IASTA-2010

H–P–8

Assessment of Ambient Air Quality of Bangalore City for 2006-2008

Nishi Srivastava1* and S.K. Satheesh1,2

1Centre for Atmospheric and Oceanic Science, Indian Institute of Science, Bangalore, India.

2Divecha Centre for Climate Change, Indian Institute of Science, Bangalore, India.

*For correspondence: nishi@caos.iisc.ernet.in

Urbanization is fastest growing problem in whole world and India is no exception of this. In last few decades rapid growth in all metropolitan cities has been observed.

Urbanization is root of several problems and it has significant impact on human health. One of the most serious problems due to urbanization is air pollution. Clean air is fundamental requirement for life. However, it is becoming a dream day by day. By definition, air pollution is declination of air purity which can occur naturally or anthropogenically (Kaufman et al., 2002), but in cities it is mainly due to anthropogenic activities. Main processes contributing to air pollution are anthropogenic injection of chemicals, particulate matter or biological materials into the atmosphere, which causes harm and discomfort to humans and other living organisms and damages the environment (Brulfert et al., 2005). Main air pollutants are oxides of nitrogen (NOx), carbon monoxide (CO), suspended particulate matter (SPM), respirable suspended particulate matter (RSPM), hydrocarbon (HCs), lead (Pb), sulphur dioxide (SO2), carbon dioxide (CO2), methane

Figure 1. Variaiton of monthly variation of pollutants over Bangalore for study period (2006-2008)

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(CH4), Ozone (O3) and volatile organic carbon (VOC). Long term exposure to these pollutants affects lung functioning, respiratory system, increases frequency of asthma attack and sometime even causes pre-mature deaths (TERI, 2001; Maynard, 2004). In order to reduce air pollution, air quality standards have been introduced. But it does not mean that below this limit there will be no adverse effect (WHO 2000a). In the present work, we have analyzed the air quality status of Bangalore, one of the fastest growing cities in India, for three consecutive years, 2006-2008. Ambient air pollution level was monitored for study period with respect to four pollutants (NO2, SO2, SPM, and RSPM). Gaseous pollutants, SO2 and NO2 were observed within residential limits while SPM and RSPM (particulates matter) concentrations were occasionally exceeded permissible

Figure 2. (a) Variation of monthly AQI sub-index over Bangalore for each pollutants for study period 2006- 2008 (b) Variation of monthly AQI over Bangalore for 2006-2008

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residential limits except monsoon months (Fig. 1). Inhalation of polluted air can cause several health problems; hence it was useful to estimate the minimum pollution level of ambient air. Study shows that NO2 and SPM background pollution level were unhealthy for sensitive group while that for SO2 and RSPM were well within the allowed limits. When we examined the ambient pollutants concentration with respect to residential limits, it shows that about 55% of observations were higher than prescribed limits.

To make air pollution problem easily understandable by general public it was necessary to make it more representable. Pollutant concentration does not represent severity of pollution properly. To make this concept easily assessable, scientists have defined a new parameter to represent air pollution and term coined for it, “Air Quality Index (AQI)”. AQI includes sub indices for O3, PM, CO, SO2 and NO2, which relates ambient pollutant concentration to index values on a scale from 0-500. In general this health index has the following description: “Good (0-100)”, “Moderate (101-200)”, “Poor (201-300)”, Very Poor (301-400)” and “Severe (401-500)” (Sharma et al. 2001). In simple words, AQI can be explained as a number which reflects effects of air pollution on human health (Ott, 1976; Bortnick et. al., 2002). To examine severity of pollution in Bangalore, we have calculated Air Quality Index (AQI) for study period with respect to all four pollutants (Fig. 2). SPM AQI sub-indices indicate the frequent episode of poor quality air. Hence Bangalore city seems to be polluted because of high concentration of suspended particulate matter. AQI calculations also show that ~52% time ambient air quality was moderate to very poor (~24% moderate, ~22% poor and ~6% very poor). Bangalore air is unhealthy for all groups for about 50% of time and for sensitive group throughout the year. Decreasing trend has been observed in gaseous air pollutant concentration but still it is higher for sensitive group. High particulate matter concentration is also a serious health issue for all groups of people.

References

Bortnick, S.M., Coutant, B.W. and Eberly. S.I. ,2002, Using Continuous PM2.5 Monitoring Data to Report an Air Quality Index. J. Air Waste Manage. Assoc. 52: 104-112

Brulfert, G.T., Cholleta, J.-P., Jouveb, B., Villard, H., 2005., Atmospheric emission inventory of the Maurienne valley for an atmospheric numerical model. Science of the Total Environment 349, 232–248

Kaufman, Y.J., Tanre, D., Boucher, O., 2002. A satellite view of aerosols in climate systems. Nature 419, 215– 223.

Maynard, R., 2004. Key airborne pollutants—the impact on health. Science of the Total Environment 334–335, 9– 13

Ott, W.R., Hunt, Jr., W.F., 1976. A quantitative evaluation of the pollutant standards index. Journal of Air- Pollution Control Association 26, 1051Ð1054.

Sharma, M., Maheshwari, M., Pandey, R., 2001. Development of air quality index for data interpretation and public information. Department of Civil Engineering, IIT Kanpur, Report submitted to CPCB, Delhi

TERI, 2001. Review of past and on-going work on urban air quality in India. Report submitted to the World Bank, December, Tata Energy Research Institute, 2001EE41.

WHO (World Health Organisation), 2000a. Air Quality Guidelines for Europe, second edition. WHO Regional Publications, European Series, No. 91.

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H–P–9

Wet Deposition Chemistry over West Coast of India

P Hegde

Space Physics Laboratory, Vikram Sarabhai Space Centre, Trivandrum – Kerala

ABSTRACT : Wet-only rainwater samples were collected from seven stations during the southwest monsoon to determine pH, electrical conductivity and major ionic concentrations in view of increasing urbanization and industrialization in the study area. The pH was weakly acidic to nearly neutral at almost all stations. Na+ and Cl- concentrations were similar to tropical and temperate areas, while Ca2+, Mg2+ and K+ were significantly higher in the study area implying an additional input from the continental source. Furthermore, Ca2+/Na+, Mg2+/ Na+, K+/Na+ and Cl-/Na+ ratios of rainwater are significantly higher than those for the average seawater, supporting this interpretation.

Introduction

Atmosphere is an important source of chemical elements to terrestrial, aquatic and marine environments. Due to increase in anthropogenic activities, the health of the environment is deteriorating in terms of increase in different types of contaminants and acidic species. Precipitation is a major removal pathway of selected atmospheric species (aerosols and trace gases) over several regions of the world. Thus, a systematic study of the chemical composition of precipitation helps to probe the chemical state of the

atmosphere in which rain-bearing clouds have formed.

…As there is no report on the chemistry of rainwater around the study area, this work has been taken up to trace sources of major ions and also to determine pH and electric conductivity of rainwater.

The study area includes seven monitoring stations in the southwest coast of India (Fig.1). The rainfall rate increases from 200 to 500 cm/yr from coast to Western Ghats. About 85% of the total annual rainfall occurs during the southwest monsoon season. Humidity is particularly high during monsoon season. Wind velocity during southwest monsoon is higher than that during northeast monsoon. During the southwest monsoon, wind direction is westerly through southwesterly, where as during northeast monsoon, it is blowing from east through northeast.

Materials and Methods

In order to collect rainwater samples, polyethylene funnel-type of collectors (755 sq. cm) connected to the pre-cleaned polyethylene cans were installed at seven monitoring stations on terrace of buildings of height about 10-15 m above the ground level (Fig. 1). Event-wise wet-only rainwater samples were collected from 1st August to 4th November 1999. Physico-chemical parameters were determined for both anions and cations by Ion Chromatography and AAS/ICP-AES respectively, as per standard procedures (APHA, 1995).

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Results and Discussion

Summary statistics of the data of rainfall, major ions, pH and conductivity of rainwater samples collected at different monitoring stations are given in Table 1. The rainfall in the study area varied from 5.15 cm to 6.49 cm during sampling period.

Figure 1. Map of the study area depicting the sample monitoring stations.

The pH of rainwater samples was weakly acidic to nearly neutral (Table 1). It did not vary much in different monitoring stations as supported by a low range and standard deviation. However, few occasions of low pH of rainwater were recorded around Mangalore Refineries and Petrochemicals Limited (RN 6), heavy traffic density zone (RN 3) and city residential area (RN 4) indicate acidification. This is due to an increase in the combustion of fossil fuels because of road traffic and small electric power generators used in the city areas, smelting of iron ore and localized biomass (garbage) burning. Nevertheless, the pH of rainwater was nearly neutral at same sampling stations during the rest of the sampling periods, particularly during the southwest monsoon season. The pH value of rainwater in the study area was almost similar to other cities of India, but considerably higher than that for the developed countries (Table 1).

The conductivity in the study area was fairly uniform and it ranged from 20.11 to 39.77 mS/cm. It was relatively low in pristine areas like stations RN 1 and RN 2 as compared to other strongly human influenced stations. Conductivity of rainwater samples in the study area was comparable to that in the other coastal cities like Goa, but high as compared to Delhi and Pune (Table 1) due to the deposition of sea salt in the coastal area.

The mean concentration of Cl- varied from 4.61mg/l to 8.67mg/l which were higher in the study region than those observed in Goa, Pune and Delhi (4.78, 1.76 and 0.1 mg/l respectively). Usually the Cl- ion is abundant (10 to 15 mg/l) in coastal rainwater as compared to that in interior continental areas (0.15 - 0.2 mg/l) because of the deposition of sea salt in coastal areas (Berner and Berner, 1987). Furthermore, Cl-/Na+ ratios are particularly high (4.68 to 11.59) relative to that for seawater (1.0 to 1.8), suggesting anthropogenic input of Cl- in the study area. The probable sources could be expected from combustion of fossil fuels, biomass (garbage and hospital wastes) burning, automobile

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Table 1. Rainfall (cm), conductivity (mS/cm) and major ion concentrations (mg/l) in rainwater samples of the study area, other parts of India (Parashar et al.,1996) and the world (Berner and Berner, 1987).

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exhaust (Paciga and Jervis, 1976, Berner and Berner, 1987) and fertilizers and chemicals industry.

Magnesium, Ca2+ and K+ are the next dominant ions in rainwater samples of the study area. They varied from the mean values of 6.02, 1.73 and 0.16 to 8.15, 2.47 and 0.59 mg/ l respectively. These ions normalised to Na+ are particularly higher as compared to those for the average seawater (Table 2). All these observations suggest that terrestrially dominated ions are more in the lower atmosphere in the area of investigation and are brought back to the ground during precipitation. In contrast, these ionic ratios to Na+ for south Atlantic rainwater were nearly the same as those of the average seawater (Stallard and Edmond, 1981).

