Characterization of PM, PM 10 and PM 2.5 mass concentrations at a tropical semiarid station in Anantapur, India

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1 Indian Journal of Radio & Space Physics Vol 40, April 2011, pp Characterization of PM, PM 10 and PM 2.5 mass concentrations at a tropical semiarid station in Anantapur, India G Balakrishnaiah 1, K Raghavendra Kumar 1, B Suresh Kumar Reddy 1, K Rama Gopal 1,$, *, R R Reddy 1, L S S Reddy 1, K Narasimhulu 2, Y Nazeer Ahammed 3, C Balanarayana 4, K Krishna Moorthy 5 & S Suresh Babu 5 1 Aerosol and Atmospheric Research Laboratory, Department of Physics, Sri Krishnadevaraya University, Anantapur , India 2 Government First Grade College, Bellary , India 3 Department of Physics, Yogi Vemana University, Kadapa , India 4 Department of Physics, Sri Venkateswara University, Tirupati , India 5 Space Physics Laboratory, Vikram Sarabhai Space Center, Trivandrum , India $ Received 20 September 2010; revised received and accepted 28 February 2011 The particulate matter (PM), PM 10 and PM 2.5 concentrations are estimated from regular measurements of size segregated as well as total mass concentration of near surface composite aerosols, using a ten-channel Quartz Crystal Microbalance (QCM) Cascade Impactor in a tropical semi-arid station, Anantapur, India for the period May 2006 April The monthly variations of PM, PM 10 and PM 2.5 and season-wise shares of PM 10 and PM 2.5 to PM have been computed. The highest contribution of PM 10 to PM has been noticed during local summer season, while the maximum share of PM 2.5 to PM has been noticed during the winter season. The average values of PM, PM 10 and PM 2.5 mass concentrations have been found to be 21.21±1.21, 18.7±1.06 and 17.02±1.28 µg m -3, respectively. Seasonally, the concentration has been highest in winter (24.62±3.53, 22.07±2.56, 21.29±2.31) and lowest in monsoon (18.12±1.62, 16.46±1.82, 14.47±1.57) for PM, PM 10 and PM 2.5, respectively. The back trajectory cluster analysis revealed that the aerosol loading has been significantly higher in fine mode during periods of continental air mass (winter) but when the winds shift to marine (monsoon), the loading became higher due to major contribution of sea salt aerosols, particularly in the coarse mode. PM 10 and PM 2.5 concentrations has been highly correlated with PM and inversely correlated with local wind speed. The results of this analysis underlined the importance of local emission sources, mostly from anthropogenic, which are responsible for the high PM 10 and PM 2.5 concentration levels observed during this one year - sampling period. Keywords: Particulate matter (PM), Fine particles, Coarse particles, Meteorological parameters, Aerosol optical depth (AOD) PACS Nos: Mt; Sz 1 Introduction Atmospheric aerosols influence the Earth s climate in many important ways. Aerosols interact (both directly and indirectly) with solar radiation and give rise to radiative forcing 1,2. The direct interaction of aerosols involves both scattering and absorption of radiation, while the indirect effect of aerosols on climate occurs by modifying the optical properties and lifetime of clouds. In the troposphere, the sources of aerosols are widely varied and differ on a regional basis leading to regional variations on the Earth s radiation budget 3. The role of aerosols in climate is one of the major sources of uncertainty in the prediction of climate change 4. The physical and chemical properties of aerosols are strong functions of their sources. The populated tropical region is found to contribute the most to the global aerosol surface forcing and Asia has been the largest contributor 3. In addition to optical and radiative interactions, which affect the geosphere and biosphere, atmospheric aerosols have a direct bearing on the Earth s environment and thus to human health. The health hazards due to toxic aerosols and the environmental degradation is becoming increasingly important particularly in cities and large urban conglomeration where extensive anthropogenic activities thrive 5,6. The increase in ambient particle concentrations are associated with an array of adverse health outcomes, ranging from the least adverse (increase in symptoms of respiratory irritation and small decrease in level of lung function), to the most adverse, mortality 7. Because of the ability of particulate matter (aerosols) to enter the body via the respiratory tract, its size has important toxicological and regulatory relevance. The environmental regulators have chosen to divide particles into various

