reevaluation of the open ocean source of methane to the atmosphere, J. Geophys. Res., 101(D3), 6953–6961.

Blanchard D. C. and Woodcock A. H. (1980), The production, concentration, and vertical distribution of the sea-salt aerosols, Ann. N. Y. Acad. Sci., 338, 330-347.

Exton, H. J., Latham J., Park P. M., Perry S.G., Smith M. H. and Allan R. R. (1985), The production and dispersal of marine aerosol; Q. J. R. Meteorol. Soc., 111, 817-837.

Fairall, C. W., Davidson K. L. and Schacher G. E. (1983), An analysis of the surface production of sea-salt aerosols, Tellus 35B, 31-39.

Seinfeld, J. H. and S. N. Pandis (1998), Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, John Wiley and Sons, New York, 1326p.

Swinnerton J. W., Linnenbom V. J. and LaMontagne R. A. (1970), The ocean: a natural source of carbon monoxide, Science 167, 984–986. doi:10.1126/science.167.3920.984.

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H–O–5

Qualitative Source Apportionment of PAHs in PM10 of Mumbai City Using Diagnostic Ratios

Mihir Herlekar # *, Abba Elizabeth #, Rakesh Kumar #

and Indrani Gupta#

# NEERI, 89/B, Dr. A.B. Road, Mumbai – 400018.

* Email address: - mihirherlekar@yahoo.com

Introduction

During the past decades, organic aerosols, which form major fraction (20-50%) of fine particle mass in polluted urban areas have received high attention. It has many adverse health impacts. Particle deposition has been the major transfer pathway for these compounds [1]. One method that has been used to apportion ambient particulate matter to respective sources is use of organic molecular markers [2]. Compounds associated with specific source classes are commonly referred to as molecular markers [3]. Among hundreds of individual organic compounds detected in particulate matter, nonpolar organic compounds like Polynuclear aromatic hydrocarbons (PAHs) are of major concern due to adverse impacts like carcinogenicity and mutagenicity [4]. The common sources of PAHs in urban atmosphere are automobiles, re- suspended soils, refineries and power plants. In India, cooking fuel combustion is also a likely source of PAHs [5]. One of the uncertainties in ascertaining sources of PAH has been the major impediment in controlling sources. Diagnostic ratios and PCA are the most widely used techniques to identify and characterize the emission sources [6]. Beginning with the work of Daisey et al. in 1979, numerous studies have used diagnostic ratios of PAH concentrations to infer sources of airborne particulate PAH content [7]. This is based on the assumption that different sources release PAH in characteristic proportions, which remain unaffected by partitioning between vapour and particle phase and hence these ratios can be used to predict PAH origin/sources [8]. In this paper, an attempt was made to identify sources of PAHs in ambient atmosphere of Mumbai by using Diagnostic ratios.

Methodology

Study site : Ambient air monitoring was carried out at 7 different sites in Mumbai. These sites represented control, commercial, industrial, kerb and residential areas. Colaba was a control site, Dadar was commercial site and Mahul was industrial site. Andheri and Mulund were kerb sites; Khar was residential site of upper income group whereas Dharavi was a slum residential site.

Sampling and Analysis: Samples for molecular marker analysis were collected on pre fired (9000 C for 3 hours) Tissue Quartz filter paper (PALL Life Science, 47 mm, pore size 1 ) using Partisol® Model 2300 Speciation Sampler. The duration for sampling was 24

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hours for 30 days in each season at all the sites. The flow rate was maintained at 16.7 l/ minute. Samples were stored at -200 C to prevent loss due to volatilization. The composite samples for each season were then analyzed for non polar particulate organic compounds at Desert Research Institute (DRI), Nevada, USA by DRI’s In-Injection Port Thermal Desorption Method followed by Gas Chromatography/Mass Spectrometry. For QA/QC, replicates at a rate of one every ten samples was performed to ensure good instrument reproducibility. Also, certified standard solutions were used to check the calibration created using a six-point calibration curve from mixed standards.

Results and Discussion

The highest concentration of particulate phase PAHs was observed at Dharavi (426.989 ng/m3) in winter season whereas the lowest concentration was at Khar (30.308 ng/m3) in summer season. Diagnostic ratios were calculated only for those PAHs which always exist in particle phase (PAHs with 4 or more rings) and also named in ATSDR/US EPA’s list of priority pollutants viz. Indeno(1,2,3-c,d-pyrene) [IND], Benzo(ghi)perylene [BghiP], Benzo(a)pyrene [BaP], Chrysene [CHR], Benzo(b)fluoranthene [BbF], Benzo(k)fluoranthene [BkF], Benzo(a)anthracene [BaA], Benzo(e)pyrene [BeP]. Site wise variations of averages for 3 season’s diagnostic ratios for all sites are shown in Figure 1.

Figure 1. Site Wise Variation of Diagnostic Ratio of Different PAHs

Conclusion

Concentrations of particulate phase PAHs were estimated at sites which were representative of different land use patterns in Greater Mumbai. The average values of different diagnostic ratios indicate that vehicular exhaust; both from gasoline and diesel vehicles, wood combustion and coal combustion are the predominant sources of ambient concentrations of PAHs. Some other sources which are indicated to be the contributing factors are typically site specific viz. at Dharavi, smelting is seen as one of the sources. Khar, an upper income residential site has vehicles and domestic soot as the sources.

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Table 1. Sources Identified at Different Sites

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Table 1 (Contd..)

Mahul has ratios indicating petroleum refining and thereby justifies its selection as an industrial site. Kerb site like Andheri shows highest value for the ratio which is used as a tracer for contribution from road dust. The source identification corroborates with earlier work related to PAH source apportionment in Mumbai. Also, it was found that the sources match with site wise emission inventory. In order to make more confirmatory source apportionment and to devise appropriate control strategies to minimize the adverse impacts of organic compounds of organic compounds like PAHs, quantitative source identification should be carried out.

Acknowledgement

The Authors are thankful to the staff of Desert Research Institute, Nevada, USA, and are grateful to NEERI Staff for their support.

References

1.Bi, X., Sheng, G., Peng, P., Chen, Y. and Fu, G., 2005. Atmospheric Environment, 39, 477-487

2.Fraser, M.P., Yue, Z.W., Tropp, R.J., Kohl, S.D. and Chow, J.C., 2002. Atmospheric Environment, 36, 5751- 5758

3.Shrivastava, M.K., Subramanian, R., Rogge, W.F. and Robinson, A.L., 2007. Atmospheric Environment, 41, 9353-9369

4.Yue, Z.W. and Fraser, M.P., 2004. Aerosol Science and Technology, 38:12, 60-67

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5.Kulkarni, P. and Venkataraman, C., 2000. Atmospheric Environment, 34, 2785-2790

6.Khaiwal, R., Bencs, L., Wauters, E., Hoog, J., Deutsch, F., Roekens, E., Bleux, N., Berghmans, P. and Grieken, R.V., 2006. Atmospheric Environment, 40, 771-785

7.Galarneau, E., 2008. Atmospheric Environment, 42, 8139–8149

8.Allen, A.G., Rocha, G.O., Cardoso, A.A., Paterlini, W.C., Machado, C.M.D. and Andrade, J.B., 2008.

Transportation Research, Part D, 483–490

9.Manoli, E., Kouras, A. and Samara, C., 2004. Chemosphere, 56, 867–878

10.Mantis, J., Chaloulakou, A. and Samara, C., 2005. Chemosphere, 59, 593–604

11.Han, B., Bai, Z., Guo, G., Wang, F., Li, F., Liu, Q., Ji, Y., Li, X. and Hu, Y., 2009. Journal of Hazardous Materials, 170, 934–940

12.Khaiwal, R., Sokhi, R. and Grieken, R.V., 2008. Atmospheric Environment, 42, 2895-2921

13.Bourotte, C., Forti, M.C., Taniguchi, S., Bícego, M.C. and Lotufo, P.A., 2005. Atmospheric Environment, 39, 3799–3811

14.Saarnio, K., Sillanpää, M., Hillamo, R., Sandell, E., Pennanen, A.S. and Salonen, R.O., 2008. Atmospheric Environment, 42, 9087–9097

15.Sienra, M.R., Rosazza, N.G. and Préndez, M., 2005. Atmospheric Research Volume 75, Issue 4, 267-281

16.Gaga, E.O., 2004. Thesis submitted to The Graduate School of Natural and Applied Sciences of the Middle East Technical University

17.Guo, Z., Lin, T., Zhang, G., Hu, L. and Zheng, M., 2009. Journal of Hazardous Materials, 170, 888–894

18.Liu, M., Cheng, S.B., Ou, D.N., Hou, L.J., Gao, L., Wang, L.L., Xie, Y.S., Yang, Y. and Xu, S.Y., 2007.

Atmospheric Environment, 41, 8785–8795

19.Kavouras, I.G., Lawrence, J., Koutrakis, P., Stephanou, E.G. and Oyola, P., 1999. Atmospheric Environment, 33, 4977-4986

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H–O–6

Size Distribution and Chemical Composition of Aerosols at the Coastal Environment of Trivandrum (8.55ºN, 77ºE)

Prabha R Nair and Susan George K1

Space Physics Laboratory

Vikram Sarabhai Space Centre,Trivandrum 695 022, India

1 National Physical Laboratory,NewDelhi 110012

Introduction

The atmospheric aerosol system is a mixture of organic and inorganic particles with their sizes lying in the range 10-3 to 102 m. They include sea salt, soil dust, sulphates nitrates, fly ash, carbonaceous particles, biogenic particles, etc. Even though aerosols contribute only parts per billion mass of the atmospheric mass, they play very crucial roles in the geosphere-biosphere system. Most of the studies on atmospheric aerosols focus on two aspects viz., radiative/climatic impacts and the environmental/health impacts. All these effects depend on the physical as well as chemical nature of aerosols. In the present scenario, the largest uncertainties in global climate predictions arise due to the inadequate representation of aerosol characteristics [IPCC, 2007] in radiative transfer models. To understand the climate perturbations, the radiative effects must be accurately quantified and attributed to chemical components and ultimately to sources. Since atmospheric aerosols originate from a variety of natural and anthropogenic sources, they exhibit large variability on both spatial and temporal scales which demands their characterization on regional scales. This paper presents the observational results of the studies on the Number density and bulk chemical composition of aerosols at the tropical coastal environment of Trivandrum (8.55ºN; 77ºE).