Table 2. Major ions normalised to Na+ in rainwater samples

Ammonium is also an important ion in the study area not only because of chemicals and fertilizers industry, but also due to the influence of biomass. Ammonium concentrations in rainwater samples (0.33 to 0.79 mg/l) were by and large within the range for other Indian cities (0.15 - 0.51 mg/l) and different parts of the world (0.01 to 1.0 mg/l; Berner and Berner 1987). The emission of ammonia is particularly high in densely populated tropical and temperate countries as compared to the cold parts of the world (Adams et al., 1999).

The NO3- ion in rainwater samples was low and did not show much variation as compared to those obtained in the other places of India and rest of the world (Table 1). This may be due to heavy rainfall during the southwest monsoon that can dilute the excess of contaminants in the atmosphere (Saxena et al 1996).

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References

Adams, P.J., J.H. Seinfeld, and D.M. Koh, 1999: Global concentrations of tropospheric sulfate, nitrate, and ammonium aerosol simulated in a general circulation model. . J. Geophys. Res., 104 (D11): 13791- 13,823.

APHA, 1995: Standard Methods for the Examination of Water and Waste Water, edited by A.D. Eaton, L.S. Clesceri and A.E. Greenberg, pp. I-47, 19th edition, Washington D.C.

Berner, E.K. and R.A. Berner, 1987: The Global Water Cycle: Geochemistry and Environment. Prentice-Hall Inc., N.J., pp. 397.

Paciga, J.J. and R.E. Jervis, 1976: Multi element size characterization of urban aerosols. Environ. Sci. Technol. 20: 1143-1145.

Parashar, D.C., L. Granat, U.C. Kulshrestha, A.G. Pillai, M.S. Naik, G.A. Momin, P.S.P. Rao, P.D. Safai, L.T. Khemani, S.W.A. Naqvi, P.V. Narverkar, K.B. Thapa and H. Rodhe: 1996. Chemical composition of precipitation in India and Nepal: A preliminary report on an Indo-Swedish project on Atmospheric Chemistry. Report No. CM-90, Department of Meteorology, Stockholm University, International Meteorological Institute, Stockholm, pp. 27.

Stallard, R.F. and J.M. Edmond, 1981: Chemistry of the Amazon, precipitation chemistry and the marine contribution to the dissolved load at the time of peak discharge. J. Geophys. Res., 86 (C10):9844-9858.

Saxena A, Kulshrestha U C., Kumar N, Kumari K M and Srivastava S S (1996). Characterization of precipitation at Agra. Atmospheric Environment, 30, 3405-3412.

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H–P–10

Surface Ozone Episodes in the Northwestern Indian Himalayan Region: A Case study of Mohal-Kullu in Himachal Pradesh, India

Priyanka Sharma, Jagdish C. Kuniyal*, Kesar Chand

and Harinder K. Thakur

G.B. Pant Institute of Himalayan Environment and Development,

Himachal Unit, Mohal-Kullu, (H.P.), India

*Corresponding author : E-mails: jckuniyal@rediffmail.com / kuniyaljc@yahoo.com

Introduction

Surface ozone is a phytoxic pollutant generated due to anthropogenic emissions in presence of sunlight and nitrogen dioxide concentrations (USEPA, 1996). The stratospheric ozone is good to mankind since it absorbs ultraviolet rays coming to the Earth’s surface. However, the tropospheric ozone is bad since it is being created due to biotic interferences in the certain ecosystem. The surface ozone is again bad since it is being created on the Earth’s surface which adversely affects the human populations with a variety of respiratory, skin and other diseases. Similarly, due to surface ozone exposure above 50 ppb for duration of more than 1 h, it starts to hamper the growth of plants and damages its stomata with yellowing the plants and hence deteriorating its growth and productivity (Aneja et al., 1991). It is therefore urgent to observe surface ozone episodes in the Himalayan ecosystem characteristic for topographically very fragile and ecologically very delicate. Being a greenhouse gas, ozone plays a key role in controlling the chemistry and climate of the tropical troposphere (Crutzen, 1988; Thompson et al., 1997). Atmospheric ozone plays an important role in the physio-chemical processes of the troposphere but it has also strong oxidant properties, which at certain level may cause damage to humans, animals and vegetation (Bates, 1994; Finlayson-Pitts and Pitts, 1997). In the lower troposphere, ozone is mainly formed by an action of U.V. light from the sun on nitrogen oxides, and the ozone level is significantly influenced by meteorological conditions, such as solar radiation, temperature, precipitation, wind speed, wind direction, which could

affect ozone formation, its accumulation, and transport (Thompson et al., 2001).

Experimental site and Methodology

The observations are carried out at Mohal (1154 m), 5 km south to Kullu town. The sampling site is located in the campus of G.B. Pant Institute of Himalayan Environment and Development, Himachal Unit, Mohal-Kullu (H.P.). The distance of the sampling site from National Highway (NH)-21 is about 200 m.

The Ozone Analyzer (Monitor Europe, ML9811) is used to monitor surface ozone (O3) concentration in ambient air on continuous basis to find the diurnal mean values. Ozone

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exhibits strong absorption in the ultraviolet spectrum at 254 nanometre (nm). The Analyzer can accurately measure ozone concentration less than 0.5 ppb. A stream switched, single beam photometer serves as the basis for the Analyzer. A mercury vapour lamp is used as the source while a solar blind vacuum photodiode as the detector. A glass tube serves as an absorption cell. During the reference cycle of the stream switching process, air is drawn into the photometer through a scrubber which removes all ozone and the light intensity (I0).The valve is then switched to allow ambient air to fill the cell. During this cycle of measurement, the light intensity (I) is determined through which ozone concentration is obtained.

Results and Discussion

The observation on surface ozone during four years (2004 - 2007) showed the maximum hourly concentration with 95.19 ppb at 1700 hr IST on 10 June, 2007 (Kuniyal et al. 2007; Fig.1a). This concentration was followed by 86.78 ppb at 2000 hr IST on 26 April, 2004 and 84.21 ppb at 1600 hr IST on 22 June, 2006. Temperature has a direct link with the increasing concentrations of surface ozone (Fig.1b). The monthly maximum value of surface ozone was observed 37.5±5.8 ppb on May 2004 (Fig.1c). The seasonal variations of O3 concentration on monthly mean basis has shown maximum values 33.69±1.2 ppb during summer 2007 (Fig.1d). From the Fig.1d, summer is the season in which the ozone concentration was maximum in all the four years.

Surface ozone concentrations were noted to be high when NO2 increases due to vehicular emissions. In summer peak tourist season in Kullu-Manali hill spots, surface ozone remains

Figure 1. Surface ozone concentrations at Mohal-Kullu in Himachal Pradesh: (a) daily, (b) diurnal, (c) monthly, and (d) seasonal

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high. In presence of high temperature, photo-oxidation process during this time is greatly favoured (Kuniyal et al. 2003; Kuniyal et al. 2004; Gajananda et al. 2005; Kuniyal and Vishvakarma, 2006). At contrary, lowest concentration of surface ozone was measured when rainfall and humidity was maximum.

Using a back-trajectory model popularly known as Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) and Total Ozone Mapping Spectrometer (TOMS) and Aura Ozone monitoring Instrument (OMI) satellite imagery, the ozone episodes analyzed in relation to the present study region—Mohal during 2004-2007 (Fig.2). In April 2004, there were 65 hours within 16 days when surface ozone remained e”50ppb. Interestingly, surface ozone episodes were traced e”75ppb for 14 hours within 3 days in April 2004. Based on hourly maximum value of surface ozone, surface ozone concentrations remained up to 86.2 ppb; while its daily maximum value on April 27, 2004 was 53 ppb. April was the month when it could be considered one of the most polluted months of the year. Such ozone episodes from April 25 to 27, 2004 were directly related to long range transport sources through air masses. The relation of surface ozone between ground based measurements and satellite based TOMS was established. This indicates that besides having local determinants, there is a strong role of long range transport sources from outside the regions dominating with higher concentrations of columnar ozone. Surface ozone e” 50 ppb during 45 hours within 6 days were observed during June 2004. This value in this month was followed by July having period of 80 hours in14 days.

In the following year 2005, maximum hours of surface ozone concentrations e” 50ppb were noted to be for a resident period of about 38 hrs within 12 days in April and 24 hrs within 5 days in May. The maximum hourly average value of surface ozone stood to be 67.3 ppb on May 6, 2005; while the maximum daily average value remained 39±2.6 ppb on May 8, 2005, 36±3.4 ppb on May 6 and 36±3.2 ppb on May 7, 2005. Based on a comparative study between OMI satellite imagery for columnar ozone concentration and

Figure 2. Satellite Imageries and HYSPLIT Back trajectories during ozone episodes days at Mohal

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HYSPLIT back trajectories for May 8, it is well proved that its sources are mainly from long range transport sources outside the region.

In 2006, maximum hours of high concentration of surface ozone = 50 ppb remained for 172 hrs within 27 days in April, 89 hours within 12 days in May and 76 hours within 10 days in June. Such episodes remained =75 ppb for 8 hrs during 4 days in April and 1 hr in May and 6 hrs in June in one day. Maximum hourly average value of ozone stood to be 84.2 ppb on June 22, 2006 while daily maximum value of ozone remained 46±3.8 ppb on May 28, 2006 followed by 45±5.6 ppb on June 22 and 44 ±2.7ppb on April 17.

It was June 22, 2006 which was most polluted day of the year. Month wise if we observe the highest values, June was considered to be most polluted month of the year 2006. When five days back trajectories were plotted for June 22, 2006, the long range transport pollutant sources were identified from other polluted regions. However, maximum concentration of ozone = 50 ppb in 2007 showed 91 hrs within 21 days in April, 126 hrs within 17 days in May and 174 hrs within 23 days in June. Surface ozone episodes =75ppb continued for 2 hrs during one day in April, 15 hrs during 6 days in May and 12 hrs for 3 days in June. Maximum hourly value of surface ozone observed as 95.2 ppb on June 10, 2007 while the daily maximum was 56±5.2 ppb on the same day.

Conclusions

The concentration of ozone within permissible limit is set by USEPA’s standard. In all four years, the concentration of ozone was maximum in summer season. The high frequency of this type of air mass in summer causes the fact that there is a common seasonal characteristic of surface ozone. The maximum concentration of surface ozone was observed 95.19 ppb at 1700 hr IST on 10 June, 2007. The diurnal variation in ozone shows high concentration during day time and low concentration during late night and early morning. Local sources make a great contribution, but long range transport sources also play a very important role in seasonal behavior of surface ozone.

Acknowledgement

The authors are heartily thankful to the Director, G.B. Pant Institute of Himalayan Environment and Development, Kosi-Katarmal, Almora (Uttarakhand) for providing facilities in the Himachal Unit of Institute.

References

Aneja, V.P., Businger S., Li, Z., Claiborn, C.S. and Murthy, A. (1991) Ozone climatology at high elevations in the southern Appalachians, J. Geophysical Res. (USA), 96:1007.