2 96 INDIAN J RADIO & SPACE PHYS, APRIL 2011 size fractions (as measured by aerodynamic diameter) and measure them in units of particle mass per unit volume (µg m -3 ). Mainly two size fractions PM 10 (particulate matter whose aerodynamic diameter is less than 10 µm) and PM 2.5 (particulate matter whose aerodynamic diameter is less than 2.5 µm) are of interest, especially in view of clean air regulations. PM 10 may be emitted directly (primary particulate) or from chemical or thermal reactions in the atmosphere (secondary particulate). It is commonly referred to as inhalable or thoracic particles, as they can penetrate into the thoracic compartment of the human respiratory tract. Vedal 7 reported that a 10 µg m -3 increment (an exposure increment) of inhalable particulate above a base level of 20 µg m -3 results in linear increase in health impacts. The greater the exposure increments are, the greater is the risk of impacts. Thus, assessment of PM 10 and PM 2.5 concentrations as well as their share to the total PM concentration assumes significance from environmental perspective. With this view, the long-term data collected using the Quartz Crystal Microbalance (QCM) has been examined for PM 10 and PM 2.5 concentrations, and their seasonal dependence as well as relationship with wind speed has been studied for the first time over this site. 2 Site description and Prevailing meteorology The actual measurements have been carried out at the Department of Physics, Sri Krishnadevaraya University (SKU, o N, o E, 331 m above mean sea level), which is situated at the southern edge of Anantapur town. Figure 1 represents the location map of Anantapur in India. Anantapur represents a very dry continental region of Andhra Pradesh, India. It is geographically situated on the boundary of a semi-arid and rain shadow region. The climate, here, is primarily hot and dry in the summer (March to May), hot and humid during the monsoon and postmonsoon (June to November) and dry in winter season (December to February). This region, in general, receives very little rainfall, and the average annual rainfall is of order of 450 mm during the whole year (about 300 mm in southwest monsoon and 150 mm in the northeast monsoon periods). Within a 50 km radius, this region is surrounded by a number of cement plants, lime kilns, slab polishing and brick making units 8. These industries release large quantities of particulate matter into the atmosphere every day. The national highways (NH 7 and NH 205), industries and town area are situated in the north to south-western region, km away from the observational site. These provide a strong local source of aerosols at Anantapur and some special features are expected at this station 9. In the present study, all the data has been classified in terms of four major seasons, namely, winter (December-February), summer (March-May), monsoon (June-September) and post-monsoon (October-November), primarily on the basis of different meteorological conditions prevailing over this site during different months of the year 10. Meteorological data used in the present study has been obtained from the Automatic Weather Station (AWS) of Indian Space Research Organization (ISRO), Bangalore installed in the university campus. Figure 2 shows the monthly variations of major meteorological parameters observed over the measurement site during the study period. It has been observed that within a year, the pattern of seasonal variation in different meteorological parameters is different. The daily mean temperature is minimum, in the range o C during winter season; and maximum of about 40 o C during summer season. In general, relative humidity (RH) is found to be less than 30% during winter season, while it ranges 30-50% during both in summer and post-monsoon seasons. The season which markedly differs from all other seasons is the monsoon season, spread over 4 months from June to September, when average RH over this site is more than 70% and surpasses 90% mark quite a few times in monsoon season. Fig. 1 Location map of Anantapur city in India