Experimental site and meteorological conditions

The observation site Trivandrum (8.55°N, 77°E, 3m asl) is located at the southern end of the west coast of India. The site is characterized by a fairly flat and sandy terrain, devoid of any large scale industrial activity. It is ~500 m away from the coast line of Arabian Sea and ~10 km north-west of Trivandrum city. The terrain is fairly flat and sandy, devoid of any large-scale industrial activity. The major synoptic meteorological phenomenon at this site is the Asiatic monsoon which sets in June and extends till November. During June to August/ September, the synoptic wind is south westerly/ westerly (from ocean to land). By October, the wind direction changes to north easterly (from inland) and continues till February. The months December, January, and February are marked as the winter period, March to May as premonsoon/summer season. Being a coastal location the prominent mesoscale phenomena is the sea breeze and land breeze activities. Sea breeze sets in between 0900-1100 IST and lasts till 1900-2100 IST around which onset of Land breeze occurs.

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Instrumentation and Data

An Aerosol Spectrometer (model 1.108 of GRIMM Germany) is used for the continuous measurement of number density of near surface aerosols. It perates in 15 size channels with aerodynamic cut-off diameters 0.3, 0.4, 0.5, 0.65, 0.8, 1, 1.6, 2, 3, 4, 5, 7.5, 10, 15 and 20 μm to provide size-segregated number density in real time with a fine temporal resolution of 5 minutes (http:/www.grimm-aerosol.com). Measurement of aerosol mass loading is carried out by using a single-stage High Volume Sampler (Model GH2000 of Graseby Anderson, USA). The instrument essentially collects aerosols on preconditioned quartz fibre substrates. The sample-laden substrates are later subjected to gravimetric analysis for the estimation of aerosol mass loading (in g m-3) and chemical analysis for identifying and quantifying various chemical species. Ion Chromatography was used to quantify the concentration of different anions like, SO42-, NO3-, Cl-, PO43-, F-, Br- and the cation NH4+. Atomic Absorption Spectroscopy was used for estimating the concentration of cations Na+ and K+ and Inductively Coupled Plasma-Atomic Emission Spectroscopy for quantifying the concentration of other cations like, Fe3+, Ca2+, Mg2+, Al3+, Cu2+, Zn2+, Pb2+, and Mn2+. In addition to this, an automatic weather station located at the experimental site measures the meteorological parameters viz. temperature, RH, wind speed and direction.

Results and Discussions

Diurnal variation of aerosol Number density

Near surface aerosol number density shows day-to-day variation, in general, lying in the range 104 to 109 with lower values encountered during daytime. These diurnal changes are found to be closely linked with the changes in atmospheric boundary layer height (BLH) and mesoscale circulations like sea breeze (SB) and land breeze (LB).

The daytime drop in the number density is seen to be associated with the decrease in BLH and onset of SB and the evening /nighttime increase with increase in BLH and onset of LB. However, the diurnal variation is size-dependent with smaller particles showing low values during daytime and high values during night and early morning. For larger particles, diurnal variation is either less pronounced or characterized by noontime increase.

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period with low values during winter. This is similar to the seasonal pattern of large particles (Fig. 3b). On the other hand, the mass concentrations of SO42-, NH4+ and PO43- show a minimum during monsoon and maximum during winter, a pattern similar to that of small particles. Species Al, Fe Ti, etc. which are of crustal origin dominates during the summer months like the giant particles (Fig. 3c). Comparing the seasonal patterns of size resolved number density and those of various chemical species, inferences are made on the size-dependent chemical composition of aerosols at this coastal site.

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H–O–7

Secondary Organic Aerosols and Associated Acidity over an Urban Environment

R. Rengarajan, A. K. Sudheer and M. M. Sarin

Physical Research Laboratory, Navrangpura, Ahmedabad 380 009

Email: rajan@prl.res.in

Introduction

Carbonaceous aerosols (elemental carbon (EC) and organic carbon (OC)) are ubiquitous in the atmosphere, comprising up to 80% of urban fine particulate matter, and impact significantly the regional air quality and climate. The organic aerosols, emitted from both natural and anthropogenic sources are primary and secondary in nature. In this context, estimates of secondary organic aerosol (SOA) production based on biogenic (isoprene and terpenes) and/or anthropogenic volatile organic compound (VOC) precursor fluxes and on the characteristic EC/OC ratio suggest that their dominance over primary component, especially from biogenic sources. However, large discrepancies exist in estimating fluxes, up to an order of magnitude, and the inconsistencies are attributed to the poor understanding of SOA production mechanism from the precursors. An enhancement in SOA production from oxidation of VOC with increased acidity of seed aerosols has been demonstrated by several laboratory experiments (Jang et al., 2002; Gao et al., 2004) but requires evidence from field observations. In this study, the co-variation of secondary organic carbon (SOC) along with H+ ion concentration (referred as aerosol acidity) over an urban environment has been investigated.

Experimental Methods

PM2.5 samples (aerodynamic diameter <2.5 μm) were collected on Tissuquartz filters (Pall Life Sciences) using high-volume air samplers (Tisch Inc. Ltd., USA) for a period of 30 days from 8th December, 2006 to 7th January, 2007 at Ahmedabad (23°02’N, 72°32’E), an urban location in semi arid region of Western India. Elemental carbon and organic carbon content were measured using EC-OC analyzer (Sunset Laboratory) by NIOSH protocol (Rengarajan et al., 2007). Organic matter concentrations were estimated from measured OC by a conversion factor of 1.6. One aliquot of sample filter was subjected to water extraction and the pH of the solution was determined immediately using glass electrode and subsequently water-soluble organic carbon (WSOC) and water-soluble ionic species were measured using TOC analyzer (Shimadzu, TOC5000A) and Ion chromatography (DIONEX 500) respectively. pH of water extract was expressed in terms of atmospheric H+ ion concentration which can be considered as a measure of pH of the deliquescent particles. Castro et al. (1999) had suggested the use of minimum OC/EC ratio in the ambient aerosols to be of primary origin. Thus SOC was estimated by EC- tracer method assuming minimum OC/EC as the primary ratio.

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Results and Discussion

During wintertime (Dec-Jan), PM2.5 mass ranges from 32 to 106 g m-3 (Av. = 56 g m-3). The average chemical composition of PM2.5 at the study location is summarized in Fig. 1. Of the total mass, inorganic salts constitute 29%, organic matter 53%, EC 5.4% and unidentified insoluble component is 21%. The OC varied from 11 to 39 g m-3 (organic mass: 17 to 62 g m-3) and exhibits a linear correlation with EC indicating its major contribution from anthropogenic sources. The OC/EC ratio varies from 4.0 to 8.1 and SOC content constitutes about 25% of total OC. SO42- and NO3- are the dominant inorganic acidic species (SO42-: 3.2 – 23 g m-3, NO3-: 0.7 - 2.1 g m-3), mostly neutralized by NH4+ and their major sources in the atmosphere are the oxidation of their gaseous precursors, NOx and SO2, emitted from various anthropogenic activities.

Water soluble organic matter (calculated from WSOC by multiplying with 1.9) is the major water soluble component and ranged from 7.6 to 28 g m-3. Water soluble organic component generally consists of oxygenated organic compounds containing various functional groups such as alcohols, carbonyls, and dicarboxylic acids and significant fraction of SOC is expected to be water soluble. WSOC/OC ratio varied from 0.26 to 0.52 and on an average, WSOC constitutes 41% of the total OC during the study period.

Figure 1. Contribution of carbonaceous and water-soluble ionic species to the total mass of the PM2.5 aerosol samples. Mineral component is calculated by subtracting the measured mass of OC, EC and water soluble ionic species from that of PM2.5 aerosols

The secondary organic aerosol formation is favoured by the acidic nature of pre- existing aerosols on which the heterogeneous reactive uptake of VOC can occur. H+ ion concentration determined from the measured pH of aerosol water extract shows significant correlation with SOC concentration (Fig. 2). This provides the direct evidence for the enhanced SOC formation at higher pH of the aerosols. WSOC concentration also varies linearly with H+ ion concentration further indicating that aerosol acidity favours the SOC formation. These results have major implications on the understanding the SOA formation

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mechanisms and dominance of regional scale sources of carbonaceous aerosols in the South Asian region. Detailed studies covering sufficient spatial and temporal scales with multi-parameter tracers are necessary in order to understand SOA formation quantitatively.

Figure 2. H+ ion concentration in determined from the measured pH of aerosol water extract shows significant correlation with SOC and WSOC concentrations

References

Castro, L.M., C.A. Pio, Roy M. Harrison and D.J.T. Smith (1999) Carbonaceous aerosol in urban and rural European atmospheres: estimation of secondary organic carbon concentrations, Atmos. Environ., 33, 2771-2781.

Gao, S., N. L. Ng, M. Keywood, V. Varutbangkul, R. Bahreini, A. Nenes, J. He, K. Y. Yoo, J. L. Beauchamp, R. P. Hodyss, R. C. Flagan and J. H. Seinfeld (2004) Particle-phase acidity and oligomer formation in secondary organic aerosol. Environ. Sci. Technol. 38, 6582-6589.

Jang, M., N. M. Czoschke, S. Lee and R. M. Kamens (2002) Heterogeneous atmospheric aerosol production by acid-catalyzed particle phase reactions. Science 298, 814-817.

Rengarajan, R., M. M. Sarin, and A. K. Sudheer (2007) Carbonaceous and inorganic species in atmospheric aerosols during wintertime over urban and high-altitude sites in North India, J. Geophys. Res., 112, D21307, doi:10.1029/2006JD008150.

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H–O–8

Aerosol Columnar Optical and Chemical Properties Over Kharagpur and Implications to Climate Impact

K. R. Santhosh1 and S. Verma1

1Department of Civil Engineering

Indian Institute of Technology, Kharagpur, West Bengal, India

Keywords : Aerosols, Aerosol optical depth, Angstrom Exponent, Single scattering albedo

Aerosols are tiny, suspended solid particles or liquid droplets emitted into the atmosphere from either natural or anthropogenic sources. Aerosol particles induce radiative forcing through reflection and absorption of solar and infrared radiation in the atmosphere. Aerosol emissions resulting from human activities can significantly affect local climate through shifts in radiation causing a substantial effect on surface energy and water balance (IPCC, 2007). With the growing population, industrialization and urbanization, the aerosol loading in India is increasing substantially that has significant impact on the weather or climatic conditions.