Bates, D. (1994) The effects of ozone on plants and people. In: Calvert, J. (ed.) Chemistry of the Atmosphere: Its impact on global change; Blackwell Scientific Publications, pp.239-244.

Thompson, M.L., Reynolds J., Cox, LH, Guttorp, P. and Sampson, P.D. (2001) A review of statistical methods for the meteorological adjustment of Tropospheric ozone. Atmos. Environ. 35: 617-630.

Crutzen, P.J., (1988) Tropospheic Ozone: An overview. In: Isaksen, I.S.A. (ed.) Tropospheric Ozone, pp. 3-32.

Thompson, A. M., Tao, W.K., Pickerring, K.E., Scala, J.R., Simpson, J. (1997) Tropical deep convection and ozone formation, Bull. Am. Meteorol. Soc.78: 1043-1054.

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Kuniyal, J.C., Rao, P.S.P., Momin, G.A., Safai, P.D., Tiwari, S., Ali, K. (2007) Trace gases behaviour in sensitive areas of the northwestern Himalaya: A case study of Kullu-Manali tourist complex, India, Journal of Radio & Space Physics, 36(3): 197-203.

Gajananda, Kh., Kuniyal, J.C., Momin, G.A., Rao, P.S.P., Safai, P.D., Tiwari, S. and Ali, K. (2005) Trend of atmospheric aerosols over the North Western Himalayan Region, India, Atmos. Environ. 39(27): 4817- 4825.

Kuniyal, J.C. and Vishvakarma, S.C.R. (2006) Changing behaviour of ambient air quality and surface ozone in hill spots: A case study of Kullu-Manali Tourist complex (KMTC), northwestern Himalaya (2003-2005). Final Technical Report submitted to DST, Govt. of India, New Delhi, pp. 1-36.

Kuniyal, J.C., Jain, A.P. and Shannigrahi, A.S. (2003) Environmental impacts of tourism in Kullu-Manali complex in North Western Himalaya, India. Part 1: The Adverse Impacts. International Journal of Fieldwork Studies 1(1), http://www.virtualmontana.org/ejournal/vol 1(1)/tourism.htm.

Kuniyal, J.C., Vishvakarma, S.C.R., Badola, H.K. and Jain, A.P. (2004) Tourism in Kullu Valley: An Environmental Assessment, Bishen Singh Mahendra Pal Singh, Dehradun, pp.1-210.

USEPA (1996) Air quality criteria for ozone and related photochemical oxidants. U.S. EPA, Research Triangle Park, NC EPA Report No. EPA/600/P-93/00aF, Vol.II, pp.5-85.

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H–P–11

Physical and Chemical Characteristics of PM10 and PM2.5 at

Delhi

S. Tiwari1, Atul K. Srivastava1, D. S. Bisht1 and Manoj K. Srivastava2

1 Indian Institute of Tropical Meteorology, Pune, India

2 Department of Geophysics,Banaras Hindu University, Varanasi, India

Introduction

The concentration of aerosol particles in the troposphere has increased significantly over the last 150 years (Lavanchy et al. 1999), and may increase further as developing countries grow in population and industries. There has been mounting evidence of the significance of both natural and anthropogenic origin of aerosols, particularly in context to the climate change and health effect (Charlson et al. 1992, Hansen et al. 1997). The size distribution and chemical composition of aerosols is of crucial importance to understand atmospheric processes such as radiative transfer, cloud droplet nucleating ability, acidification, precipitation chemistry and dry deposition. Fast growth in industries, vehicles, populations, anthropogenic activities caused higher levels of aerosol pollutants in the megacities and of most of the rapidly developing countries in Asia (Menon et al. 2002; Beegum et al. 2009; Tiwari et al. 2008,). The chemical composition of these aerosols highly depends on the source regions, which changes with the meteorological conditions in the course of a year; and can be used to characterize air masses coming from different source regions (Gabriel et al. 2002). Some earlier studies have reported chemical composition of total suspended particulates in the Indian region (Kulshrestha et al. 1998; Tiwari et al. 2008, Safai et al. 2007; Beegum et al. 2009). However, the sparse data on chemical characteristics of particulate matters (PM10 and PM2.5----) are available over Delhi. In view of the above importance, the characteristics of the surface aerosol measurements were carried out at New Delhi, India. However, present study delineates the physical and chemical characteristics of the PM to understand broadly their significance in consideration

to local or regional climate system.

Experimental Site

PM10 and PM2.5 aerosol sampling was conducted inside the campus of the Indian Institute of Tropical Meteorology - New Delhi Branch, (28.63oN, 77.18oE), during January to December 2007, except monsoon due to frequent rain and high humid condition, on the rooftop of the building (~15 m above the ground level). Sampling of aerosol was carried out using single stage PM10 and PM2.5 aerosol samplers, which provides information about aerosol mass concentrations of sizes up to 10 μm and 2.5 μm, respectively. Both aerosol samples were collected once in a week on Whatmann, Teflon Micro fibre filter papers (2μm PTFE) of the size 46.2mm using APM 550 and APM 541 samplers (Envirotech Pvt. Ltd., India) for PM2.5 and PM10, respectively. The sampling cycle was 24 hrs with a flow rate of one cubic meter per hour collecting sufficient mass of aerosols. The particle

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concentrations were determined gravimetrically through the difference in their weights before and after the sampling.

One fourth sample filters were extracted with ultrapure water (50 ml) via ultrasonication for 50 minutes. Then the samples were filtered through a prewashed Whatman filter No. 41 into pre-cleaned polypropylene bottles. All filtered samples were preserved at 40C in a refrigerator until subjected to major inorganic ionic analysis. The major ionic species anions (F-, Cl-, NO3- and SO42- ) and cations (Na+, K+, Ca2+ and Mg2+) were quantitatively determined by Ion Chromatograph (DIONEX-2000, USA).

Results and Discussion

Fig. 1 shows monthly averages of PM2.5, PM10 and PM10-2.5 concentrations along with their Indian National Ambient Air Quality Standards (NAAQS). The PM10 concentration, were between 91 μgm-3 (February) and 465 μgm-3 (October) with an annual mean 219 (±84) μgm-3. The annual mean of PM10 is about more than two times higher than the standard set by NAAQS (100 μgm-3) for PM10 as indicated in Fig. 1 by box with solid lines. The higher PM10 levels were due to windblown dust loads during summer or pre-monsoon months, which were transported from the adjoining Desert regions, especially from the Thar and Margo Deserts of Western India and beyond (Pandithurai et al. 2008) along with the thermodynamic conditions in the planetary boundary layer, which influence the pollutants dispersion. An annual mean PM2.5 concentration was found to be 97 (±56) μgm-3, which is slightly lower as compared to the value reported by Tiwari et al. (2008) during 2005 at the same station and about two times higher than standard (40 μgm-3) set by NAAQS for PM2.5 as indicated in Fig.1 by box with dotted lines. The PM2.5 concentrations varied between 27 μgm-3 (March) and 227 μgm-3 (December). The high winds and the broader mixing layer improve the dispersion of particles in the atmosphere during summer. However, frequent thermal inversions, foggy conditions and stable atmospheric boundary layer during winter causes accumulation of particulates matter in the lower atmosphere as reported by Tripathi et al. (2006), who have also reported ~75% contributions of fine particles to total mass of aerosols at Kanpur (Indo-Gangatic Basin site) and suggested their significant association with the prevailing foggy conditions in the winter. The higher percentage contribution of fine size particles at Delhi attributed to a very high emissions from the bursting of the fire- crackers during Diwali festival (October or November), bio-mass burning to curb severe cold and favorable meteorological conditions for accumulation of pollutants in the lower

levels during winter.

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effects caused by acid rain depositions (Pope et al. 1995). However, coarse mode particles (d > 2.5 μm) are mainly produced by natural processes, which include sea-salt aerosols produced by direct dispersal of Ocean water and Crustal aerosols, which originate from the solid surface of the Earth. In this point, it is worthy to note that although PM10 is a better indicator of total suspended particulate (TSP), it may not necessarily represents true picture of more hazardous fine particulate (PM2.5). This situation is particularly important in Indian context, where significant proportion of PM10 may be due to locally generated wind-blown dust in the coarse fractions (i.e. PM10), and which may not be as harmful as PM2.5.

By difference between the concentrations in PM10 and those in PM2.5, we have obtained the contribution of the coarse fraction (PM10-2.5). The mass concentrations of PM10-2.5 were varied corresponding to the variations in PM2.5 and PM10, as shown in Fig.1. The monthly mean variations in PM10-2.5 concentrations provides the clear picture of the fraction of coarser aerosol particles over observation site, which shows significantly higher fractions during summer months and lower fractions during winter months.

To understand the contributions of PM2.5 in PM10, the ratio of PM2.5/PM10 is calculated. The mean ratio is found to be ~0.48 ±0.2, which varies from 0.18 (June) to 0.86 (February).

The ratio is much lower during summer months, indicating lesser fine particle fraction in PM10 and suggesting the dominance of coarser particles due to mineral dust transported from the adjacent Desert region. However, the ratio is much higher during winter months, clearly indicating larger fine particle fractions in PM10 at this location. These high fractions of fine mode particles, attributed to low level inversion and favorable meteorological conditions for accumulations of pollutants in lower atmosphere, which are emitted from the various anthropogenic sources such as biomass burning in open fields, domestic fuel in rural settings, emissions from thermal power plants, brick kilns, fossil fuel burning and vehicular exhausts.

Water Soluble Ions in PM10 and PM2.5

The monthly mean ±ó (standard deviation), maximum and minimum values of water-

soluble ionic species in the aerosol samples of PM2.5 and PM10 are shown in Table 1. Among all chemical species, SO42- has the highest concentration in both the aerosol samples,

which varied from 2.14 to 71.86 μg m-3 in PM2.5 with a mean concentration 19.76 (±14.65) μgm-3. However, SO42- concentrations in PM10 varied between 6.03μgm-3 and 104.94μgm-3 with a mean concentration 27.71(±19.37)μgm-3. In PM10, the concentration of Fluoride (F- ) ion was ~0.26 (±0.13) μgm-3, however, due to its low concentration, it was not detected

in PM2.5. The ionic abundance, on an average, showed the general trend as SO42- > Cl- > Na+ > NO3- > K+ > Ca2+ > Mg2+ in PM2.5 and SO42- > Cl- > NO3- > Ca2+ > Na+ > K+ > Mg2+ > F- in PM10.

The percentage contribution of each chemical species in both aerosol samples calculated and found that approximately 40% and 20% in total PM2.5 of water-soluble ionic fraction as anions and cations respectively whereas 27% and 14% in total PM10. The unanalyzed portion of both PM10 and PM2.5 samples consist of carbonaceous aerosols such as black carbon and organic carbons, ammonium and other insoluble elements.