3 BALAKRISHNAIAH et al.: CHARACTERIZATION OF PM, PM 10 & PM 2.5 MASS CONCENTRATIONS IN ANANTPUR 97 Fig. 2 Prevailing meteorological features over Anantapur during May 2006 April Panels from top to bottom represent monthly average temperature, relative humidity and monthly total rainfall, respectively Near surface wind speeds over Anantapur are the fastest during the monsoon season (5.14 ms -1 ), which is closely followed by the summer season (3.71 ms -1 ), whereas the winds are usually calm during the postmonsoon season (2.23 ms -1 ) and then increases slightly by the end of the winter season (2.57 ms -1 ). Apart from the speed, wind direction can also play a role in determining the type of aerosols present over a location as they help in bringing aerosols from different neighboring regions to the measurement site. Figure 3 shows the wind speed and wind direction prevailed over Anantapur during all the four seasons for the study period. The winter season is characterized by dry soil conditions, low relative humidity, scanty rainfall and low north-easterly prevailing winds constituting a continental airmass and hence, they are rich in land derived dust particles apart from other submicron aerosols produced because of anthropogenic activities. The rainfall and wind speed become moderately strong and RH increases in the summer season when the prevailing winds start shifting from north-easterly to southwesterly. During the monsoon season, the wind speed further increases and the rainfall becomes more extensive (more than 60% of the annual) and the airmass is purely marine in nature. In the postmonsoon months, the rainfall and RH decreases, and Fig. 3 Daily average values of surface level wind speed and wind direction measured over experiment site during all four seasons for the years

4 98 INDIAN J RADIO & SPACE PHYS, APRIL 2011 also the wind speed. The direction starts shifting back to north-easterly Instrumentation and Data analysis Near real-time measurements for mass size distribution of aerosols are taken regularly using a 10 channel QCM Impactor (model PC-2, California Measurements Inc). The QCM operates at a flow rate of 0.24 L min -1 and segregates particles into ten size bins with their 50% lower cut-off particle diameters (D pi ) at 25, 12.5, 6.4, 3.2, 1.6, 0.8, 0.4, 0.2, 0.1 and 0.05 µm. The typical sampling duration was kept as 5 to 6 minutes and the samples are collected at hourly intervals. The measurements are made at SKU regularly from 12 m above ground level using QCM Impactor at least once a week from morning till evening (mostly on every Wednesday of the week) with nine to ten samples taken 10 on each day of operation and atleast once a month the air samples collected at hourly interval continuously for 24 hours in a day. The ambient meteorological parameters (wind, temperature and RH) have been regularly monitored and the QCM operated only when RH<80%. The details on the ambient conditions, precautions taken and error budget are same as already reported 11. A total of 481 samples for 44 days were collected during May 2006 April 2007 at SKU, which formed the database for the present investigation (Table 1). Due to frequent occurrence of rains and RH > 80% prevailing over the study region during the monsoon season, there is less data from June to September The measurements were restricted to periods when the ambient RH was greater than 80%. Following the error budgeting given by Pillai & Moorthy 11, the error in the estimated mass concentration was in the range 10-15% for each measurement. Higher chances of error in the mass measurement for all stages of QCM occured under high RH conditions during the monsoon season because within a measurement time of 5 to 6 minutes, there could be an evaporation loss of the adsorbed water from the water-soluble particles which were being collected under low pressure conditions inside the Impactor stages 12 and therefore, measurements above 