The Indo-Gangetic Basin (IGB) occupies a vast area around 21% of the land area in India, which is densely populated accommodating around 40% of the Indian population. Recent studies showed the presence of high aerosol optical depth (AOD), greater than 0.6, over the IGB with an increasing aerosol concentration dominated by finer particles in the eastern part of the basin (Aloysius et.al., 2008). Aerosols over the basin reduce the solar radiation reaching the surface by 19% (Dey and Tripathi, 2007). Aerosol optical properties measured over the eastern part of IGB at Kharagpur (22.3oN, 87.2oE) during December 2004 showed the mean AOD of 0.7 on all clear days (Niranjan et.al., 2006). It is required to characterize the aerosol optical and chemical properties over the eastern IGB during the different seasonal periods.

This work was undertaken to estimate the columnar aerosol optical and chemical properties and understand their climate impacts at Kharagpur (22.3oN, 87.2oE) during the different seasonal periods, including the south west monsoon (August, September), post monsoon (October, November) and winter (December to February) seasons. Kharagpur is located at the eastern end of the IGB, towards the east coast of India, and is one of the pollution outflow vents from Indian subcontinent into the Bay of Bengal. Aerosol columnar optical and chemical characteristics were estimated through fitting an appropriate aerosol model in OPAC (Optical Properties of Aerosols and Clouds) (Hess et.al., 1998) with applied constraints which included measured surface mass concentration of aerosols, measured aerosol optical depth (AOD) using MICROTOPS II Sunphotometer and Angstrom Exponent, AOD and angstrom exponent retrieved from satellite observations with MODIS (Moderate Resolution Imaging Spectroradiometer, http://disc.sci.gsfc.nasa.gov/giovanni) and other available ground based observations from literature. Figure.1a depicts the comparison between AOD measured using MICROTOPS II Sunphotometer with the AOD retrieved

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from MODIS at Kharagpur showed a good match during the period of study while the Figure.1b shows the comparison of clear-sky AOD measured from MICROTOPS II Sunphotometer with the OPAC model estimated clear-sky AOD which pictures the measured AOD was exactly matched with the model estimated AOD. Monthly variation of clear-sky AOD @500 nm measured during the study period showed the highest AOD in December (0.80) during winter and lowest August (0.53) during monsoon. The measured Angstrom Exponent values were well matched with model estimated Angstrom Exponent and found to be greater than 1 for all the months except August in which the value was found to be lower which clearly indicates the domination of larger particles in the atmosphere while for other months the values were higher indicates the dominance of finer particles. Clear-sky AOD estimated from the various aerosol components contributing to the total clear-sky AOD from OPAC showed that the major contributor was water- soluble part of aerosols contributing a mean of 56% followed by soot (31%) and sea-salt accumulation mode (20%) which was pictured in the Figure.2c. Single Scattering Albedo (SSA) estimated at 550 nm was found to be higher during August (0.99) and September (0.99) in monsoon season which clearly indicates the absence of soot particles. The minimum value was found to be estimated during January (0.64) which clearly indicates the domination of soot particles in the atmosphere due to increased anthropogenic activities

Figure 1. (a) Comparison of AOD measured using MICROTOPS II Sunphotometer with MODIS data ; (b) Comparison of clear-sky AOD measured using MICROTOPS II Sunphotometer with estimated AOD from OPAC

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and absorbing type of aerosols in the atmosphere during winter season. The paper will include analysis on aerosol properties during the different seasonal periods.

Figure 2. (a) Species contribution to total surface mass concentration for the different months ; (b) AOD contributed by each species in the different months; (c) Percent AOD contributed by each species in the different months

References

1.M. Aloysius, M. Mohan, K. Parameswaran, S.K. George, and P.R. Nair. Aerosol transport over the Gangetic basin during ISRO-GBP land campaign-ii. Ann. Geophys., 26:431–440, 2008.

2.M. Hess, P. Koepke, and I. Schult. Optical properties of aerosols and clouds: The software package OPAC. Bull. Am. Meteorol. Soc., 79:831–844, 1998.

3.Intergovernmental Panel on Climate Change (IPCC). Climate Change 2001: The Scientiûc Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. J. T. Houghton et al., Cambridge Univ. Press, New York, 2001.

4.K. Niranjan, V. Sreekanth, B. L. Madhavan, and K. Krishna Moorthy. Wintertime aerosol characteristics at a north Indian site Kharagpur in the Indo-Gangetic plains located at the outûow region into Bay of Bengal. J. Geophys. Res., 111(D24209), 2006.

5.Sagnik Dey and S. N. Tripathi. Estimation of aerosol optical properties and radiative effects in the Ganga basin, northern India, during the wintertime. J. Geophys. Res., 112(D03203), 2007.

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H–O–9

Rapid Elemental Characterization of Respirable Aerosols with Scanning Electron Microscope Hyphenated with Energy Dispersive X-Ray Spectrometry

R.K.Singhal, Manisha Venkatesh, H.Basu, P K Sharma and

A.V.R.Reddy

Analytical Spectroscopy Section, Analytical Chemistry Division

BARC,Trombay Mumbai-40085

rsinghal@barc.gov.in

Trace metals are released into the atmosphere during combustion of fossil fuels and wood as well as during high temperature industrial processes and waste incineration. This may result in elevated elemental concentrations in atmospheric particulate matter which can poses a risk to human health. During this work respirable particle in the size range of <0.08 -10 m were collected by using nine stage “Anderson cascade impactor”. Details of sampling are given elsewhere1-2.

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Fig.2 gives the mean (six different sampling) mass concentration of particle collected at different stages while Fig.3 gives the mean

elemental percentage distribution for size fraction between >0.7- 1.1 m. At other stages similar distribution was obtained with variation in the range 3-7%. Elemental composition of the particles reveals the presence of many elements viz. Si, Al, Fe, K, Fe, Ca, S and C in appreciable quantity. The occurrence of these elements point towards the presence of sources other than natural. These sources could be vehicular, industrial and the thermal power plants or oil refinery in the vicinity of sampling site. Elemental composition of the particles shows that Si, Al, Na and Cl are dominating over all the elements. Higher concentration of Si & Al confirms that at Trombay in this particular size range most of the particles are of natural origin i.e. mountainous (dusts eroded from mountainous rocks) whereas Na & Cl confirm the presence of marine environment. Low concentration of carbon and Pb indicate that Trombay environment is not much influenced by vehicular & other industrial pollutants. However occurrence of these metals point towards the presence of sources other than natural.

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References

1.Singhal R.K., .Narayanan U, and Bhat I.S. Investigation on Interception and Translocation of Airborne 85Sr, 131I, 137Cs in Beans, Radish, Spinach Plants. Journal of Water, Air & Soil pollution 101 163-176 1998.

2.Singhal R.K., Preetha J, Kumar Ajay, Divaker J., Karpe Rupali and Hegde A.G. Predication of long term behaviour of resuspension factor for respirable dust in Tropical environment. IASTA Bulletin 17 ( 1&2) 728-730, 2005.

3.Allen, A. G., Nemitz, E., Shi, J. P., Harrison, R. M., and Greenwood, J. C. Size distribution of trace metals in atmospheric aerosols in the United Kingdom. Atmospheric Environment, 35, 4581–4591 2001.

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H–P–1

Particulate Polycyclic Aromatic Hydrocarbons (Pahs) Concentration and Related Carcinogenic Potencies in the Central Part of India

Amit Masih*1 and Ajay Taneja2

1St.Andrew’s College, Gorakhpur,India,

2Dr. B.r.a. University, Agra, India

E-mail : 1amitmasih10@yahoo.com, 2ataneja5@hotmail.com

ABSTRACT : Atmospheric particulate matter from four different areas within Agra city (a semi-arid region) were collected using respirable dust samplers during the 2006 summer season and were then extracted with dichloromethane using an automated Soxhlet Extraction System (Soxtherm®). The extracts were analyzed for 17 target Polycyclic Aromatic Hydrocarbons (PAHs). The total PAH (TPAH) concentrations were 76.6, 27.9, 23.7 and 6.5 nanograms per cubic meter (ng m-3), respectively, at the industrial, residential, roadside and agricultural sites. The combined mean concentration of TPAH was 33.9 ng m-3 for all sites. The industrial site had the highest TPAH concentration followed in order by the residential, roadside and agricultural sites. Indeno(1,2,3-cd)pyrene, benzo(g,h,i)perylene and benzo(b)fluoranthene were the predominant compounds found in the samples collected from all of the sites. The carcinogenic potencies related to PAHs have been calculated by using Toxic Equivalent Factors (TEFs) compiled from the literature.

Introduction

Polycyclic Aromatic Hydrocarbons (PAHs) are chemicals containing two or more fused benzene rings in a linear, angular or cluster arrangement. PAH contain only carbon and hydrogen. They belong to the group - Persistent Organic Pollutants (POPs) known for their chemical carcinogenicity. They are formed during incomplete combustion of organic materials and geochemical formation of fossil fuels and are the products of thermal decomposition. Sources of PAHs include automobiles, re-suspended soils, refineries and power plants. It is well established that some PAHs have carcinogenic, mutagenic and immunotoxic effects on animals and can occur in low concentration in many parts of the environment (Grimmer, 1983). Due to their mutagenic and carcinogenic potential the atmospheric concentrations of PAHs in many geographical locations of the world have been measured and reported, e.g. Massachusetts, USA (Allen et al, 1996) Ontario, Canada (Katz et al, 1978), Athens, Greece (Viras et al, 1987), Antarctica (Caricchia et al, 1999), Lahore, Pakistan (Smith et al,1996) and even in Mumbai, India (Kulkarni and Venkataraman,2000). In many circumstances the environmental occurrence of PAHs has been associated with adverse effects on public health (Grimmer, et al, 1983). It is believed that there is no “Threshold” or “Safe” level for the mutagenic compounds, hence exposure to these PAHs at any level provide the risk of toxic effects.

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In Agra the most important source of PAHs is expected to be vehicular emission since motor vehicles contributed as much as 60% of pollution. As of August 2006 there were 3, 36,635 registered vehicles in Agra (News item, Amar Ujala, 2006). There are also other important potential sources of PAHs such as smoke coming from diesel generators which are 32,030 in Agra and are in use because of erratic power supply.