The analyzed ionic species in PM10 mainly consists of secondary inorganic aerosols (SO42+, NO3- and F-) which on an annual basis, accounts for 42.41 μgm-3, salt aerosols (Na+

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and Cl-), which account for 27.40 μgm-3 and mineral matter (K+, Mg2+ and Ca2+), account

for 20.73 μgm-3.The PM2.5 are mainly made up of not-determined fractions (39.46 μgm-3), secondary inorganic aerosols (26.15 μgm-3), salt aerosols (22.48 μgm-3) and mineral

matter (8.41 μgm-3). However, the difference between analyzed ionic species in PM10 and those in PM2.5 gives the contribution of the ionic species in coarse fractions (PM10-2.5). Out of total coarse fractions,

Table 1. Annual mean, maximum and minimum values of water soluble ion concentrations in PM2.5 and PM10

Not Detected = NA

72.9 % are not-analyzed fractions. The analyzed coarse fractions (PM10-2.5) mainly composed of secondary inorganic aerosols species (13.07%), mineral matter (10.06%) and salt particles (4.02%). The relatively high percentage of nitrate and sulfate in PM10-2.5 indicates their association with other coarse components in mineral matters, not-determined elements and salt aerosols originated from the various local and regional sources. In mineral matters such as silicates, carbonates, alumina, dolomite etc. and in not-determined fractions, the contributions from local or regional origin could be road traffic dust re- suspension, soil re-suspension, construction-demolition activities and handling bulk materials for metro-rails network inside the entire megacity Delhi.

Secondary inorganic aerosols had a prevalent fine grain size (a mean PM2.5/PM10 ratio of 0.48). This fine grain size is generally observed for sulfate and nitrate. Nevertheless, nitrate occurs with a prevalent coarse mode (mean PM2.5/PM10 ratio of 0.44) which may be attributed to the formations of NaNO3 and Ca(NO3)2 particles from the reaction of HNO3 with the salt and/or the mineral dust. Very high mean PM2.5/PM10 ratio of 0.82 for salt

particles attributed to the same mean level of Na+ for both PM2.5 and PM10 and a mean PM2.5/PM10 ratio of 0.71 for Cl-. The variations of Cl-/Na+ ratio in PM2.5 and PM10 during 2007 are plotted in Fig. 6. The much higher ratio (23.8 for PM2.5 and 26.0 for PM10) in December (winter) is attributed Cl- to non-marine sources and slightly less than one (0.84

for PM2.5 and 0.95 for PM10) in June (pre-monsoon) indicates that the source of Cl- and Na+ from the marine air masses for both PM2.5 and PM10.

Significant contributions of SO42-, Cl-, Na+ and K+ were found in PM2.5, which could possibly be linked to the anthropogenic emission sources mostly burning of fossil fuel and biomass (Tare et al. 2006). On the other hand, considerable amounts of Ca2+ along with SO42-, Cl-, Na+ and K+ were found in PM10 are linked to the natural sources, which are

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essentially soil derived (Wang et al. 2003). Significant large contribution of Na+ in PM2.5 suggests their presence of non-marine sources other than marine salts whereas low contribution of Na+ in PM10 could be due to soil derived. Parmar et al. (2001) have found equal distribution of sodium in both fine and coarse modes in their study at Agra during monsoon period. The source for fine mode sodium is largely unknown. However, Hong and Chak (1997) have reported that the combustion of coal, oil or biomass may be important sources for abundance emission of fine mode sodium. The percentage contribution of NO3- was found to be approximately equal in both PM2.5 and PM10 samples. Finlayson- Pitts and Pitts (2000) have reported that NO3- can be found in the atmosphere both in the fine and coarse modes with highly variable amount, where the fine particles are generally associated with polluted urban region and the larger particles are associated with marine region. As the experimental site is far away from the marine regions, the possible source of NO3- in coarse mode is due to soil derived as reported at the nearby stations, Agra (Parmar et al. 2001) and at Kanpur (Tare et al. 2006). Ammonium ion was not detected in both PM10 and PM2.5 samples in the present study; however, much of the water-soluble ammonium ion (~77%) was obtained from fine mode aerosols over Kanpur by Tare et al. (2006) and in fog water and rain water samples at Delhi (Ali et al., 2004).

Conclusions

PM10 and PM2.5 mass concentrations and their chemical characteristics along with their source of origin have been studied, at New Delhi. The mean annual PM10 and PM2.5 levels (± standard deviation) were ~219 (±84) and 97 (±56) μg m-3, respectively. These levels are two times higher than the Indian National Ambient Air Quality Standards. PM2.5 shows the higher concentration during winter, as a result of the enhanced levels of secondary aerosols. PM10 exhibited higher concentrations particularly during transition period (pre- monsoon) due to mineral dust transported from Thar Desert region. The mean PM2.5/ PM10 ratio was found to be ~0.48± 0.2, which varies from 0.18 in June due to dominance of coarse mode natural mineral dust and 0.86 in February due to dominance of fine mode anthropogenic particles. The PM2.5 are mainly made up of not-determined fractions (39.46 μgm-3, 40.9%), secondary inorganic aerosols (26.15 μgm-3, 27.1 %), salt aerosols (22.48 μgm-3, 23.3%) and mineral matter (8.41 μgm-3, 8.7 %).

References

Ali K., Momin G.A., Tiwari S., Safai P.D., Chate D.M. and Rao, P.S.P., 2004, Atmosph Environ, 38, 4215-4222.

Beegum, N.S., Moorthy, K.K., Babu, S., Satheesh, S.K., Vinoj, V., Badarinath, K.V.S., Safai, P.D., Devara, P.C.S., Singh, S., Vinod, Dumka, U.C. and Pant, P., 2009, Atmosph Environ, 43, 1071–1078.

Charlson, R.J., Schwartz, S.E., Hales, J.M., Cess, R.D., Coakley, J.A., Hansen, J.E. and Hoffmann, D.J., 1992, Science 255, 423-430.

Gabriel, R., Mayol-Bracero, O.L. and Andreae, M.O., 2002, J Geophys Res, 107(D19), 8005, doi:10.1029/ 2000JD000034.

Hansen, J. E., Sato, M. and Ruedy, R., 1997, J Geophys Res, 102, 6831-6864. Hong, Z. and Chak, K. C., 1997, J Aerosol Sci, 28(101), 213-214.

Kulshrestha, U., Saxena, A., Kumar, N., Kumari, K.M. and Srivastava, S.S., 1998, J Aerosol Chem, 29(20), 109-118.

Lavanchy, M.G., Schotterer, U., Schwikowski, M., Gaggeler, H. W. and Baltensperger, U., 1999, J Geophys Res, 104, 21227-21236.

Menon, S., Hansen, J., Nazarenko, L. and Luo, Y., 2002, Science, 297, 2250-2253.

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Parmar, R.S., Satsangi, G.S., Kumari, M., Lakhani, A., Srivastava, S.S. and Prakash, S., 2001, Atmosph Environ, 35, 693-702.

Pope, C.A., Thun, M., Namboodira, J., Dockery, D.W., Evans, J.S., Speizer, F.W. and Heath Jr., C.W., 1995, Am J Resp Crit Care Med, 151, 669-674.

Pandithurai, G., Dipu, S., Dani, K.K., Tiwari, S., Bisht, D.S., Devara, P.C.S. and Pinker, R.T., 2008, J Geophys Res, 113, D13209, doi:10.1029/2008JD009804.

Safai, P.D., Kevat, S., Praveen, P.S., Rao, P.S.P., Momin, G.A., Ali, K., and Devara, P.C.S., 2007, Atmosph Environ, 41, 2699-2709.

Tare, V., et al., 2006, J Geophys Res, 111, D23210, doi:10.1029/2006JD007279. Tiwari, S., Srivastava, M. K. and Bisht, D.S., 2008, Earth Sci India, 1(III), 92-107 Tripathi, S.N., et al., 2006, J Geophys Res, 111, D23209, doi:10.1029/2006JD007278.

Wang, G., Wang, H., Yu, Y., Gao, S., Feng, J., Gao, S. and Wang, L., 2003, Atmosph Environ, 37, 2893-2902.

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H–P–12

Ozone Distribution using TES Measurements

Sunita Verma* and John Worden

*Birla Institute of Technology Mesra,Extn Centre Jaipur, Rajasthan, India

JPL,California Institute of Technology, Pasadena, CA-91109, USA

The ozone (O3) measurements obtained from Tropospheric Emission Spectrometer (TES) during the Asian summer monsoon of July 2007 over the Tibetan Plateau and Indian

subcontinents show high O3 mixing ratio (> 100 ppb) in the upper troposphere.

The global 3D chemistry transport model GEOS-Chem is used to infer the lightning and surface emissions contributions to the O3 distribution. The enhancement in upper tropospheric O3 shows correlation with regions of deep convection indicating that surface emissions and lightning significantly affect this O3 distribution.

Introduction

The O3 distribution, its annual and interannual trends over the highest plateau on the Earth are especially important. We investigate here the high values of O3 over the Tibetan Pleatau and the Indian subcontinent, in summer as observed by Tropospheric Emission Spectrometer (TES) instrument. An analysis is done to see the origin and evolution of the O3 enhancement by analyzing the TES data and GEOS-Chem model for the period in July 2007.

Observations

TES is an infrared, high resolution, fourier Transform spectrometer covering the spectral range between 650 to 3050 cm-1 (3.3 to 15.4 μm) with a spectral resolution of 0.1 cm-1 for the nadir viewing [Beer, et al., 2001]. TES provides a global view of tropospheric trace gas profiles including O3, water vapor, and carbon monoxide along with atmospheric temperature, surface temperature and emissivity, and an estimate of effective cloud top pressure and an effective optical depth [Worden, et al., 2004]. This analysis uses TES data taken during the summers of 2007, from both the nominal operation mode and “global survey” and from special observations using the “Step-and-Stare” mode [Beer, 2006].

Model description and simulations

The GEOS-Chem global 3-D chemical transport model (Bey et al., 2001) for data interpretation is used. The specific simulation used here are based on GEOS-Chem version 7- 02-04 (http://www-as.harvard.edu/chemistry/trop/geos), has been previously described by Sauvage et al. (2007). Briefly, the simulation is driven by assimilated meteorological data for the year 2007 from the Goddard Earth Observing System (GEOS- 5) at the NASA Global Modeling and Assimilation Office (GMAO). Anthropogenic emissions are from the Global Emissions Inventory Activity (GEIA) [Benkovitz et al.,

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considering the simulations with and without lightning flash rates. The lightning influence is particularly strong between 10-30N at 200-400 hPa at around regions of India and Tibetan Plateau where NOx emissions (Fig. 3b) are also high because of anthropogenic activity. For the regions where TES observes enhanced O3, over the Tibetan Pleatau and the Indian region, the GEOS-Chem model predicts that NOx emissions contribute to increase in the upper tropospheric O3 background by 30–40%.