80% RH levels 13,14 have been avoided. During each sampling time, the QCM provides total particulate mass concentration (PM) and the mass concentration, m ci, for each of its 10 size bins (which gives the mass-size distribution). The instrument sucks in the ambient air and segregates the aerosols in accordance with the aerodynamic diameter into one of its ten size bins. For spherical particles with a density (ρ), the aerodynamic diameter (D a ) and particle diameter (D p ) are related through 15 D p = D a. ρ -1/2 (1) The QCM provides mass concentration of the particles collected in each stage (m ci ) as a function of particle diameter assuming a value of 2000 kg m -3 for Season (months) Table 1 Seasons and the number of samples obtained during each season for the period May 2006 April 2007 Prevailing synoptic meteorological conditions Number of sampling days Number of samples collected Winter (December, January and February) Low winds Dry soil conditions Scanty rainfall Cloud free Summer (March, April and May) Increase in wind speed Increased relative humidity Moderate rainfall Partly cloudy Monsoon (June, July, August and September) High wind speed High relative humidity Extensive rainfall Cloudy Post-monsoon (October and November) Wind weakens Relative humidity decreases Moderate rainfall Total number of samples collected = 481 Partially cloudy

5 BALAKRISHNAIAH et al.: CHARACTERIZATION OF PM, PM 10 & PM 2.5 MASS CONCENTRATIONS IN ANANTPUR 99 ρ. Accordingly, it yields mass concentration in ten size bins; the 50% cut-off diameter and the geometric mean diameter of these bins are given in Table 2. The stage 1 collects all particles with diameter >25 µm, and hence no mean diameter is assigned to that stage. Particulate matter (PM) is the mass of aerosols suspended in unit volume of air in the atmosphere which is similar and same as that of the total mass concentration (M t ). PM is estimated as PM 10 = i= 1 m ci = M t (2) PM 10 are those particles whose aerodynamic diameter is less than 10 µm and PM 2.5 are those particles whose aerodynamic diameter is less than 2.5 µm. From the size segregated mass concentration provided by the QCM, PM, PM 10 and PM 2.5 have been estimated based on the aerodynamic diameters. From Table 2, it can be seen that most of the PM 10 is contributed by the QCM stages from 3 to 10, while the channels 5 to 10 contribute mostly to the PM 2.5 (refs 11,16). Accordingly, from the QCM data (m ci as a function of i ), PM 10, PM 2.5 are estimated as 10 PM 10 = mci and PM 2.5 = mci (3) i= 3 4 Results and Discussions 10 i= Diurnal and monthly variations in aerosol mass concentrations To examine the diurnal variations, the PM, PM 10 and PM 2.5 mass concentration estimates as a function of local time for the entire period of study, has been shown in Fig. 4. All the three particulate matter size segregation mass concentrations gradually increase just an hour after the local sunrise in the morning and Table 2 Stage and cut points of QCM Impactor Stage No Particle diameter (D pi ) Lower cut-off diameter, µm Geometric mean diameter (D gi ) Aerodynamic diameter (D ai ) attains a sharp peak at around 10:00-11:00 hrs LT. The morning buildup of local anthropogenic activities associated with the traffic density is responsible for this peak 17. The morning high concentrations, low concentration in mid-afternoon hours between 14:00 and 16:00 hrs LT and nocturnal peak have also attributed with the atmospheric boundary layer (ABL) dynamics. From 12:00 to 17:00 hrs LT during the period of study, PM, PM 10 and PM 2.5 remained more or less steady. More importantly, aerosol concentrations appeared to drop rapidly between 12:00 and 14:00 hrs LT. In the evening, the concentrations of all PM segregations increased gradually due to build-up of local anthropogenic activities and increased traffic density. Figure 4 also shows mean surface wind speeds coincident with the QCM measurements. During nighttime, the wind speed has been generally slow (2-3 ms -1 ), and the nocturnal boundary layer has been shallow 18,19 in the range ( m) resulting in a low ventilation coefficient (defined as the product of boundary layer height and horizontal wind speed). This