The concentration determined for individual PAH will help Planners, Scientists, and Administrators to draw strategies to reduce PAH exposure to the people living in this area. The aim of this study is to investigate the concentration and distribution of particulate PAHs in Agra.

Methodology

Air sampling stations were set up in the four locations, representing industrial, residential, roadside and agricultural areas, were selected for study. Each station was monitored for ambient air quality twice a month in a scheduled manner. Particulate Matter (PM10) in air were collected on 20.3 x 25.4 cm2 glass fiber filter paper (EPM-2000) using respirable dust samplers (RSPM Envirotech Sampler RDS, 460 DX, New Delhi, India) at the rate of 1.0 cubic meter per minute (m3/min). The air suction rate was verified every week using calibrated rotameters with an accuracy of ±1%. Samples were stored in a cool, dark place until analysis. Samples and blanks were extracted with 140 milliliters (mL) methylene chloride by Soxtherm®. Blank spike/blank spike duplicate (BS/BSD) samples (spiked with PAH spiking solution) were extracted using clean fibreglass thimbles. No surrogates were added. After the samples were extracted for one programmed cycle, 100 mL of additional solvent was added. All samples were extracted for another programmed cycle and then concentrated to 1.0 mL. Internal standards were added to all extracts prior to sample injection. The gas chromatograph (GC) oven was temperature programmed to separate the method analytes on a fused silica column, which were then detected with a mass spectrometer (MS).

Results and Discussion

Summer season comprises of four months i.e. from March to June. The atmospheric pollution load is high and because of the down ward wind, pollutants may be transported to the different areas mainly from an oil refinery situated in Mathura (50 kms from the centre of Agra City).

This period is often characterized by strong dust storms caused due to low pressure developed in this area. The temperature and relative humidity ranges from 15.4°C to 48.8°C and 18.4%- 62.7% respectively. The down ward wind is west and north-north-

west and its speed

Figure 1: TPAH concentrations in ambient air at Agra during summers.

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ranges from 0.2 m s-1 to 9.2 m s-1 in summers (Parivesh, 2006). The average TPAH concentrations measured in ambient air at the various sites are presented in Figure 1. The TPAH concentrations were 76.63, 27.96, 23.79 and 6.54 ng m-3 at industrial, residential, roadside, and agricultural sites, respectively. The combined mean concentration of TPAH was 33.95 ng m-3 for all sites. The industrial site had the highest TPAH concentration followed by the residential, roadside and agricultural sites. These results also indicate that PAH concentrations are strongly linked to land use.

Table 1 indicates the mean concentration of TPAHs in Agra to be 33.6 ng m-3, which corresponds to a B(a)P equivalent exposure of 8.9 ng m-3 and 8.6 ng m-3 with respect to carcinogenicity, using TEFs given by Tsai et al. (2004) and EPA Region III (2006), respectively.

Table 1. BaP toxic equivalency factors (TEFs) and BaPeq exposure profiles (ng m-3)

*TEFs cited by Tsai et al. (2004) +TEFs cited by EPA Region III (2006)

Figure 2 shows the relative contribution of 2-, 3-, 4-, 5-, and 6-ring PAHs in the atmosphere at the locations investigated in this study. The average TPAH percentage based on the number of rings were 0.67% (2-ring), 3.41% (3-ring), 21.72% (4-ring), 41.18% (5- ring), and 33.05% (6-ring). The major contributors to TPAH in the Agra region were 5-ring and 6-ring PAHs (41.18% and 33.5% of the TPAH respectively).

The concentration trends of the major PAH found in present study are illustrated in Figure 3, which were: benzo (g, h, i)perylene > indeno(123-cd)pyrene > benzo(b)fluoranthene benzo(a)pyrene at the industrial site; benzo(b)fluoranthene >

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Figure 2. Distribution of PAHs based on benzene ring at different locations of Agra in summers

indeno(123-cd)pyrene > benzo(k)fluoranthene > benzo(g,h,i)perylene at the residential site; benzo(g,h,i)perylene > benzo(b)fluoranthene > benzo(a)pyrene > indeno(123-cd)pyrene at the roadside site: and benzo(g,h,i)perylene > indeno(123-cd)pyrene > benzo(k)fluoranthene > benzo(b)fluoranthene at the agricultural site. At all the sites, indeno(123-cd)pyrene, benzo(g,h,i)perylene, and benzo(b)fluoranthene were the predominant compounds.

Figure 3. Trends of individual concentrations of PAHs in ambient air at different sites of Agra (ng m-3) during summers

Figure 4 shows the variation in the concentration of PAHs depending on different locations. It is clear from the figure that much variation is found in industrial and agricultural sites whereas the residential as well as roadside sites have almost similar concentration of PAHs.

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Figure 4. Location based variation in the concentration of individual PAHs in summers

Conclusion

The TPAH concentrations were 76.63, 27.96, 23.79 and 6.54 ng m-3 at industrial, residential, roadside, and agricultural sites, respectively. The combined mean concentration of TPAH was 33.95 ng m-3 for all sites. The industrial site had the highest TPAH concentration followed by the residential, roadside and agricultural sites. These results also indicate that PAH concentrations are strongly linked to land use. The average TPAH percentage based on the number of rings were 0.67% (2-ring), 3.41% (3-ring), 21.72% (4- ring), 41.18% (5- ring), and 33.05% (6-ring). The major contributors to TPAH in the Agra region were 5-ring and 6-ring PAHs (41.18% and 33.5% of the TPAH respectively). The result shows that the variation in the concentration of PAHs depends on different locations. The mean concentration of TPAHs in Agra to be 33.6 ng m-3, which corresponds to a B(a)P equivalent exposure of 8.9 ng m-3 and 8.6 ng m-3 with respect to carcinogenicity. It is also clear that much variation is found in industrial and agricultural sites whereas the residential as well as roadside sites have almost similar concentration of PAHs.

Acknowledgement

The authors gratefully acknowledge the financial assistance received from DST (Department of Science and Technology, New Delhi, India) Project No. SR/S4/AS: 228/03.

References

Allen, J.O and Dookeran, N.M., 1996. “Measurement of PAHs associated with size segregated atmospheric aerosols in Massachusetts”. Environmental Science &Technology., 30: 1023-1031

Caricchia A.M., Chiavarini S. and Pezza M., 1999. Polycyclic aromatic hydrocarbons in the urban atmospheric particulate matter in the city of Naples (Italy). Atmospheric Environment 33, 3731-3738

EPA Region III, 2006. Table of Risk-Based Concentrations, 2006. Published by the US Environmental Protection Agency on the Internet at: http://www.epa.gov/reg3hwmd/risk/human/rbc/rbc0406.pdf

Grimmer, G.G. (Ed), 1983. “Environmental Carcinogens: PAHs Chemistry, Occurrence, Biochemistry, Carcinogenicity”. CRC Press, Inc., Boca Raton, FL.

Kayz, M., Sakuma, T. and Ho,A., 1978. “Chromatographic and spectral analysis of Polynuclear Aromatic Hydrocarbons quantitative distribution in air of Ontario cities”. Environmental Science & Technology., 12: 909-915

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Kulkarni, P. and Venkataraman, C., 2000. “Atmospheric PAHs in Mumbai, India”. Atmospheric Environment 32, 3795-3799

Parivesh, 2006. - A magzine published by Dr. B. Sengupta, Member Secretary, CPCB, Delhi, November 2006, Page-8

News item, Agra delimma, Amar Ujala, August 12, Page-8 (2006)

Smith, D.J.T., Harrison, R.M. and Luhana, 1996. “Concentrations of particulate airborne PAHs and metals collected in Lahore, Pakistan”, Atmospheric Environment, 30: 4031-4040

Tsai, P-Jy., Lee, C.C., Shih, T.S., Chen, S.L., Lee, W.J., Lai, C.H. and Liou, S.H., 2004, “Assessing and predicting the exposure of PAHs and their carcinogenic potencies from vehicle engine exhausts to highway toll station workers”. Atmospheric Environment, 38, 333—343

Viras, L.G., Siskos, P.A. and Stephanou, AS.E., 1987. “Determination of PAHs in Athens atmosphere”.

International Journal of Environmental Analytical Chemistry, 28:71-85

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H–P–2

Water-soluble Ionic Speciation of PM10 Aerosol of Different Land use Locations in Mumbai city

Abhaysinh Salunkhe#+, Sugandha Shetye+, Rakesh Kumar#

and Indrani Gupta#

# National Environmental Engineering Research Institute, Mumbai Zonal Laboratory, Worli, Mumbai-18.

+ K.J.Somaiya College of Science & Commerce, Vidhyavihar, Mumbai-77.

abhay.salunkhe@rediffmail.com,rakeshmee@rediffmail.com,indranig1@rediffmail.com

Introduction

Mumbai is one of major conglomerations of urban clusters called Greater Mumbai which comprises of island city and its suburban regions. In recent times, urban centers are struggling with the particulate levels as other pollutants largely meet the standards. Monitoring of PM10 is of great significance because of its serious health problems related to the respiratory & cardiovascular systems. Airborne PM may be either primary or secondary in origin. Primary particles are emitted directly into the atmosphere from the sources such as road traffic, coal burning, industries, wind blown soil dust and some natural sources such as sea spray. Secondary particles are those that form in the atmosphere from chemical reaction of gases that are directly emitted by varied sources. SOx, NOx and NH3 are the precursors for Sulphuric acid, Ammonium bisulphate, Ammonium Sulphate, Ammonium nitrate and also to some extent Ammonium chloride particles (Zhang et al., 2002). The major pathways for such a transformation are photochemical redox reactions. Duration of formation of secondary aerosol varies from the few minutes to hours or in some cases days. These particles have long atmospheric life time. Particles such as Ammonium nitrate are highly volatile in nature and transfer mass between the gas and particle phase to maintain the equilibrium (Chen, et al., 2001). In this study an attempt has been made to understand the variation of main acid precursors which are responsible for acid nuclei formation in PM10. Acid precursors are of environmental concern as they have deleterious effects on forest as well as aquatic system. They are dominant pollutants which are responsible for causing the various chronic disorders. Even on global scale, these species are responsible for causing disturbances in radiation balance and affect the mechanisms of various photochemical reactions in the atmosphere (Abba E, et al., 2002).