Figure 3. GEOS-Chem Simulated a) ozone produced from surface emissions using TES averaging kernals and b) Lightning NOx averaged over 70-105E for July month.

Acknowledgement

The research described in this paper was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The GEOS-Chem model is managed at Harvard University with support from the NASA Atmospheric Chemistry Modeling and Analysis Program.

References

Beer, R. (2006), TES on the Aura Mission: Scientific objectives, measurements and analysis overview, IEEE Trans. Geosci. Remote Sens., 44, 1102– 1105, doi:10.1109/TGRS.2005.863716.

Beer, R., T. A. Glavich, and D. M. Rider (2001), Tropospheric emission spectrometer for the earth observing system0s Aura satellite, Appl. Opt., 40, 2356–2367, doi:10.1364/AO.40.002356

Bey, I., D. J. Jacob, R. M. Yantosca, J. A. Logan, B. D. Field, A. M. Fiore, Q. Li, H. Y. Liu, L. J. Mickley, and M. G. Schultz (2001), Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, J. Geophys. Res., 106(D19), 23,073–23,095, doi:10.1029/2001JD000807.

Hudman, R. C., et al. (2007), Surface and lightning sources of nitrogen oxides over the United States: Magnitudes, chemical evolution and outflow, J. Geophys. Res., 112, D12S05, doi:10.1029/2006JD007912.

Sauvage, B., Martin, R. V., van Donkelaar, A., Liu, X., Chance, K., Jaegl´ e, L., Palmer, P. I., Wu, S., and Fu, T.- M.: Remote sensed and in situ constraints on processes affecting tropical tropospheric ozone, Atmos. Chem. Phys., 7, 815–838, 2007,

Worden, J., S. S. Kulawik, M. W. Shephard, S. A. Clough, H. Worden, K. Bowman, and A. Goldman (2004), Predicted errors of tropospheric emission spectrometer nadir retrievals from spectral window selection, J. Geophys. Res., 109, D09308, doi:10.1029/2004JD004522.

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H–P–13

Studies on Variations of Trace Gases and Particulate Matters in Mysore City, India

T S Shashikumar, M S Chandrashekara, N Ragini,

B M Rajesh and L Paramesh*

Department of Studies in Physics, University of Mysore ,

Manasagangotri, Mysore–570 006, India

Email: lp@physics.uni-mysore.ac.in

Introduction

Particulate air pollution, specifically the fine particle fraction, has been associated with increased cardiopulmonary morbidity and mortality in general population studies.

Occupational exposure to fine particulate matter can exceed ambient levels by a large factor. Due to increased interest in the health effects of particulate matter, many particle sampling methods have been developed [1]. Particulate matter is an air pollutant only when it is aerosol. Aerosols differ widely in terms of particle size, particle density and their importance as pollutants. Their diameters generally range from 0.01 ìm or less, up to about 100 ìm. Long-term changes in urban air quality are of importance to studies of human health, and urban aerosol changes may also contribute to regional aspects of climate changes. Quantitative measurements of atmospheric aerosol concentrations are therefore important [2].

Aerosols may be primarily in nature, a major contribution to PM pollution in urban area is believed to be attributed to the traffic especially to emission from diesel engines are formed at high temperature in the engine, in exhaust pipe or immediately after emission to the atmosphere. Air borne particles are important carriers of metals, certain of which posses toxic properties and commonly are present in excess of natural levels.

The present study area is Mysore city, in Karnataka, India lies between 12015" and 12025" N latitude and 76035" and 760 45"E longitude with a height of about 767 m above mean sea level.

Materials and Methods

The measurements for trace gases SO2, NO2 and aerosols RSPM (Respirable Suspended Particulate Matter) and SPM (Suspended Particulate Matter) were performed at two locations using Respirable Dust Sampler (Envirotech Model APM-460), for RSPM measurement, Whatman GF/A type No. EPM 2000 on 24 hr basis is used with an average flow rate of 1.1m3/min. For SPM cyclone cups are used and these samples were stored in polythene bags and refrigerated. The concentration of SO2, NO2 in ambient air environment was measured 24 hours with the help of Gaseous Impingers attached with the High Volume sampler (APM-460). The standard calorimetric methods were used for obtaining the concentration of SO2, NO2. First location is at KSRTC-building (Karnataka State Road

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Transport Corporation), located in central part of the Mysore city, where the vehicular traffic is the major contributor for air pollution. The second location is at KSPCB –building (Karnataka state Pollution Control Board), located in the industrial area at about 10 km from the central part of the city. Here industrial effluents are the major contributors of air pollution.

Results and discussions

The average concentration and diurnal variation of SO2, NO2, TSPM and RSPM near KSRTC and KSPCB sites in Mysore are shown in Table (1) and (2). Higher concentration of SPM is observed near KSRTC-building compared to KSPCB site, because KSRTC-Building is located in central part of the Mysore city and is more polluted due to vehicular traffic than the KSPCB site. Mysore records a low count of SO2 and NO2, and moderate to low RSPM and SPM. The concentration of SO2 and NO2 in both the sites are much low compared to the prescribed standards.

Table 1. Diurnal variations of RSPM & SPM near KSRTC, KSPCB buildings, Mysore

Table 2. Diurnal variations of SO2 and NO2 trace gases near KSRTC, KSPCB buildings, Mysore.

The average value of TSPM on KSRTC-Building is 100 mg m-3which is significantly more then on KSPCB-Building of 79mg m-3. The average value of Trace gases SO2 and NO2 in KSRTC-Building is 11.9mg m-3 and 17.5mg m-3 which is more significant then in KSPCB- Building of 10.5mg m-3 and 15.3 mg m-3. The diurnal variations SO2 and NO2 trace gases near KSRTC buildings and KSPCB buildings are shown in Fig (1) and (2).

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Conclusion

The measurements for trace gases SO2, NO2 and aerosols RSPM and SPM were performed near KSRTC, KSPCB-buildings, in Mysore city. Higher concentration of SPM is observed near KSRTC-building compared to KSPCB site. Mysore records a low count of SO2 and NO2 and moderate to low RSPM and SPM. At both places concentration of SO2 and NO2 is much low compared to the prescribed standards.

Reference

1.Kim, Jee Young., Magari, Shannon R., Herrick, Robert F., Smith, Thomas J., Christiani, David C., Comparison of Fine Particle Measurements from a Direct-Reading Instrument and a Gravimetric Sampling Method. Journal of Occupational and Environmental Hygiene, 2004, 1, 707–715.

2.Brazenor, T. J and Harrison, R. G., Aerosol modulation of the optical and electrical properties of urban. Atmospheric Environment, 2005. 39, 5205–5212.

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H–P–14

Measurement and Chemical Characterisation of Roadside Aerosol in the Delhi Region

Tarachand Lohia1, Anil Mandaria2, Gazala Habib1 and Tarun Gupta2

1Indian Institute of Technology Delhi

2Indian Institute of Technology Kanpur

*Corresponding Author: Email:gazalahabib@gmail.com

Introduction

Aerosols affect the health, urban air quality and regional/global climate, however the magnitudes of these impacts are highly uncertain. Aerosols are emitted to the atmosphere from various combustion sources including biofuel combustion for cooking, space heating, biomass burning in forest and agricultural field and fossil fuel combustion in automobiles, power plant and industries. These submicron range particles divided into the ultrafine (dp = 0.1 ìm) and accumulation (0.1 ìm = dp = 2.5 ìm) range [Friedlander, 2000]. The primary part of the fine aerosol comprises of black carbon and high molecular weight organic compounds [Friedlander, 2000]. The secondary part consists of sulfate, nitrate, and aerosols formed from organic vapour precursors [Friedlander, 2000]. Urban air pollution due to the presence of these aerosols poses significant threats on human health and environment worldwide. The problem of urban air quality is receiving more attention as an increasing fraction of population are now living in urban centres and are

demanding a cleaner environment.

Numerous epidemiological studies have reported associations between aerosols and morbidity and mortality [Dockery et al. 1993; Burnett et al., 1995; Koenig 1999; Simkhovich et al., 2008]. Various toxicological studies have linked the size and composition of aerosols with pulmonary disease [Adamson, 1999, Nel et al., 2001; Ibald-Mulli et al., 2002]. Organic carbon emitted primarily from combustion sources also form as a result of atmospheric photochemical processes which produce low volatility carbon compounds, making these particles toxic in nature and result in adverse health effect [Harrison and Yin, 2000; Jansen et al., 2005]. Some trace metals present in fine aerosols such as lead, cadmium and mercury are highly toxic in sizeable doses [Harrison and Yin, 2000].

The size range of accumulation mode particles is of the same order of magnitude as the wavelength of visible light and thereby affects atmospheric visibility [Hinds, 1999]. These particles containing sulphate and nitrate participate in acid formation and produce acid rain. Aerosols affect the climate in several ways, such as by absorbing and scattering the solar radiation, therefore changing the Earth-Atmosphere energy balance. In addition to this, aerosols also affect the microphysical and optical properties of cloud and increase the cloud life time [Andreae, 1995; Twomey, 1977; Albrecht, 1989] therefore, suppress the precipitation event. Once produced, the particles are removed from the troposphere relatively quickly (within a few days), primarily by precipitation scavenging. As a result,

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their distribution is very inhomogeneous, both in the horizontal and vertical directions. Therefore, their regional effects have been observed more severe than global effects [Ramanathan et al., 2001].

Recently, some studies have reported atmospheric particle concentration and their microphysical, chemical and optical characteristics for urban [Khare et al., 1998; Ghose et al., 2004; Tripathi et al., 2005; Kumar et al., 2006; Kumar et al., 2007; Sabapathy, 2008; Rana et al., 2009], rural [Gupta et al., 2003], coastal and continental [Moorthy et al., 2005] and oceanic regions [Vinoj et al., 2004; Satheesh et al., 2006]. These studies were aimed to assess the impact of aerosol on health, urban air quality and climate. Few recent studies [Kothai et al., 2008; Srivastava et al., 2008; Stone et al., 2009] have also focused on source apportionment of atmospheric aerosol in Indian/South Asian region. Sharma et al., [2003] have reported the concentration of organic compounds for Delhi region. However, the assessment of impact on air quality and health and regional climate also needs atmospheric concentration of other species including OC, EC, ions and trace metals. Therefore, this study is focused on measurement and chemical characterisation of atmospheric aerosol near a busy roadside.

Methodology

Experimental Setup

Two impactors designed for 1.0 mm and 2.5 mm cut size were operated at 10 and 15 lpm respectively. The impactors are made of aluminium [Figure 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 (Gupta et al., 2009).

Figure 1. PM1.0 and PM2.5 air sampler and its inertal components

Details of impactors have been reported in parallel abstract [Submitted by Amrita Singhai].