had caused confinement of aerosols and manifest as an increase in the concentration during early night period. As night advanced, there has been a drastic reduction in aerosol generation, while the aerosols closer to the surface had lost by sedimentation, resulting in a decrease in the concentration as seen in the early morning hours. Similar nocturnal behavior of mixed region aerosols has been reported earlier over coastal 20 and urban areas 17. As day progressed, the wind speed increased to 6-8 ms -1. Moreover, the solar heating of the land also increased, resulting in increased convective activity leading to an increase in the boundary layer height ( m and much Fig. 4 Diurnal variation of PM, PM 10 and PM 2.5 concentrations in correlation with wind speed during May April 2007

6 100 INDIAN J RADIO & SPACE PHYS, APRIL 2011 higher 18,21 ). This increased the ventilation coefficient leading to a faster dispersion of aerosols. Thus, the combined effects of high wind speeds and increase in the ventilation coefficient resulted in the decrease in concentration of PM, PM 10 and PM 2.5 (ref. 16). The monthly mean variations of PM, PM 10 and PM 2.5 mass concentrations obtained from the QCM measurements by averaging the daily mean concentrations from May 2006 to April 2007 over the study area have been plotted in a stack as a function of months in Fig. 5 and corresponding values have been given in Table 3. Basically, the nature of variations is the same for all the three, with the annual low occurring during the monsoon months. High values occur during the winter period, when continental airmass prevails from north-easterly followed by summer and post-monsoon seasons. PM, PM 10 and PM 2.5 values have been found to be high around 29.42±3.22, 25.44±2.63 and ±3.39 µg m -3, respectively during the winter period; with low values (15.12±1.65, 14.52±1.53, 12.14±1.53 µg m -3 ) during the monsoon months. It can also be seen that during months of continental airmass, when the PM concentration is generally high, the values of PM 10 and PM 2.5 are similar, whereas during the monsoon months Fig. 5 Monthly variation of PM, PM 10 and PM 2.5 (bottom to top panels, respectively), mass concentrations during May April 2007 in a stack both these are well resolved, with PM 10 remaining significantly higher than PM 2.5. This is due to the combined effects of wet removal of aerosols by extensive monsoon rains, and replenishment of the finer aerosols by enhanced sea spray caused by stronger monsoon winds, indicating dominance of the coarse mode aerosols in monsoon and post-monsoon seasons Season-wise percentage share of PM, PM 10 and PM 2.5 and its frequency distribution By averaging the data in each seasonal ensembles, one gets the seasonal mean values of PM, PM 10 and PM 2.5 as shown in Fig. 6. Seasonally, the concentration is highest in the winter for all PM, PM 10 and PM 2.5. The concentration decreases in the summer and reaches its minimum in the monsoon season (decrease by 2-3 µg m -3 from the summer) before increasing again during the post-monsoon season (increase by 2-3 µg m -3 from the monsoon season). However, these changes are more marked in PM 2.5 as compared to PM or PM 10 showing larger seasonal variations for the finer particles. In the bottom panel of Fig. 6, the season-wise percentage share of PM 10 and PM 2.5 to PM has been shown. The number of each slice of the pie chart indicates the percentage share of each species to PM. The PM 10 share to PM is found to be >90% always (except post-monsoon) while the share of PM 2.5 to PM is highest in winter (86.54%) and starts decreasing from monsoon (79.83%) with the lowest (72.26%) in post-monsoon season. The share of PM 2.5 to PM is highest in winter season indicating dominance of finer mode aerosols prevailing from continental airmass. Table 3 Monthly averaged PM, PM 10 and PM 2.5 concentrations, µg m -3 Month PM (Mean±SD) PM 10 (Mean±SD) PM 2.5 (Mean±SD) May ± ± ±1.53 June ± ± ±1.42 July ± ± ±1.64 August ± ± ±1.36 September 23.79± ± ± October ± ± ±1.53 November 21.48± ± ± December ± ± ±1.41 January ± ± ±2.69 February ± ± ±3.39 March ± ± ±1.56 April ± ± ±1.48