Sampling Location and Experimental Methodology

PM10 was measured at four different locations which were categorized as Colaba as Control site, Dadar as Kerb cum commercial site, Khar as residential site and Mahul as industrial site during 2007-2008. PM10 was collected on a glass fiber filter (8X10"pall life science GF/A) using Envirotech Respirable dust Sampler (Model APM460NL).The collected mass was first analyzed gravimetrically and later for the water soluble anion and cations.

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Small portion (47mm) of exposed filter paper was subjected to extraction using ultra pure distilled water in ultrasonic bath for 60 minutes. The extract was filtered using the Teflon syringe filters and final volume was made up to 50ml by ultra pure water. Extracted samples were preserved at 40C to avoid any volatilization loss and microbial contamination. Samples were then analyzed on Ion chromatograph (Dionex ICS3000) equipped with electrochemical detector for the cations Na+,K+,Ca+2 and Mg+2 and Anion F-,Cl-,SO4-2 ,NO3- and PO4-2.

Results

Table 1. gives the descriptive statistics at four sites of Mumbai. The average concentration of PM10 was very high at Mahul followed by Khar, Dadar and Colaba. At all locations the average concentration of PM10 is exceeding the CPCB 24 hrs average standard of 100 μg/ m3 for rural residential and mix use area.

Table 1. Ionic mass concentration at four locations in Mumbai

Note: All values are average of 30 samples at each site

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At Mahul, major petroleum refineries are located along with a Thermal power plant. Among anions, concentrations of Sulphate were very high at Khar and Mahul followed by Colaba and Dadar. Whereas in case of Nitrate, values were observed very high at Dadar followed by Mahul, Khar and Colaba. Precursor of NO3- is the NOX emission which is mainly emitted from vehicular exhaust. The higher values at Dadar and Mahul are due to high density of vehicles in that area. NH4+ ion is found to be higher at Dadar and Mahul followed by Colaba and Khar. The major origin of NH4+ ion is the Ammonia gas which is emitted from the sanitary waste and biomass degradation. Mahul site is located near the Fertilizer industry, having production of Ammonium based fertilizers. Next important ion is the K+, which is the tracer for the biomass burning. Potassium shows high values in the order of Mahul, Dadar, Khar and Colaba. In case of Mahul and Dadar the biomass and refuse burning are the possible sources of K+ emission. Mumbai being the coastal city, sea spray is one of the source of PM10. Ions like Na+, Cl- and F- having major contribution from sea salt; however it shows unequal distribution at four locations. Among all four locations, Colaba and Mahul are very close to sea shore showing considerable levels of sea salt. Other most important elements such as Ca+2 and Mg+2 are contributed from resuspended road dust and some anthropogenic activities such as construction and demolition activities. In present study, higher values of Ca+2 and Mg+2 are observed at all four sampling locations.

Pearson correlation matrix

Pearson correlation was determined to understand association between ionic species. Pearson correlation matrix between the ions was obtained using the SPSS software Ver.13.2. From the statistical analysis, some significant correlation between the ions was found at all four sites. Of those which are correlating significantly above 0.5 at four study locations are presented in Table 2.

*Correlation is significant at 0.05 level (2-tailed), ** Correlation is significant at 0.01 level (2-tailed).

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From the above table, it is clear that NO3- correlate significantly with the SO4-2 at all site at 0.01% significance level. It indicates that formation of these two ions is from common sources. They are formed from their precursor gases like SO2 and NOx. Similarly in case of NH4+ vs. SO4-2 correlation, it is found to be at significant level at Colaba, Dadar and Mahul. In case of Khar, it is very poor, the reason for such a circumstance at Khar could be that, SO4-2 instead of combining with ammonium ion it gets bound with some other ions such as potassium which is mainly contributed from biomass and vegetative burning or natural source such as sea spray (S.Liu et al.2008). Similar relation of K+ vs. SO4-2 was observed at Dadar as well as Mahul. According to other researchers that NH4+ never neutralize all the SO4-2 in the particulate matter but some part of SO4-2 may go with some other cationic species such as K+ or in some cases with Na+ also. It has been observed in case of Dadar that, Na+ vs. SO4-2 showing negative correlation it concludes that these two ionic species do not exist together. Where interms of K+ vs.SO4-2 shows the significant correlation at Dadar, Khar and Mahul. Whereas in case of NH4+ vs. NO3- relations it shows that these species are existing together in the form of Ammonium Nitrate particles It seems NH4NO3 particles have less life time due to high volatilization rate hence these molecules are dissociated reversibly. This mechanism of dissociation and reformation is the function of temperature and humidity (Chen, et al., 2001). Hence NH4NO3 is more stable during the night time. Due to this volatility of NH4NO3 particles, there could be a possibility that NO3- particles forms stable compound with K+ ions which gets corroborated by the correlation of K+ vs. NO3- ions. This good correlation is observed at all the four sites. In another correlation of NH4+ vs. Cl-, ammonium ions may be combining with the Chloride ions to form the Ammonium Chloride particles. Since its known that NH4Cl particles are highly volatile in nature, it was found that there is a very poor correlation of NH4+ vs. Cl- at Colaba and Dadar. Amongst the other ions, Ca+2 vs. Mg+2 show significant correlation at Dadar, Mahul and moderate at Colaba and Khar indicating that their possible source could be soil. Similarly significant correlation between K+ vs. Cl- at Colaba, Dadar and Mahul indicates biomass burning as well as K+ vs. Mg+2 also supports to some extent the contribution from soil and sea spray.

Cation-anion Balance

It was found from an ion balance study for PM10, that correlation coefficient (r) of cation to anion is ranging between 0.58-0.92. The anion and cation balance may vary due to presence of some ionic species, not easily quantifiable. In ionic balance, anion deficiency is mainly due to unidentified carbonate and bicarbonates, which dominantly originate from soil. In case of cations, Hydrogen ion has not been measured (H.Wang et al., 2002). In case of Colaba site, correlation coefficient between ionic balance is at significant level (r =0.67) as also in case of Dadar (r =0.76). Similar results were found in case of Mahul (r = 0.92) and with Khar, (r =0.58).

Ammonia Balance by calculated and measured values at four sites

Ammonium ion is the major component of Particulate matter. Ammonia emitted by decomposition of biogenic mass and waste material gets rapidly converted to NH4+ aerosols at a rate of 30% h-1(Abba E, et al., 2002). It reacts with acidic gases like sulphuric and nitric acid in the air, forming Ammonium salts and it most likely prevails in the form of ammonium sulphate/bisulphate and ammonium Nitrate. Many studies performed at different places in the world have pointed out that this cation accumulates in the fine

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particulate ranges and correlating well with sulphate,suggesting that ammonium sulfate/ bisulphate must be the major ammonium salt (Zhang, et al., 2002) (Kumar et al., 2006). The ammonium based on NH4NO3 and NH4HSO4 is calculated from the Eq.I , whereas the Ammonium based on NH4NO3 and (NH4)2SO4 is calculated from Eq. II

Values calculated for ammonium aerosol in the form of Sulphate/bisulphate and nitrate using above Eq.I and II are use to calculate measured values of ammonium ion for all four sites and summary of correlation coefficient (r) as shown in Table 3. From the r values it can be concluded that in case of Colaba, Dadar and Mahul formation of Ammonium bisulphate [(NH4)HSO4] and NH4NO3 are considerably dominant than the formation of (NH4)2SO4 and Ammonium nitrate aerosol. Whereas in case of Khar similar trend were observed but values are not to significant level.

Table 3. Correlation coefficient (r) of plot of Measured NH3 VS. NH4HSO4 / (NH4)2SO4 andNH4NO3.

Conclusions

It is highly desirable to monitor particulate matter concentration (PM10) and report water soluble inorganic ionic composition associated with this PM10. From the ionic data analysis it can be observed that city like Mumbai has mixed type emission sources which are responsible for high levels of PM10. The anthropogenic sources include Vehicular exhaust, Biomass burning and Industrial emissions and some other diverse sources such as Hotels Restaurants, Crematoria and Bakeries and locomotives. Due to high density of vehicular movements and poor road conditions in the area such as Mahul and Dadar, the prevalence of road dust is very high. Mumbai being the coastal city shows the significant contribution of sea salt into the PM10.With respect to the Secondary inorganic aerosol formation and different photochemical oxidation reactions of precursor gases like SOx, NOx and NH3 which finally result into the formation of sulphate, nitrate and ammonium ions can be interpreted by the concept of ion balance and Ammonia balance around the study area. To understand more about the ionic behavior in Fine mode of particulate matter (i.e.PM2.5 or PM1.0) there is need of more such type of study for Mumbai city.

Acknowledgment

The authors wish to thank EMU Division and Mr.A.G.Gawane, NEERI, Nagpur for providing instrumental facilities. Also wish to thank NEERI staff at Mumbai Zonal Laboratory.

References

Zhang X.Y.,Cao J.J.,Li L.M.,Arimoto R.,Cheng Y.,Huebert B. and Wang D., (2002). Characterization of Atmospheric Aerosol over XiAn in the South Margin of the Loess Plateau, China, Atmospheric Environment 36 (2002), 4189-4199.

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Chen S.J.,Tsai C.C.,Shue F.M. and Fang C.G., (2001) Contribution of Secondary Aerosol to PM10 In Kaoping Metropolitan Area Over Southern Taiwan, Journal of Chinese Institute of Environmental Engineering,Vol.11, No.2, (2001), 105-113.

Abba E., Sawant A.D. and Srivastava A., (2002). Anionic Composition of PM10 Aerosol-a case study in Mumbai city, IASTA-2002/SessionII/P-2,138-141.

Liu S.,Hu M.,Slanina S.,He Y.L.,Niu W.Y.,Bruegemann E.,Gnauk T. and Herrmann H.,Size distribution and source analysis of ionic compositions of aerosols in polluted periods at Xinken in Pearl River delta (PRD) of China, Atmospheric Environment42 (2008),6284-6295.

Wang H. and Shooter D.,Coarse-fine and day-night differences of water-soluble ions in atmospheric aerosol collected in Christchurch and Auckland, New Zealand, , Atmospheric Environment 36 (2002),3519-3529.

Kumar R.,Abba E.,Gawane A.G.,(2006) Air Quality profile of Inorganic ionic Composition of Fine Aerosols at Two Sites in Mumbai City, Aerosol Science and technology, 40:477-489.2006

Standard Operating procedure for PM2.5 Anion and Cation analysis, Environment and Industrial Measurement Division Research institute, California.