Gravimetric and Chemical Analysis

Gravimetric and chemical analysis procedure have been detailed in parallel abstract by Amrital et al., [2010]

Sampling Site

A busy roadside, near IIT Delhi was selected to carry out aerosol sampling using the two impactors. The sampling will be carried out for 22 h.

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Results

Following outcomes will be presented from this study.

1.Atmospheric roadside concentration of PM1.0 and PM2.5.

2.Concentration of chemical constituents including OC, EC, anions and trace metals.

3.Monthly variation in concentration of particulate matter and their chemical constituents.

References

Adamson IYR, Prieditis H and Vincent R. Pulmonary toxicity of an atmospheric particulate sample is due to the soluble fraction. Toxicol Appl Pharmacol. 1999; 157: 43-50.

Albrecht BA. Aerosols, cloud microphysics, and fractional cloudiness. Science 1989; 245: 1227–1230.

Andreae MO, Mora SJ and Elbert W. Biogenic sulfur emissions and aerosols over the tropical South Atlantic. 3. Atmospheric dimethylsulfide, aerosols and cloud condensation nuclei. J. Geophys. Res. 1995; 100: 11,335-11,356,.

Burnett, RT, Dales, R, Krewski, D, Vincent, R, Dann, T and Brook JR. Associations between Ambient Particulate Sulfate and Admissions to Ontario Hospitals for Cardiac and Respiratory Diseases. Am. J. Epidemiol. 1995; 142:15-22.

Dockery DW, Pope CA, Xu X, Spengler JD, Ware JH, Fay ME, Ferris BG, Jr and Speizer, FE. An association between air pollution and mortality in six US cities. New England J. of Medicine 1993; 329:1753–1808.

Friedlander SK. Smoke, dust, and haze Fundamentals of Aerosol Dynamics, Oxford Unversity Press, 2000; pp. 480.

Ghose MK, Paul R and Banerjee SK. Assessment of Impacts of vehicular emissions on urban air quality and its management in Indian context: the case study of Kolkata (Calcutta). Environ. Sci. and Pol. 2004; 7:345-351.

Gupta A, Kumar R, Kumari KM and Srivastava SS. Measurement of NO2, HNO3, NH3 and SO2 and related particulate matter at a rural site in Rampur, India. Atmos. Environ., 2003; 37:4837-4846.

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).

Hansen J and Nazarenko L. Soot climate forcing via snow and ice albedos. Proc. Natl. Acad. Sci. 2004; 101, 423- 428, doi:10.1073/pnas.2237157100

Hansen J, Sato M and Ruedy R. Radiative forcing and climate response. J. Geophys. Res., 1997;102, 6831-6864, doi:10.1029/96JD03436.

Harrison RM and Yin J. Particulate matter in the atmosphere: which particle properties are important for its effects on health? The Sci. Tot. Environ. 2002; 49:85-101.

Ibald-Mulli, A, Wichmann, H-E, Kreyling, W and Peters, A. Epidemiological Evidence on Health Effects of Ultrafine Particles. J. Aerosol Med. 2002; 15(2): 189-201.

Jacobson MZ. Global direct radiative forcing due to multicomponent anthropogenic and natural aerosols, J. Geophys. Res., 2001; 106:1551-1568.

Jansen KL, Larson TV, Koenig JQ, Mar TF, Fields C, Stewart J and Lippmann M. Associations between Health Effects and Particulate Matter and Black Carbon in Subjects with Respiratory Disease. Environ Health Perspect. 2005; 113(12):1741–1746.

Khare P, Kumar N, Satsangi GS, Kumari KM and Srivastava SS. Formate and Acetate in particulate matter and dust fall at Dayalbagh, Agra (India). Chemosphere, 1998; 36(14): 2993-3002.

Koenig JQ, Mar TF, Allen RW, Jansen K, Lumley T and Sullivan JH. Pulmonary effects of indoor- and outdoor- generated particles in children with asthma. Environ. Health Perspec. 2005; 113: 499–503.

Kumar R, Kumari KM and Srivastava SS. Field measurement of aerosol particle dry deposition on tropical foliage at an urban site. Environ. Sci. Technol. 2006; 40: 135-141.

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Kumar R, Srivastava SS and Kumari KM. Characteristics of aerosols over suburban and urban site of semiarid region in India: Seasonal and spatial variation. Aerosol Air Qual. Res. 2007; 7(4): 531-549.

Moorthy, KK, Babu SS and Satheesh SK. Aerosol characteristics and radiative impacts over the Arabian Sea during inter-monsoon season: Results from ARMEX field campaign. J. Atmos. Sci., 2005; 62 (1): 192- 206.

Nel AE, Diaz-Sanchez D and Li N. The role of particulate pollutants in pulmonary inflammation and asthma: evidence for the involvement of organic chemicals and oxidative stress. Curr. Opinion in Pulmon. Med. 2001; 7: 20–26.

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

Rana S, Kant Y and Dadhwal VK. Diurnal and Seasonal Variation of Spectral Properties of Aerosols over Dehradun, India. Aerosol Air Qual. Res. 2009; 9: 32-49.

Sabapathy A. Air quality outcomes of fuel quality and vehicular technology improvements in Banglore city, India. Transportation Research. 2008; 13: 449-454.

Satheesh SK, Moorthy K, Kaufman YJ and Takemura T. Aerosol Optical Depth, Physical Properties and Radiative Forcing over the Arabian Sea. Meteorol. Atmos. Phys. 2006; 9: 45-62.

Schauer et al. ACE-Asia Intercomparison of a Thermal-Optical Method for the Determination of Particle- Phase Organic and Elemental Carbon. Environ. Sci. Technol. 2003; 37, 993-1001.

Sharma DN, Sawant AA, Uma R and Cocker DR. Preliminary chemical characterization of particle-phase organic compounds in New Delhi, India. Atmos. Environ. 2003; 37: 4317-4323.

Simkhovich BZ, Kleinman MT and Kloner RA. Air Pollution and Cardiovascular Injury: Epidemiology, Toxicology, and Mechanisms. J Am Coll Cardiol 2008; 52:719-726.

Srivastava A, Gupta S and Jain VK. Source Apportionment of Total Suspended Particulate Matter in Coarse and Fine Size Ranges over Delhi. Aerosol Air Qual. Res. 2008; 8: 188-200.

Tripathi SN, Dey S, Tare V, Satheesh SK and Lal Venkataramani S. Enhanced Layer of Black Carbon in a North Indian Industrial City. Geophys. Res. Lett. 2005; 32: L12802.

Twomey S, The Influence of Pollution on the Shortwave Albedo of Clouds. J. Atmos. Sci. 34: 1149–1152.

Venkataraman, C, Reddy CK, Josson S and Reddy MS, Aerosol Chemical and Size Characteristics at Mumbai, India, during the INDOEX-IFP (1999). Atmos. Environ., 2002; 36(12), 1979-1991.

Vinoj V, Babu SS, Satheesh SK, Moorthy KK and Kaufman YJ. Radiative Forcing by Aerosols over the Bay of Bengal Region derived from Shipborne, Island-Based and Satellite (Moderate-Resolution Imaging Spectroradiometer) Observation. J. Geophys. Res. 2004; 109: D05203.

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H–P–15

Chemical Speciation of Multicomponent Aerosols From The Agricultural Field by Laser Raman Spectroscopy

V.M.Harpale1 and R.S.Gosavi2

1Department of Physics, Ahmednagar college , Ahmednagar (M.S.) 414001

2Arts,Science and Commerce College Rahuri. Ahmednagar (M.S) 413705

Introduction

The aerosols are not only influencing the climate and atmospheric chemistry but also human health, cloud precipitation, the energy balance by scattering and absorption of radiations (Ramanathan et.al,2001). Because of the public health dangers, it is important to have accurate and sensitive analytical method for detection and chemical characterization of these particles, which has been formidable challenge due to their complexicity. Optical spectroscopy is an especially powerful tool for chemical analysis, which has been used for many years to obtain chemical information about bulk phases. Raman measurement technique, especially, has high selectivity, giving information not only about the identity of molecule but also about their immediate environment as well (S.K.Sze,et.al,2001).By comparison with IR measurements Raman spectroscopy of particles can provide higher sensitivity. While it provides little information about particle size, Raman spectroscopy more than compensates for this with its capability for chemical speciation. Taking in to consideration above facts( Rosen and Novkov1978),we have assessed the application of Raman spectroscopic technique for the chemical characterization of atmospheric aerosols collected on quartz filters from the environment of agriculture

university campus at Rahuri,in Maharashtra state in the month of March 2008.

Experimental

In the application of Raman spectroscopic technique, a beam of monochromatic visible laser light is focused aerosol sample. The radiations scattered by the sample contain weak lines, at frequency both lower and higher than exciting radiations. The frequency difference, called Raman shift, is the characteristics of the sample and is independent of exciting frequency. The spectra obtained with the spectrometer are called Raman spectra. This arises from molecules, which scatter photon, with lower frequency is called stokes lines, and that of with higher frequency is called Antistokes lines. Thus, the Raman pattern they represent provide a molecular fingerprint for identification and characterization of the aerosol particles.

We have under taken to explore the use of Raman spectroscopy for the identification of atmospheric aerosol particles. For this purpose, we have constructed a Raman spectrometer, rather than purchasing a commercial instrument, because of the extra flexibility this approach affords. The instrument consist of (a) an excitation source (diode laser with 532 nm wave length and 25mW power) (b) sample cell (c) monochromator (d) detection

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system (Photomultiplier tube with S-20 response (e) data acquisition system and computer. The aerosol samples are collected on pure quartz filters with high volume aerosol sampler and Raman spectra is obtained using above experimental set-up. The spectrometer uses double monochromator with diffraction grating having grooves density 1800 grooves/ mm and diode laser(532 nm wave length) with 25 mW power. The spectra of aerosol samples are collected in the perpendicular direction to incident beam form the surface of quartz filter containing aerosols. Thus, the identification of aerosol samples is carried out using this spectroscopic technique.

Selection of Filter And Aerosol Sampling

The most conventional method of sampling ambient aerosols is their collection on filters. Several types of plastic film are commonly used as a filter media (e.g.Millipore, Nucleopore,etc.) for the collection of ambient aerosols. The filter material made with inorganic binders, Telflon, Polycarbonate or other polymeric materials, however, give unacceptable levels of background fluorescence and therefore are unaccepted (Barthelmie R.J.and PryorS.C.1997).The samples of ambient aerosols were obtained in short term (24 hours) collection through the use of standard high volume (2m3min-1) air sampler employing quartz filters. Before the use of collection, these filters are baked at 3000C for at least 2 hours to reduce the organic levels. Also these filters will be equilibrated for 24 hours at constant relative humidity between 20% to 40% as followed by(Qin Y and Oduyemi K,2003),and at constant temperature 150 C to 300 C. This is achieved by placing a filter paper in desiccator at least for 24 hours before investigation for chemical composition using Raman spectrometer. With this procedure lowest manipulation of aerosol samples is expected.