7 BALAKRISHNAIAH et al.: CHARACTERIZATION OF PM, PM 10 & PM 2.5 MASS CONCENTRATIONS IN ANANTPUR 101 Fig. 6 Seasonal variation of absolute mass concentrations of PM, PM 10, PM 2.5 (top panel) and the percentage share of PM 10 and PM 2.5 to PM (bottom panel) represented as pie chart PM 10 is highest in the summer (92.63%) season, representing the abundance of coarser mode aerosols derived from land composed of mineral dust aerosols and hygroscopic growth of water soluble aerosols due to higher ambient RH. The share of PM 10 and PM 2.5 to PM decreased substantially in the monsoon season and then increased from the post-monsoon season which is observed in both PM 10 as well as PM 2.5. The dry land conditions, low RH, high diurnal variation in ambient temperature and the rather cloud free skies prevailing during the winter season are highly conducive for generation of continental aerosols (dominance of finer aerosols); both naturally and also from anthropogenic and urban activities. The scanty rainfall and absence of clouds during this period renders scavenging processes to be poor and a high level of aerosol loading is maintained. These aerosols would comprise of coarse aerosols arising from mechanical processes associated with urban activities as well as the finer aerosols formed from precursors as well as those lifted up by turbulence. The coarse aerosols are rather short lived; while the fine aerosols have longer residence time and hence eventually dominate the spectrum during the winter season. Thus the PM 10 and PM 2.5 mass concentrations also remain high during this season. In the summer season, the continental airmass gradually shifts to marine as such the winds transition from north-easterly to south-westerly (Fig. 3), the wind speed, rainfall and cloud cover increases leading to increased scavenging of aerosols and hence the finer aerosol concentration decreases. The increased wind speed causes the increase in the coarse mode aerosol concentration such as wind blown derived mineral dust and sea salt particles, which mainly arise from natural sources. Consequently, though the PM decreases, PM 10 share to it increases as seen in Fig. 6. In fact, PM 10 share to PM is the highest in this season (92.63%). The frequent occurrence of rains and clouds results in nucleation and cloud scavenging of finer aerosols 22 and are not replenished by sea spray so that PM 2.5 share is lower than in the winter. During monsoon, the wet removal process is most effective and the particulate concentration reaches its minimum. The land remains wet, the sky is generally cloudy and diurnal variation in air temperatures is the lowest resulting in weakening of the continental sources. However, the increased wind speed and higher RH are favourable for generation and advection of more coarse aerosols and in fact the aerosol system is then dominated by these. The washout process removes both large and small particles, the larger ones more efficiently 23. But the larger particles are faster replenished by the sea spray activity. Stronger winds produce larger particles; small particles, however, are

8 102 INDIAN J RADIO & SPACE PHYS, APRIL 2011 not replenished. So, the fine particle concentration depletion results in the decrease in the share of PM 2.5 and PM 10 to PM; more rapid for PM 2.5 (Fig. 6). During the post-monsoon season, the scenario reverses; air mass generally shifts to continental followed by reduction in rainfall and cloudiness and thus the aerosol concentration gradually increases after the monsoon. The frequency distribution of PM, PM 10 and PM 2.5 for the present database in steps of 10 µg m -3 has been shown in Fig. 7. The distribution is highly skewed, spanning a wide range from 0.4 to 68 µg m -3, with most of the values lying in the range µg m -3. Considering the entire database of 12 months, the mean values are 21.13, and µg m -3 for PM, PM 10 and PM 2.5, respectively, which are quite high, particularly PM µg m -3 and 50 µg m -3, respectively for wind speed values less than 3 ms -1, whereas lower concentrations have been observed for wind values greater than 3 ms - 1. It has been reported that the impact of wind speed on PM concentrations are strongly correlated 25,26. It is also observed that there