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H–P–3

Measurement and Chemical Characterisation of Background Aerosol in the Delhi Region

Amrita Singhai1, Anil Mandaria2, Gazala Habib1,*, Tarun Gupta2

Indian Institute of Technology Delhi1, Indian Institute of Technology Kanpur2

*Corresponding Author: Email:gazalahabib@gmail.com

Introduction

Anthropogenic aerosols are thought to have severe impacts on health, urban air quality and climate, although the magnitudes of these impacts remain quite uncertain. Aerosols comprise of elemental carbon (EC) organic carbon (OC) sulfate, nitrate, trace elements and organic compounds formed from chemical conversion of organic vapour precursors. Aerosol affects the climate directly by perturbing the Earth-Atmosphere energy budget and indirectly by changing the cloud properties and lifetime a thus affecting the hydrological cycle [Ramanathan et al., 2001]. For example EC, emitted from the incomplete combustion, is light-absorbing component plays an important role in visibility reduction and contributes to aerosol radiative forcing. EC may also perturb the vertical temperature profile and hence alter the level and degree of cloud formation [Hansen et al., 1997]. Once emitted, the particles are removed from the troposphere within few days, primarily by precipitation scavenging. As a result, their distribution is very inhomogeneous, both in the horizontal and vertical directions. Therefore, their impacts on local air quality and climate have been observed more severe than global [Ramanathan et al., 2001]. In order to understand the impact of aerosols and their sources on regional air quality and climate the first step is to establish the link between the aerosol properties and change in meteorological parameters, next is to identify the strength of local sources.

Recently, many Indian studies have focused on atmospheric aerosol measurement and their characterisation for health and local air quality assessment covering urban [Chowdhury et al., 2007; Badrinath et al., 2007; Ganguly et al., 2006; Karar and Gupta, 2006]. However, more measurements and detailed chemical characterisation of aerosols are needed for highly industrialised and densely populated metropolitan city like Delhi with following scientific objectives.

a) to understand the spatial distribution of source strength for implementation of pollution control strategy b) to understand the effect of long range transport of pollutants d) to understand the impact of pollutants on local air quality and meteorology. Therefore, present study is focused on measurement and chemical characterisation of the atmospheric background aerosol and their link with meteorology and long range transport.

Methodology

Experimental Setup

Two impactors designed for 1.0 mm and 2.5 mm cut size were operated at 10 and 15

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lpm respectively. The impactors are made of aluminium (Figure 2.1), developed at IIT Kanpur and evaluated in laboratory as well as in the field for the sampling of ambient particulate matter before final experiments. These impactors remove particles greater than 1.0 μm and 2.5 mm, respectively from the air stream and collect the remaining smaller size particles on filter substrate. These impactors were evaluated in the laboratory by using the wet and dry aerosol generation system and then tested in the field to collect ambient particulate matter. The developed sampling device consists of a single impaction stage and an after filter.

The ambient sampling was carried out at the roof (~20 m high) of the Administrative building within IIT-Delhi. Separate samples were collected for during day and night and averaged over 10 hrs each. The day time sampling were started at 7:00 am and stopped at 5:00 pm, night time sampling were started at 8:00 pm and stopped at 6:00 am. The sampling frequency was 3 days per week including Monday, Tuesday and Wednesday.

Figure 2.1. PM1.0 and PM2.5 air sampler and its internal components

Gravimetric Analysis

After completion of sampling, all the collected filters will be analyzed gravimetrically using a microbalance (Mettler, Toledo) range between 0.001 mg to 2 g. Before weighing the filters will be conditioned in a room with controlled temperature (25oC ±1oC) and relative humidity (50% ±5%) and permit the filter to equilibrate for at least 8 h. About 5% of the filters will be kept as blank.

Chemical Analysis

OC-EC Analysis : The collected particles will be subjected to elemental carbon (EC) and organic carbon (OC) measurement using the thermal optical- transmittance (TOT) carbon aerosol analyzer (Sunset Lab, USA) which was optimized to avoid biases in the organic and elemental carbon split according to ACE-Asia carbon inter-comparison study [Schauer et al., 2003]. The method involves thermal evolution of carbonaceous aerosol constituents, oxidation to CO2, followed by reduction to methane, and detection through flame ionization.

Anion and Elemental Analysis : Particles collected on Teflon filters will be analyzed for major elements – As, Ca, Cd, Co, Cr, Cu, Fe, Mg, Ni, Pb, Se, V, Zn and anions –F-, Cl-, NO3-, SO4-2, PO4-3. For chemical analysis each collected filter will be cut into two equal

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halves using a clean scissor. One half will be used for elemental analysis using ICP-OES (Inductively coupled plasma – optical emission spectrometer, Thermo Fischer, iCAP6300, Duo) and another half will be used for anion analysis using Ion Chromatography (compact IC 761, Metrohm).

Results

Average (20 h) concentration of PM2.5 and PM1.0 (Figure 3.1) have shown large monthly variation with lowest concentration were observed in the month of November, 2009 (175±50 mg m-3) and highest in December (285±117 mg m-3) and January (280±157 mg m- 3), 2010. PM1.0 was about 67-82% of PM2.5 showing same trend in monthly variation as PM2.5. Day to day variation was also high in December and January (Figure 3.1) indicating effects of regional meteorology and probably long range transport. Excessive foggy conditions were observed in these months resulting in fog formation through heterogeneous nucleation of water vapour on pollution particles. Further aerosol formation through aqueous-phase reactions of soluble gaseous precursors (SO2, H2O2) results in high aerosol concentration of species like sulphate, which then subsequently nucleate fog-smog-fog cycle [Pandis et al., 1990]. The aerosol concentrations were high during foggy days (Table 3.1), the high relative humidity at night time resulted in further increase in aerosol concentration corroborating role of aerosol in fog formation (Table 3.1). High contributions of aerosol during foggy days compared to clear days were also reported in previous studies [Mehta et al., 2009].

Further analysis of link between regional meteorological parameter (wind speed, wind direction, RH, temperature) and aerosol chemical species concentration will be presented. The back trajectories will be included to identify the prominent days of long range transport of aerosol.

Figure 3.1. Daily average (20 h) concentration of PM1.0 and PM2.5 during winter season

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Figure 3.2 Average (10 h) day and night concentrations of PM2.5

Table 3.1 Average 10 h PM2.5 concentration during foggy and clear days of winter season

References

Badarinath, K.V.S, K. M. Latha, T. R. K. Chand, R. R. Reddy, K. R. Gopal, L. S. Reddy, S. K. Narasimhulu, and K. R. Kumar (2007). Black carbon aerosols and gaseous pollutant in an urban area in North India during fog period, Atmos. Res. 85: 209-216.

Chowdhury, Z., M. Zheng, J. J. Schauer, R. J. Sheesley, L. G. Salmon, G. R. Cass, and A. G. Russell (2007), Speciation of ambient fine organic carbon particles and source apportionment of PM2.5 in Indian cities, J. Geophys. Res., 112, D15303, doi:10.1029/ 2007JD008386.

Ganguly, D., A. Jayaraman, T. A. Rajesh, and H. Gadhavi (2006), Wintertime aerosol properties during foggy and nonfoggy days over urban center Delhi and their implications for shortwave radiative forcing, J. Geophys. Res., 111, D15217, doi:10.1029/2005JD007029.

Karar K., and Gupta A. K. (2006), Seasonal variation and chemical characterisation of ambient PM10 at residential and industrial sites of an urban region of Kolkata (Calcutta), India, Atmos. Res., 81, 36-53.

Mehta B., C. Venkataraman, M. Bhushan, and S. N. Tripathi (2009) Identification of sources affecting fog formation using receptor modelling approaches and inventory estimates of sectoral emissions,

Atmospheric Environment 43 1288–1295.

Pandis, S. N., J. Seinfeld, and C. Pilinis (1990). The smog–fog–smog cycle and acid deposition. J. Geophys. Res. 95 (D11), 18489–18500.

Ramanatha et al. (2001) The Indian Ocean Experiment: An Integrated Assessment of the Climate Forcing and Effects of the Great Indo-Asian Haze. J. Geophys. Res., 106 (D 22): 28371-28399.

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H–P–4

Identification of Air Pollution Sources at Kanpur during Winter Season

Anil Mandaria, Jaiprakash and Tarun Gupta*

Environmental Engineering and Management Program, Department of Civil Engineering, Indian Institute of Technology, Kanpur, India

*Corresponding Author Email: tarun@iitk.ac.in

Introduction

Ambient origin fine particles have been found to play a key role in global climate change, in air pollution problems and in causing human health hazard. They affect atmospheric temperature by disturbing the natural energy balance of the Earth mainly by reflecting/absorbing solar radiation and influencing the reflective and absorbing properties of clouds. The study of the large-scale influence of aerosols on climate and human health hazards needs a deep knowledge of smaller particles and of their variations in size, chemical composition, distribution in time and space and residence times. The chemical composition of ambient aerosol was demonstrated as an important factor in component deposition, human health and visibility in urban regions (Shen et al., 2009). Ambient fine particle concentrations, especially the submicron fraction (particles having aerodynamic diameter < 1 ìm, PM1) that can easily penetrate into the alveolar region of the lungs. These studies also suggest that ambient particles of small sizes (particles having aerodynamic diameter < 2.5 ìm, PM2.5) are responsible for health effects in urban polluted areas because they act as carriers for toxicants and mutagenic components (Pope and Dockery, 2006). So far PM2.5 have been extensively measured and reported as majorly composed of sulfate (SO42-), nitrate (NO3-), organic carbon (OC) and elemental carbon (EC) (Brook et al., 1997). However, PM1 have not been extensively measured and few studies have reported enrichment of some trace elements (Na, K, Ca, Mg, Fe, Zn, Pb, Sn, As, Ag, Ti, Co, Cu, Cr etc.) in it. Several research studies have been carried on PM2.5 and very few studies have been carried out on PM1 around the world. In most of the studies PM mass was collected for some time period in a particular season or in different seasons over a year followed by quantitative chemical speciation in terms of elements, anions, organics etc. in order to identify major sources and their contributions. In a study carried out at Milan, Italy (Vecchi et al., 2004) a strong seasonal variation of PM1 and PM2.5 concentrations with the highest values during winter months (especially December, January and February) have been reported. In another study carried out in the urban city of Kaohsiung, Taiwan (Lee, 2002) it was shown that PM1 represents 50-70% of the PM10 mass and almost 80% of PM2.5 mass. In their study, it was also observed that winter time PM1 concentrations were marginally higher which can be attributed to poor ventilation, lower wind speed and mixing height.