Figure 1. Raman Spectra Aerosol From The Environment of Agriculture Field.

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Results and Discussion

Raman spectrum of aerosol sample are collected from the environment of agricultural university campus at Rahuri (Maharashtra) in the month of march 2008. The spectra present the qualitative estimates of the chemical species present in the aerosol sample. The Raman frequencies of chemical species are obtained by comparing the frequencies reported with the literature(Degan, I.A.1997). There are 22 Raman peaks (fig.1) observed in the Raman spectrum of Aerosol sample which represented 22 Raman frequencies cm-1 Each frequency characterises the chemical species present in the ambient aerosol sample. As documented, all Raman peaks are found within the range of 716 cm-1to 3396 cm-1. As observed in the spectra, four Raman peaks are at 1627 cm-1,1668 cm-1,3276 cm-1 and 3296 cm-1,1127 cm-1, 2221 cm-1are identified as secondary amides and 1825 cm-1is cyclic amide. However,1004,cm-1,1127cm-1,2221cm-1and 2276cm-1are di-subst compounds. Similarly, peaks at 716 cm-1 and 723 cm-1represent (CH3)C compounds. The species NH,CH,SH are appeared at Raman frequencies 2554 cm-1 and 2772 cm-1. In addition to these elements,

Table 1. Raman Frequencies (cm-1) and Observed Chemical Species of Aerosols.

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cyclopropane, carboxylic salts and organic carbonates are also found as trace elements in the aerosol samples. Thus, the aerosol samples constitute different types of elements which are far from being single component system. In fact, the chemical composition of atmospheric aerosol is highly complex and vary considerably with time and location. Therefore, it is quite obvious that aerosols encountered in the environment occur as a mixture of substance of nuclei coated with dissimilar materials.

Conclusions

Thus, the result suggests a positive potential for the laser Raman technique as a analytical tool. The technique developed in the present work has made it possible to identify the mixed salts which may be present in ambient aerosols; as a result of changing atmospheric conditions. Therefore, the Raman frequencies documented in the present study serve as useful guide for the chemical characterization of aerosols.

Referances

1.Ramnathan V.et.al,(2001). Aerosols,climate and the Hydrological cycles, Science 294;2129-2124

2.S.K.Sze, N.Siddique, J.J.Sloan, R.E.Escribano., 2001 Raman spectroscopic characterization of carboneous aerosols, Atmospheric Environment 35, 501-568.

3.Rosen,H.Novakov, T., Identification of primary particles carbon and sulfate species by Raman spectroscopy, Atmospheric Environment 12, 923-927

4.Degan I.A.(1997). Tables of characteristics Group frequency for interpretation of infrared and Raman spectra Acolyte colyte publication U.K.

5.Bathelmie R.J.and Pryor S.c. (1997) secondary organic aerosols; formation potential and ambient data, Sci. Total Environ, 205, 167-178.

6.Qin Y. and Oduyemi K.(2003) chemical composition of atmospheric aerosol in Dundee U.K.,

Atmos.Environ., 37, 93-104.

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H–P–16

The Ion Chemistry, Seasonal Cycle, and Sources of PM2.1-10 and PM2.1 Aerosol in Industrial City Korba

Dhananjay Kumar Deshmukh and Manas Kanti Deb*

School of Studies in Chemistry, Pt. Ravishankar Shukla University,

Raipur,492010, Chhattisgarh, India.

*Corresponding author. E-mail address: debmanas@yahoo.com

ABSTRACT : Aerosol sample of PM2.1-10 and PM2.1 were collected at the Korba (22o 25' N, 82o 15' E) from April 2008 to March 2009 using eight stage cascade impactor type aerosol sampler at a

flow rate of 28.3 ALPM. PM2.1-10 and PM2.1 mass concentrations were determined by gravimetric analysis, and Concentrations of major water soluble ions SO42-, NO3-, Cl-, NH4+, Ca2+, K+, Mg2+ and Na+ were determined by ion chromatography. The results yield information about the mass concentrations and seasonal variation of water soluble inorganic species in both coarse (2.1 μm < Da < 10 μm) and fine (Da < 2.1) fractions, the possible source and its fate. SO42-, NO3-, NH4+ and Na+ were the major ions in both coarse and fine aerosol particles. Annual mean of mass concentration for coarse and fine aerosols were monitored to be 163.5±95.2 mg m-3 and 95.4±59.9 μg m-3 respectively. This work deals with the seasonal variation and meteorological influences of inorganic components of the aerosols like SO42-, NO3-, Cl-, NH4+, Ca2+, K+, Mg2+ and Na+. The annual mean concentration of the inorganic components were monitored to be 9.59±5.94, 8.08±8.26, 6.81±2.27, 9.35±8.84, 5.56±4.06, 2.08±0.89, 1.16±1.55 and 7.80±1.08 μg m-3 respectively in coarse particles and 28.58±10.29, 7.78±2.32, 6.29±1.83, 9.83±9.14, 5.38±2.85, 1.38±0.49, 5.93±3.33, and 10.15±6.85 μg m-3 respectively in fine particles, for the above ions. The major ions were mainly in the form of CaSO4 > Ca(NO3)2 > NaCl > NaNO3 > Na2SO4 > K2SO4 > CaCl2 > NH4NO3 > KCl > KNO3 > MgSO4 > MgCl2 > NH4Cl > (NH4)2SO4 > Mg(NO3)2 in coarse aerosol particle and (NH4)2SO4 > K2SO4 > CaCl2 > CaSO4 > KNO3 > NH4NO3 > MgCl2 > KCl > NH4Cl in fine particle. The concentrations of PM2.1-10, PM2.1 as well as various chemical species were higher in summer and low in fall. Secondary ions SO42- and NO3-, exhibited high concentrations in summer and spring due to the secondary transformation accelerated under strong solar radiation in summer and higher concentration of SO2 from coal burning. Secondary aerosol (SO42-, NO3- and NH4+), road dust or/and long range transported dust from outside Korba, industry and motor vehicle emission, coal burning were the major contributors to the air-born particulate pollution in Korba. Overall coal burning and traffic exhaust, plus the dust from the long range transport, could be the major sources of the aerosol pollution at Korba.

Keywords : Water soluble ions; Coarse aerosol; fine aerosol, Seasonal variation; Source identification.

Introduction

There is quite interest in Size-segregated data for the major components in aerosol. One of the reasons is the importance on aerosol in the radiative forcing of climate, which is highly sensitive to the size of the aerosol. The sources characteristics and health hazards of the coarse (2.1 < Da < 10 μm) and fine (Da < 2.1 μm) particulate matter are distinct. It is admitted that the impact of particles, which are smaller than 2.1 μm (PM2.1), is larger than the impact of coarse one (PM2.1-10) because these particles go deeper in the respiratory tract and become trapped on it, which affects the lung function. Atmospheric aerosols

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vary markedly in size, chemicals composition, amount and distribution in atmosphere (Mouli et al., 2003). Aerosol concentrations are influenced by meteorological factors, geographical conditions and particle emissions such as industrial emissions, traffic, agriculture activities and natural sources (Tsai et al., 2003). The above characteristics of the aerosol particles are due to their water soluble components, e.g. magnesium, sodium, potassium, calcium, ammonium, nitrate, sulphate, chloride, etc. (Tsai and Kou, 2005).

There is scarce availability of aerosol data (PM2.1-10 and PM2.1) for industrial cities of eastern central India. The systematic study of aerosol particles concentration in any shed, their characteristics diameter, distribution in fine and coarse mode, as well as their seasonal variations is still needed.

Therefore, the main aim of this study was to present the data on the distribution of water-soluble inorganic aerosols between coarse and fine aerosol and to delineate their sources of origin during the different seasons based on one year of continuous measurement at the industrial city Korba. This paper introduces psycho-chemical patterns of ambient air particulate matter in coal combustion industrial city. In this area, the largest source contribution in high particulate events is due to primary emissions of mineral matters from power plants. In this study monthly coarse and fine aerosol samples were collected during a whole year in industrial city Korba for the characterization of water soluble inorganic components in aerosol and their distribution in coarse and fine aerosols with source identification.

Experimental

Study area

Korba (population 1005, 965) is an industrially important city of Chhattisgarh, located at 22o 25’ North latitude and 82o 15’ East longitude, with a height of 304.8 meter above sea level has been selected for the present study. It is the major source of electricity in Chhattisgarh. There are many giant industries established surrounding the city Korba namely, Korba Super Thermal Power Station (KSTPS – 2100 MW), Balco Captive Power Plant (BCPP – 270 MW), Hasdeo Thermal Power Station (West – 840 MW), Korba Super Thermal Power Station (East – 440 MW) etc. The establishments of industries at few locations, have no doubt, through about material wealth. Besides, these units have provided directly employment opportunities, better educational facilities to the local population. However, the industrialization of the predominantly tribal area has led to the degradation of environment due to industrial pollution. The population around the industrial complexes is exposed to the hazards of industrial pollution thereby, influencing their quality of life. Korba area has a become a high pollution load area and its inhabitants are exposed to industrial emissions. A pall of dust and smoke hang constantly over the sky at Korba.

Sampling and analysis of aerosol

The instrument used for the sampling of aerosols was an eight stage cascade impactor type Anderson sampler (Model TE 20-800 Tisch Air Pollution Monitoring Equipment, USA). It collects particulate matter in eight different sizes i.e. 10-9.0, 9.0-5.8, 5.8-4.4, 4.4- 3.3, 3.3-2.1, 2.1-1.1, 1.1-0.7, 0.7-0.4 μm. Flow rate of the sampler was 28.3 actual litre per minute (ALPM). The samples were collected on pre-weighed Whatman 41 filter paper. Also, field blanks filters were collected to subtract the artifacts due to adsorption of gas

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cations; detector – electrical conductivity detector ED50 for both anions and cations; sample volume – 25 μL sample used for both anion and cation analysis.

Results and discussions

Mass concentration and distribution of PM2.1-10 and PM2.1 aerosols

Table 1 shows the mass concentrations of PM2.1-10 and PM2.1 aerosol during study

period. The concentrations of PM2.1-10 aerosols (n = 12) and PM2.1 aerosols (n = 12) at the study area were found to be in the range 66.5 (August) to 348.9 (May) μg m-3 and 29.4

(July) to 201.1 (May) μg m-3, with a mean and SD of 163.5±95.2 and 95.4±59.9 μg m-3, respectively during the whole study period. The seasonal average of mass concentrations were observe to be in the range 109.5-270.0 and 58.8-159.7 μg m-3, respectively for PM2.1-10 (summer>spring>winter>fall) and for PM2.1 (summer>spring>winter>fall). Frequencies of coarse and fine atmospheric aerosol particulate matter concentrations exceeding 150 μg m-3 and 65 μg m-3 (National Ambient Air Quality Standards, India, NAAQS; http:/www.scorecard.org/env-releases/def/capnaaqs.html) at industrial city Korba. These results indicated clearly that the airborne particulate pollution has been serious at Korba and it is much worse in summer than in winter and spring. It has been seen from the discussion below that the industrial emissions and the dust from the long- range transport, could be the major source of the aerosol pollution at Korba. As illustrated in Table 1, PM2.1-10 and PM2.1 mass concentrations were highest in summer, decreased through spring, winter and tended to be lowest in fall. The high concentration is summer is most likely to the high wind speed in this season, which brought large quantities of particles both from outside and local areas. The low concentration in fall was likely related to large precipitation in this season.