is a high correlation between 4.3 Relationship between PM, PM 10, PM 2.5 and wind speed The relationship between particulate concentrations (PM, PM 10, PM 2.5 ) and wind speed has been shown in Fig. 8. PM, PM 10 and PM 2.5 were weakly correlated with the wind speed with a correlation coefficients of R 2 = -0.24, -0.26, -0.27, respectively. The negative correlation between wind speed and PM concentrations indicates the predominance of local sources. Strong winds flush pollution out of the system, and low winds allow pollution levels to rise 24. When data were analyzed by period, no significant difference was found between the warm and cold periods. It has been observed that PM, PM 10 and PM 2.5 concentrations are greater than 60 µg m -3, Fig. 7 Frequency of occurrence of PM, PM 10 and PM 2.5 concentrations during May 2006 April 2007 Fig. 8 Relationship between PM, PM 10, PM 2.5 concentrations and wind speed

9 BALAKRISHNAIAH et al.: CHARACTERIZATION OF PM, PM 10 & PM 2.5 MASS CONCENTRATIONS IN ANANTPUR 103 PM 2.5 share to PM has been the highest in winter (86.54%) and starts decreasing from the monsoon (79.83%) with the lowest (72.26%) in post-monsoon season. In winter season, PM 2.5 share to PM has been observed to be high due to low wind speeds and low relative humidity which represents the dominance of finer aerosol particles, whereas PM 10 share to PM observed to be high during the summer season indicating the abundance of coarser aerosol particles with land derived mineral dust aerosols and hygroscopic growth of water soluble aerosols due to increased winds and high relative humidity, respectively. PM 10 and PM 2.5 showed strong correlation (R 2 =0.94) indicating dominance of PM 2.5 share in PM 10 and negatively correlated with wind speed (R 2 =0.27). Acknowledgements The authors are indebted to Indian Space Research Organization (ISRO), Bangalore for carrying out this study through its Geosphere Biosphere Programme (GBP) under Aerosol Radiative Forcing over India (ARFI) project and Dr C B S Dutt for his help and constant encouragement. The authors are grateful to the anonymous reviewers for their constructive and useful comments which helped in improving the scientific content of the paper. Fig. 9 Scatter plots of PM vs PM 10 (top panel) and PM 10 vs PM 2.5 (bottom panel) PM 10 and PM 2.5, with correlation coefficient (R 2 ) 0.94, whereas the correlation between PM and PM 10 at the observation site has been observed to be 0.84 with 562 individual datasets as shown in Fig Conclusions The monthly and seasonal variations of the near surface measurements of PM, PM 10 and PM 2.5 concentrations were carried out using QCM. The major interesting findings of the present study are: PM, PM 10 and PM 2.5 values have been found to be high around 29.42, and µg m -3, respectively during the winter period; and having low values of 15.12, and µg m -3, respectively during the monsoon period. The share of PM 10 to PM has been found to be >90% always (except post-monsoon), while that of References 1 Ramachandran S & Ribu Cherian, Regional seasonal variations in aerosol optical characteristics and their frequency distributions over India during , J Geophys Res (USA), 113 (2008) D08207, doi: /2007 JD Ramachandran S, Aerosol optical depth and fine mode fraction variations deduced from Moderate Resolution Imaging Spectroradiometer (MODIS) over four urban areas in India, J Geophys Res (USA), 112 (2007) D16207, doi: /2007JD Chung C E, Ramanathan V, Kim D & Podgrony I A, Global anthropogenic aerosol direct forcing derived from satellite and ground-based observations, J Geophys Res (USA), 110 (2005) D24207, doi: /2005JD Ramananthan V, Crutzen P J, Althausen D, Anderson J, Andreae M O, Clarke A D, Collins W D, Coakley J A, Heymsfield A J, Holben B, Jayaraman A, Kichl J T, Krishnamurti T N, Lelieveld J, Mitra A P, Novakov T, Orgon J A, Podgorny I A, Prospero J M, Priestly K, Quinn P K, Rajeev K, Rasch P, Rupert S, Sadourney R, Saatheesh S K, Sheridan P, Shaw G E & Valero F P J, The Indian ocean experiment wide spread haze from south and south-east Asia and its climate forcing, J Geophys Res (USA), 106 (2001) pp

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