Kanpur is one of the most polluted cities in India today. Kanpur’s climate can be characterized by a very hot and dry summer and very cold winter, the temperature

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during summer can go up to 45 °C and in winter goes below 5 °C. The city’s population is around 6 million and it is dangerously congested and overcrowded and due to the onset of leather industries pollution levels have risen dangerously high, according to the CPCB (central pollution control board) the annual average RSPM (respirable suspended particulate matter, particles having aerodynamic diameter < 10 ìm, PM10) concentration in the city is H”180 ìg/m3 (www.cpcb.nic.in) which is far more than the specified (60 ìg/m3) under the National Ambient Air Quality Standards (NAAQS) of CPCB. Alarming vehicular and population growth rate, frequent traffic jams and not much improvement in the number and condition of roads has resulted in a significant rise in the RSPM level of Kanpur. Thus, identification of the air pollution sources especially during the winter season is very important for the city of Kanpur.

Objectives

(a) To determine the variation in PM1 and PM2.5 mass concentration covering winter season.

(b) Chemical characterization of PM1 in terms of elements and anions and PM2.5 in terms of EC and OC analysis.

(c) Source apportionment of PM1 and PM2.5 using well known source apportionment and source identification tools like PMF, UNMIX and PCA.

Methodology

Sampling Site : Sampling is being carried out on a 12 m high building (Western lab extension, WLE) inside the IIT Kanpur campus. IIT Kanpur is an educational institute having residential campus having no commercial and industrial activities. The campus lies about 15 km north of city in the upwind direction with minimum emissions. Within the campus vehicular population mainly comprises of two wheelers and cars. The heavy- duty vehicle population is very low. It is relatively a background site compared to the heavily polluted Kanpur city center.

Aerosol sample collection : Two impactors designed for 1.0 μm and 2.5 μm (standardized against Aerodynamic particle sizer, APS, TSI Inc.) cut size are being operated at 10 and 15 lpm (controlled by needle valve + rotameter, calibrated using a mass flow meter) respectively. The impactors are made of aluminum developed in our lab at IIT Kanpur and evaluated in laboratory as well as in the field for the sampling of ambient particulate matter before final experiments (Gupta et al., 2009). Teflon filter papers with 46.2 mm diameter and 2 ìm pore size were used for PM1 collection and 47 mm Quartz filters were

used for PM2.5 collection. Sampling will be done for 10 h in day (7 am to 5 pm) and 10 h in night (8pm to 6 am) for 3 days in a week covering winter season (November to

February). The sampling for the month of Nov has already been completed.

Gravimetric Analysis : Each Teflon filter paper used for the sampling was pre-conditioned in a controlled environment at 25°C for 24 h before the sampling (Lee, 2002) and same procedure was followed for each filter after the sampling to avoid any error in calculation of PM1 mass due to presence of moisture. Each Quartz filter was pre-conditioned in furnace at 550°C for 12 h within an Al-pouch and then packed to remove the carbonaceous contamination. Each pre-conditioned filter and post-conditioned after sampling was then weighted thrice using Metler balance (APM 440, Metler, least count 10 ìg). 10% of the

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total numbers of the collected filters were kept as a blank and they were subjected to same procedure as the sampled filters.

Chemical Analysis : Elemental and anion analysis will be carried out for the particles collected on Teflon filters using ICP-OES (6300 Duo, Thermo Inc.) and IC (Metrohm) instruments. Whereas, EC/OC analysis will be carried out over particles collected over Quartz filters using Sunset, USA field instrument.

Results

The winter season variation of PM1 and PM2.5 mass concentration and composition will be investigated for the Kanpur city. The elemental and organic carbon contribution (EC and OC) will also be determined for PM2.5 in Quartz filters. Trace metals (Na, K, As, Ca, Cd, Co, Cr, Cu, Fe, Mg, Ni, Pb, Se, V, Zn, and Al) and anions (F-, Cl-, NO3-, SO4-2, and PO43-) measured for PM1 will be presented. The salient results from this study will be presented in the proposed paper presentation.

References

Brook, J.R., Dann, T.F. and Burnett, R.T., 1997. The relationship among TSP, PM10, PM2.5 and inorganic constituents of atmospheric particulate matter at multiple Canadian locations. J. Air & Waste Management Association 47, 2–19.

Gupta T, Chakraborty A and Ujinwal KK. Development and use of a sampler for collection and chemical characterization of submicron ambient aerosol in the Kanpur region. Aerosol and Air Quality Research, 2009 (submitted).

Lee, J.H., Jang, L., K. and Chung, Y.S. (2002). Characteristics of Trace Metals in Fine Ambient Particles in Korea. Project Committee Meeting and Conference of Project Participants and End Users, 11-15th Nov. 2002, Beijing, China.

Pope III, C. A. and Dockery, D. W., 2006. Health Effects of Fine Particulate Air Pollution: Lines that Connect.

J. Air & Waste Management 56:709–742.

Shen, Z., Cao, J., Tong, Z., Liu, S., Reddy, L.S.S., Han, Y., Zhang, T. and Zhou, J., 2009. Chemical Characteristics of Submicron Particles in winter in Xi’an. Aerosol and Air Quality Research, Vol. 9, No. 1, pp. 80-93.

Vecchi, R., Marcazzan, G., Valli, G., Ceriani, M. and Antoniazzi, C., 2004. The role of atmospheric dispersion in the seasonal variation of PM1and PM2.5 concentration and composition in the urban area of Milan (Italy). Atmospheric Environment, 38, 4437–4446.

www.cpcb.nic.in

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H–P–5

Impact of Anthropogenic Sources on Chemical Composition of Atmospheric Aerosols over Bay of Bengal

Bikkina Srinivas, M.M.Sarin and A.Kumar

Physical Research Laboratory, Navrangpura,Ahmedabad, India - 380009

Introduction

The long-range transport of atmospheric fine particulate matter, derived from natural and anthropogenic sources, has profound impact on the marine atmospheric boundary layer (MABL) and on subsequent deposition of chemical constituents across the air–sea interface. For open ocean regions, it is being increasingly recognized that atmospheric supply of trace metals (such as Fe) and nutrient species (NO3-, NH4+) can enhance the surface primary production, thus, leading to increased sequestration of atmospheric CO2. There have been very few systematic studies from the perspective of atmospheric transport of mineral dust and pollutants from south and south-east Asia to the MABL of Arabian Sea and Bay of Bengal (Lelieveld et al, 2001; Kumar et al., 2008a, b; Sudheer and Sarin, 2008). A recent study has projected a two-fold increase in the deposition of anthropogenic nitrogen species in the marine areas around south-east Asia (Duce et al., 2008). However, these studies emphasize the need for better characterization of chemical composition of aerosols within the MABL. As a part of national efforts (ICARB: Integrated Campaign of Aerosols and trace gasses Radiation Budget sponsored by ISRO-Geosphere Biosphere Programme), aerosol samples were collected from the MABL of Bay of Bengal in order to assess the impact of the long-range transport of anthropogenic species and heterogeneous phase chemistry.

Aerosol Sampling and Analysis

The size-segregated (PM2.5 & PM10) aerosols were collected (during 27th Dec’08 to 30th Jan’09) on Tissuquartz filters by simultaneously operating the two high-volume samplers (flow-rate: 1.13m3/min), setup on the upper-deck of ORV Sagar Kanya. A total of 64 samples were collected and analyzed for water-soluble ions (Cl-, NO3 , SO42- & Na+, NH4+,K+,Ca2+, Mg2+), carbonaceous aerosols (EC, OC), Crustal elements ( Fe, Al, Ca and Mg ) and combustion derived trace metals (Cd, Pb).

Results and Discussion

The mass concentrations of PM2.5 and PM10 during the ICARB campaign varied as 2.0 to 76.7 and 6.0 to108 μg.m-3, respectively. The average chemical composition of the two- size fractions is summarized in Fig1. Analysis of these results suggests that MABL of Bay of Bengal is significantly influenced by pollutants derived from combustion sources (fossil- fuel and biomass burning). The anthropogenic fraction of water-soluble ionic species (ANTH = NO3- + nss- SO42- + NH4+) is most abundant in both PM2.5 and PM10.

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Figure 1. Average chemical composition of PM2.5 & PM10 during ICARB Campaign. EC = Elemental Carbon, OM = Organic Matter (= Organic carbon * 1.6), ANTH = anthropogenic fraction of water-soluble ions (nss- SO42- + NO3- + NH4+)

The mass of carbonaceous species is the second most abundant fraction in PM2.5. Such an observation, together with OC/EC ratio of 2 to 3, emphasizes that chemical composition of fine fraction is dominated by emissions from fossil-fuel combustion sources. The temporal variability in OC/EC ratio in the two size fractions is presented in Fig 2. The impact of anthropogenic sources is further reflected from chloride depletion in sea-salts (NaCl), range: 39 to 100 % and 13 to 100% in PM2.5 and PM10, respectively. This is also supported by high concentrations and enrichment factors of combustion derived heavy metals such as Cd, Pb over Bay of Bengal.

Figure 2. Temporal variability of OC/EC ratio in PM2.5 and PM10

References

1)J. Lelieveld et al., 2001. The Indian Ocean Experiment: Widespread Air Pollution from South and Southeast Asia. Science, 9 February, 291: 1031-1036.

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2)R.A.Duce et al., 2008. Impacts of Atmospheric Anthropogenic Nitrogen on the Open Ocean. Science 16 May 2008 320: 893-897.

3)Kumar, A., Sudheer, A.K. and Sarin, M.M., 2008a. Chemical characteristics of aerosols in MABL of Bay of Bengal and Arabian Sea during spring inter-monsoon: a comparative study. July 2008. J. Earth Syst. Sci. 117 (S1), 325–332.

4)Kumar, A., Sarin, M.M. and Sudheer, A.K., 2008b. Mineral and anthropogenic aerosols in Arabian sea- atmospheric boundary layer during inter-monsoon: sources and spatial variability. Atmos. Environ. 42, 5169–5181. doi:10.1016/j.atmosenv.2008.03.004.