Table 1. Concentrations (μg m-3) of PM2.1-10 and PM2.1 and ratio of PM2.1/PM10 in Korba from April 2008 to March 2009

aNumber of samples bMaximum cMinimum dStandard deviation

eCoefficient of variance (CV = SD/Mean)

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The ratio of PM2.1/PM10 is also shown in Table 1. It could be seen that PM2.1 accounted for 37, 35, 31 and 47% of PM10 in summer, fall, winter and spring, respectively. Evidently

fine particle, PM2.1 accounted for about half of the inhalable particle in spring. Such high proportional of fine particles implies that the particulate pollution at Korba would have a great effect on the health of human being and possibly to global environmental changes.

Meteorological parameters (temperature and wind velocity) also showed higher correlation with PM2.1 than with PM2.1-10. However, the effect of the meteorological factors on particles could be very complicated. For example, high temperature might favor the evaporation of volatile or semi-volatile components on the particles; meanwhile it can favor the formation of secondary species, such as sulphate, nitrate and organic components, for the strong solar radiation. Coarse and fine atmospheric aerosol particulate matter correlate with most of the factors in summer, while in winter the correlation was weak. This would indicate that the local environment might control particle loading in summer, while the outside environment could prevail in winter. In fact in summer the wind speed is high, which could bring large amount of particles from outside areas to Korba, whereas in winter the wind speed was low and the contribution of particles from the outside could be minor. This, it must be noted that the air pollution in Korba could be under the influence of both local emissions and the long-range transported from outside areas.

Ionic concentrations of PM2.1-10 and PM2.1

Water soluble ions comprise a large part of aerosol particles and play an important role in the atmosphere. The PM2.1-10 (coarse) and PM2.1 (fine) levels for the water soluble inorganic ions are presented in Table 2. Of all anions and cations, in the terms of concentration sulphate (SO42-) is the dominant component followed by ammonium (NH4+) and nitrate (NO3 ) in coarse particle. Similarly in the fine particle sulphate (SO42-) is the dominant species followed by sodium (Na+) and ammonium (NH4+). Concentration of

SO42- was 9.59±5.94 μg m-3 and 28.58±10.29 μg m-3, respectively for PM2.1-10 and PM2.1. The concentration of NO3- was 8.08±8.26 μg m-3 and 7.78±2.32 μg m-3 for PM2.1-10 and PM2.1, respectively. Average of concentration of Cl- was about 6.81±2.27 μg m-3 for PM2.1-10 and

6.29±1.83 μg m-3 for PM2.1, respectively. NH4+ and Na+ (ammonium and sodium) were the secondary most prominent cationic components for PM2.1-10 and PM2.1, respectively. The

Table 2. Average concentrations (μg m-3) of water soluble inorganic ions in PM2.1-10 and PM2.1 in four seasons in Korba from April 2008 to March 2009

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average of concentrations of NH4+ and Na+ were 9.35±8.84 μg m-3 and 7.80±1.08 μg m-3

for PM2.1-10 and 9.83±9.14 μg m-3 and 10.15±85 μg m-3 for PM2.1, respectively. Similarly the concentration of Mg2+ and Ca2+ in PM2.1-10 and PM2.1 were found to be 1.16±1.55 μg m-3, 5.56±4.06 μg m-3 and 5.93±3.33 μg m-3 and 5.38±2.85 μg m-3, respectively.

Seasonal variations of ionic species in PM2.1-10 and PM2.1

The seasonal variations for water soluble ionic components in PM2.1-10 and PM2.1 were

shown in Table 2. Clear seasonal patterns for all the ionic species in PM2.1-10 and PM2.1 were observed. Na+, Mg2+, and Ca2+, partly from the soil/dust, were frequently observed

of higher concentrations in summer and spring, as the dry weather in this season was favorable for the re-suspension of soil particles. The concentrations of this species were low in fall, which could be due to the more precipitation in this season.

High Cl- concentrations averaged of 9.1 μg m-3 and 8.3 μg m-3 for PM2.1-10 and PM2.1 were observed in winter. The major source of Cl- in Korba might be coal burning, which

could be reasonably explain the higher Cl- concentration in winter, because of the enhanced burning activities in this season.

Table 3Average (n= 12) concentration (μg m-3) of major chemical species in PM2.1-10 and PM2.1 in Korba during the study period

The concentration of K+ in PM2.1-10 and PM2.1 were higher in winter than those in spring and summer, indicating that K+ was primarily related to the burning activities, which were enhances in the cold season.

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The seasonal variations of secondary components, SO42- and NO3-, were similar, i.e. high concentrations in summer and low concentrations in fall. The high concentrations of SO42- and NO3- in summer might be result from more efficient conversion from SO2 and NO2 in summer. The high SO42- concentration in summer was mostly from the local industrial emissions. NO3- is generally from the oxidation of NOx. Thus the variation of NO3- is related closely to NO2 and meteorological factors. NO2 is mainly from traffic emissions in big cities

Molecular composition of major ionic species

The chemical forms of the ion in both PM2.1-10 and PM2.1 in Korba were identified by bivariate correlations. The concentrations of these species have been calculated based on

the individual ion concentrations and their mutual relationships. Because the concentrations of molecular species were depended according to concentration of individual ions, the concentrations of the succeeding species were calculated based on the concentrations of the formed ions and the foregoing species (Wang et al., 2005; 2006). In the PM2.1-10 calcium sulphate was in high concentration 5.69 μg m-3 and magnesium nitrate was in low concentration 1.45 μg m-3. Similarly for PM2.1 ammonium sulphate was in high concentration 19.60 μg m-3 and ammonium chloride was in low concentration 0.51 μg m-

3 .

Sources of PM2.1-10 and PM2.1 aerosol – factor analysis

Factor analysis (FA) was performed with the ionic data set of PM2.5-10 and PM2.5 at Korba to identify the source of aerosol. Three of the major component of the variation in

the ionic concentration were identified on the basis of the magnitude of Eigen value (greater than one), and these three factors accounted for 94.0% of the total variance in the entire set of the coarse aerosol data. The results of varimax-rotated factor analysis for the coarse mode are presented in Table 4. Only factor loading 0.70 were included in Table 4, smaller loading (< 0.70) were considered to be insignificant. The first factor has high

Table 4. Varimax-rotated factor matrix and corresponding probable source type for the coarse and fine aerosol data set

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loading of Na+, NH4+, K+, Cl- and SO42- and explains 50.7% of the total variance. This factor can be attributed to photochemical sources. Factor-2 explains 25.3% of the total variance in the system, and can be attributed to airborne road dust, since it is highly loaded with Mg2+ and Ca2+. Finally, Factor-3 explains an additional 18.0% of the total variance and could be identified as traffic emissions, since it is highly loaded with NO3-.

The results of varimax-rotated factor analysis for the fine mode are also presented in Table 4. The variables of chemical species in the fine fraction may be explained on the basis of three common factors, elucidating 83.2 % of the total system variance. Factor-1 consisting of high loading of Na+ NH4+, K+, SO42- and Cl-, explains 33.2% of the total variance and it may be attributed to photochemical sources. Factor-2 has high loading for Mg2+ and Ca2+, and accounts for 31.6% of the total variance of the system, and hence may be attributed to airborne road dust. Finally, Factor-3 clarifies a further 18.4% of the total variance. This factor can be ascribed to traffic emissions as it has high loading for NO3-.

Conclusion

The analysis of aerosol samples collected in Korba, India during the period of April 2008 to March 2009 has been presented. The annual average concentration of PM2.1-10 and PM2.1 were 163.5 and 95.4 μg m-3, respectively. Especially the fine particles pollution was

quite considerable in Korba. In PM2.1-10, SO42-, was the highest and NO3- was the second most abundant ion. In PM2.1, SO42- was also present in higher concentration than others.

NH4+ and SO42- existed in the form of NH4SO4, mostly. The main species forming in both

PM2.1-10 and PM2.1 were NH4SO4, NH4NO3, CaCl2, K2SO4, KNO3, Na2SO4, MgCl2 and KCl. As the tracers of soil/ dust, Ca2+ and Mg2+ were frequently observed of higher concentrations

in summer and spring, since the dry weather in this season was favorable for the re- suspension of soil particles. The concentrations of Cl- and K+ in coarse and fine particles were higher in winter, indicating that it was primarily related to heating activities, which were enhanced in the cold season. The secondary components NO3- and SO42- shows similar seasonal variation, that means high concentrations in summer and low

concentrations in fall for both PM2.1-10 and PM2.1particles. For both PM2.1-10 and PM2.1 particles all the ions shows low concentrations in fall due to large precipitation in this

season. The application of factor analysis gave a clear indication of the origin of inorganic ions from both anthropogenic and natural sources such as industrial process, incomplete combustion of hydrocarbons and automobile exhaust. Factor analysis has identified three components/sources in the PM2.1-10 and PM2.1 aerosol, namely, photochemical, airborne dust and traffic emissions. Photochemical and traffic sources become more significant with the motorization in recent year.

Acknowledgement

We thanks the Indian Space Research Organization (ISRO), Bangalore for providing financial assistance. We are thankful to Head, Pt. Ravishankar Shukla University, Raipur, India for providing necessary laboratory facilities. We are also thankful to prof. Yukio Suzuki, Kobe Institute of Health, Japan for analysis of aerosol samples.

References

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2.Tsai, Y.I., Kuo, S.C., 2005. PM2.5 aerosol water content and chemical composition in a metropolitan and a coastal area in southern Taiwan. Atmos. Environ, 40, 1781-1793.

3.Tsai, Y.I., Lin, Y.H., Lee, S.Z., 2003. Visibility variation with air qualities in the metropolitan area in southern Taiwan. Water Air Soil Pollut. 144, 19-40.

4.Wang, H., Kawamura, K., Shooter, D., 2005. Carbonaceous and ionic components in wintertime atmospheric aerosol from two New Zealand cities: implication for solid fuel combustion. Atmos. Environ. 39, 5865-5975.

5.Wang, Y., Zhuang, G., Zhang, X., Huang, K., Xu, C., Tang, A., Chen, J., An, J., 2006. The ion, chemistry, seasonal cycle, and sources of PM2.5 and TSP aerosol in Shanghai. Atmos. Environ. 40, 2935-2952.

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