5)A.K.Sudheer and M.M.Sarin, 2008. Carbonaceous aerosols in MABL of Bay of Bengal: Influence of continental outflow. Atmos. Environ. 42, 4089–4100.

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H–P–6

Distibution, Composition and Sources of Carbons and Polycycylic Aromatic Hydrocarbons in Ambient Particulates of Raipur City

K. S. Patel1, Y. Nayak1, N. K. Jaiswal1, H. Saathoff2, T. Leisner2, L. Jutta3 and M. Georg3

1School of Studies in Chemistry, Pt. Ravishankar Shukla University, Raipur, CG, India

2Institute for Meteorology and Climate Research (IMK), Atmospheric Aerosol Research Division (IMK- AAF), Forschungszentrum Karlsruhe, Germany

3Helmholtz Zentrum Muenchen, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany

The elemental carbon (EC), organic carbon (OC) and polycyclic aromatic hydrocarbons (PAH) associated to the ambient particulates are of environmental and health interests.

Thirteen PAH i.e. phenanthrene (Phe), anthracene (Ant), fluoranthene (Fla), pyrene (Pyr), benz(a)anthracene (Baa), chrysene (Cry), benzo(b)fluoranthene (Bbf), benzo(k)fluoranthene (Bkf), benzo(a)pyrene (Bap), dibenz(ah)anthracene (Dba), benzo(ghi)perylene, indeno(1,2,3-cd)pyrene (Ind) and coronene were reported as toxic air pollutants. They are emitted largely by burning of biomass, coal, gasoline, residue, etc. in the environment. In Chhattisgarh region of the country, a huge amount of coal is burnt by various industries and thermal power plants. In the present work, the EC, OC and PAH associated the particulate matter (PM) of Raipur city are investigated. The PM was collected over the quartz filter paper and they were quantified by using the appropriate techniques i.e. thermal analyzer and HPLC-MS. The annual mean concentration of the EC and OC in the coarse particulates (PM10) is 9.3±5.0 and 8.9±5.0, respectively. The annual (May,2007 – May,2008) concentration of EC, OC and PAH in the ambient air is ranged from 4.8 – 60.8 μg m-3, 5.0 – 53.4 μg m-3 and 50 – 182 ng m-3 with mean value of 26.4±11.5 μg m-3, 22.6±9.3 μg m-3 and 112±27 ng m-3, respectively. The speciation, variations and sources of EC, OC and PAH are described.

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H–P–7

Role of Organic Aerosols in an Urban Atmosphere

Kirpa Ram1#, M. M. Sarin1 and S.N. Tripathi2

1Physical Research Laboratory, Navarangpura, Ahmedabad,India-380009

2Department of Civil Engineering, Indian Institute of Technology, Kanpur

E-mail: kirpa@prl.res.in

Introduction

Aerosols derived from natural and anthropogenic emission sources significantly affect the air-quality, visibility and atmospheric chemistry on a regional scale. In an urban atmosphere, PM2.5 accounts for ~60-70% of the PM10 mass of which 30-60% is contributed by organic aerosols 1-3. Organic aerosols represent a large variety of compounds (aliphatic, aromatic compounds and acids) that act as cloud condensation nuclei (CCN) depending on their chemical composition and water-soluble components 4; thus, leading to indirect climatic effect through changes in the cloud-albedo and precipitation efficiency 5. The emissions from biomass burning and fossil-fuel produce primary elemental carbon (EC) and organic carbon (OC). However, a significant fraction of OC, referred as secondary organic carbon (SOC), is formed by the oxidation of gas-phase precursors, like volatile organic compounds (VOCs) in the atmosphere. Most of the SOC formed in the atmosphere, through oxidation processes, is soluble in water and water-soluble organic carbon (WSOC) accounts for ~30-60% of the OC 3. Thus, chemical characterization of organic aerosols for WSOC is essential. This study presents measurements of OC, EC and WSOC based on the sampling of PM2.5 and PM10 from a typical urban site (Kanpur) in the Indo-Gangetic Plain (IGP). The day (n=20) and night (n=14) samples were collected to infer the effect of photochemical activity on the formation of secondary organic aerosols (SOA) in an urban atmosphere.

Aerosol Sampling and Experimental Method

Aerosol samples (PM2.5 and PM10; particulate matter less than 2.5 mm and 10 mm aerodyne diameter respectively) were collected during 19-30th Oct 2008 by simultaneously operating two high-volume samplers (Thermo Andersen; USA) for ~6-8 hrs (at flow rate 1.1±0.1 m3 min-1) and filtering the ambient air through pre-combusted (at 650 °C for ~4 hrs) tissuquartz filters (PALLFLEXTM; size: 20.0×25.4 cm2).

The particulate matter (PM) abundance (in mg m-3) was obtained by dividing the sample weight (the difference between sample and blank filter weights) with the volume of air sampled (typical volume 500-600 m3). The abundances of carbonaceous species (OC and EC) were measured on the EC-OC analyzer (Sunset Laboratory, Forest Grove, OR) using thermo-optical transmittance (TOT) protocol as described in NIOSH-5040 protocol 2,3,6. For the WSOC measurement in aerosols, one-fourth filter (~105 cm2 area) was soaked in 50 ml de-ionized water (resistivity: 18.2 MW cm) and ultrasonicated for ~8 hrs. The

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resulting water-extract was transferred to pre-cleaned glass vials and analyzed for the WSOC content using a total organic carbon (TOC) analyzer (Shimadzu, model TOC- 5000A) 3.

Results and Discussion

The PM2.5 and PM10 mass varied from 74 to 329 mg m-3 and 107 to 396 mg m-3, respectively for the samples collected during the study period. The average PM2.5/PM10 mass ratio, 0.65±0.10 (range: 0.46 to 0.86), suggest the dominance of fine-mode aerosols at an urban location (Kanpur). In both the sizes, organic aerosols dominate the PM mass and contribute ~50% of the PM2.5 and ~40% of the PM10 mass. The water-soluble inorganic species (WSIS) constitute ~15% of the total aerosol mass in both sizes. The PM abundances increased by ~30% (in both sizes) for the samples collected during nighttime. The increase in PM abundances for the night samples can be attributed to: 1) the increase in the source strength of organic species 2) an efficient trapping of aerosols due to decrease in the boundary layer height (BLH) and 3) the increase in the abundances of WSIS and mineral aerosols. However, the WSIS contribution (to PM mass) does not show any increase in the night samples and is similar to that for the day samples (~15% of the PM mass). Since, the abundances of WSIS remain the same during day and nighttime; the increase in PM abundances (during nighttime) is attributed to the increased abundances of organic aerosols. The increase in the source strength of organic species is further supported by the relative increase in K+ concentration (a tracer of biomass burning emission) in the night samples. Furthermore, the lower OC/EC ratios in night samples (Fig. 1), compared to those for day samples, also suggest enhanced vehicular emissions during nighttime.

The abundances of OC in PM2.5 varied from 21 to 100 mgC m-3 (average: 47±21 mgC m- 3; ~29% of PM2.5 mass) whereas those varied from 24 to 132 mgC m-3 (average: 57±27

mgC m-3; ~24% of PM10 mass) in PM10 aerosol samples. The abundances of EC varied from 4.2 to 16.3 mgC m-3 (average: 7.7±2.9 mgC m-3; ~5% of PM2.5 mass) in PM2.5 and those varied from 4.6 to 22.6 mgC m-3 (average: 9.5±5.7 mgC m-3; ~4% of PM10 mass) in PM10 aerosols. Both OC and EC abundances dominate in fine-mode and the average mass ratios (of their abundances in PM2.5 to that in PM10) are ~76 and 79% for OC and EC, respectively. On average, total carbonaceous aerosols (TCA=1.6*OC+EC) account for ~50%

of the PM2.5 mass and ~40% of the PM10 mass. The abundances of OC and EC (in PM2.5 and PM10 both) were significantly higher in the night samples compared to those in the day samples (Fig.1).

The WSOC abundances in aerosol samples varied from 12.2 to 71.6 mgC m-3 (average:

31.6±15.3 mgC m-3) and 14.4 to 73.5 mgC m-3 (average: 32.9±13.8 mgC m-3) in PM2.5 and PM10 respectively. Thus, on average, WSOC constitute ~20 and 15% of the aerosol mass

in PM2.5 and PM10; and ~95% of the WSOC are found in PM2.5 aerosols. The WSOC/OC ratios are similar in PM2.5 and PM10 samples (Fig. 1). However, the WSOC/OC ratios are

relatively lower for the night samples. The WSOC/OC ratio in day (night) samples varies from 0.50 to 0.82 (0.37 to 0.55) in PM2.5 and from 0.44 to 0.90 (0.36 to 0.58) in PM10 samples. The WSOC/OC ratios at Kanpur (observed in this study) are higher than those reported for the urban sampling sites in the IGP during Dec 2004 land-campaign 3. The average WSOC/OC ratios for day and night samples are 0.66±0.10 and 0.47±0.07 (for PM2.5); 0.67±0.15 and 0.46±0.07 (for PM10) respectively (Fig. 1). Furthermore, the average WSOC/OC ratio for the samples collected during daytime are significantly higher than

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that for the night samples and thus, provide a direct evidence for the enhanced secondary aerosol formation (SOA). The enhanced SOA formation and hygroscopic nature of the WSOC may have a significant impact on hydrological cycle (through the cloud-condensation nucleation processes), reduction in the visibility and foggy-hazy weather formation over the IGP during wintertime.

Figure 1. The average abundances of total aerosol mass, OC, EC, WSOC and respective ratios at Kanpur during the sampling period

References

1.Fuzzi, S. et al., Atmospheric Chemistry and Physics 6, 2017 (2006).

2.Rengarajan, R., Sarin, M. M., and Sudheer, A. K., Journal of Geophysical Research D: Atmospheres 112 (23), doi:10.1029/2006JD008150 (2007).

3.Ram, K. and Sarin, M. M., Journal of Aerosol Science, doi:10.1016/j.jaerosci.2009.11.004 (2009).

4.Sun, J. and Ariya, P. A., Atmospheric Environment 40 (5), 795 (2006).

5.Haywood, J. and Boucher, O., Reviews of Geophysics 38 (4), 513 (2000).

6.Ram, K., Sarin, M. M., and Hegde, P., Atmospheric Environment 42 (28), 6785 (2008).

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