Seasonal variations of black carbon aerosols and total aerosol mass concentrations over urban environment in India

ARTICLE IN PRESS

Atmospheric Environment 39 (2005) 4129–4141 www.elsevier.com/locate/atmosenv

Seasonal variations of black carbon aerosols and total aerosol mass concentrations over urban environment in India K. Madhavi Latha, K.V.S. Badarinath Forestry and Ecology Division, National Remote Sensing Agency (Department of Space, Government of India), Balanagar, Hyderabad-500 037, India Received 13 September 2004; received in revised form 31 March 2005; accepted 8 April 2005

Abstract Aerosol optical properties are one of the important global geophysical variables required in climate modeling studies. The largest variability and uncertainty in estimates of the effects of atmospheric aerosols on climate is their particle size distribution. The highest non-uniform spatial and temporal distribution of tropospheric aerosols on global scale is owing to their diverse sources, chemical compositions and lifetimes require more measurements for aerosol quantification. In the present study, changes in the response of near surface aerosol properties and their association with meteorological parameters have been studied during January–December over a tropical semiarid urban environment. Diurnal variations of black carbon (BC) aerosols showed a gradual build up in BC concentration from morning and a sharp peak occurs between 7:00 and 9:00 LT almost an hour after the local sunrise and a broad nocturnal peak from
21:00 to 02:00 local time. Total aerosol mass concentration showed positive correlation with air temperature and wind speed. Diurnal variation of coarse mode and accumulation mode particles showed a nocturnal high and daytime low. Aerosol mass size distribution showed possibly a multi-modal size distribution over the study area. Coarse mode particle loading observed to be high during summer and accumulation mode particles observed to be high during winter. Seasonal variations of BC aerosol mass concentration showed high concentrations during dry season and low concentrations during the monsoon season. Monthly average aerosol optical depth (AOD) values gradually increased from January to April and then decreased after May. The average share of BC to the total mass concentration has been observed to be 15% during January to December. r 2005 Elsevier Ltd. All rights reserved. Keywords: Aerosol mass loading; Aerosol size distribution; Number density; Aerosol optical depth; Black carbon

1. Introduction The variability and uncertainty in estimates of the effects of atmospheric aerosols on climate is particle size distribution. Aerosol optical properties are considered Corresponding author. Tel.: +91 40 238 84 220;

fax: +91 40 238 75 932. E-mail address: [email protected] (K.V.S. Badarinath).

as one of the important global geophysical variable of paramount importance by the scientific community. Physical and chemical composition of aerosols is gaining importance in the studies related to global change studies and long-term measurements of these parameters at different locations spatially across the globe are important. Mega-cities are significant sources for aerosols and it is critical to understand the key chemical and physical processes controlling the concentrations of such species in such regions. It is only by making

1352-2310/$ - see front matter r 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2005.04.004

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measurements near the sources that we will be able to make the link between source emissions and regional scale-air quality and climate impacts. Important chemical transformations occur rapidly after emission. Further, an increased understanding of aerosol and organic chemistry in mega-city regions would lead to more accurate numerical model predictions of future changes in air quality and radiative forcing in urban centers and surrounding regions. Size distribution and chemical composition are fundamental aerosol properties relevant to study the climate impacts. Aerosol size distribution influences the dynamics of aerosol population (Vakeva et al., 2001), their production and removal processes, the size transformation, lifetime, optical properties and radiative effects (Huebert et al., 1996). Size distribution of atmospheric aerosols strongly depends on the sources and sinks as well as on the meteorological processes prevailing during their lifetime (Suzuki and Tsunogai, 1988; Ito, 1993). Studies on the spatial and temporal changes of aerosol characteristics provide considerable insight into the origin of particles (Toon, 2000; Arimoto et al., 1997). In the urban environments, significant short-term changes in the aerosol characteristics occurs due to changes in prevailing circulation systems, rainfall, land surface heating, air mass types, etc. Black carbon (BC) aerosol, the optically absorbing part of carbonaceous aerosols, is the major anthropogenic component of atmospheric aerosol system. The number of vehicles in India have increased from 2 million during 1970 to 38 million during 1998. Consequent increase in emissions would be contributors to the aerosol loading. Large amount of BC causes reduction in solar flux at the surface which inturn reduce the amount of photo synthetically active radiation reaching the surface. These effects are likely to influence regional aerosol radiative forcing (Schwartz, 1996; Haywood and Shine, 1997).

Whitehouse effect is introduced to refer to increased shortwave reflectivity arising from anthropogenic aerosols (Charlson et al., 1999). Further, BC emissions particularly from heavy-duty diesel engines of trucks increases with increase in ambient air temperature (Chen et al., 2001) and this would also be important during dry months. The average atmospheric residence time of BC is high during dry periods compared to wet periods (Babu and Moorthy., 2001). All the recent major field campaigns of the last decade have ascertained the importance of BC in climate change studies (Ramanathan, 2001). Present study describes the time evolution of aerosol loading, size distribution, effective radius, mass mean radius and their association with prevailing meteorological conditions in a typical semiarid tropical urban environment of Hyderabad, India.

2. Study area The study area pertains to Hyderabad (Fig. 1), which is the fifth largest city in India. Fig. 1 shows the proximate industrial locations over the study area. It has twin cities viz., Hyderabad and Secunderabad with its suburbs extending upto 16 km. Hyderabad city is situated in 171 100 to 171 500 N latitude and 781 100 to 781 500 E longitude. Population of the city according to 1991 census is 3,145,939, which is purely urbanized. The climate of the study area is of semi-arid type with total rainfall of
700 mm occurring mostly during monsoon season corresponding to June–October. The air masses during monsoon months (June–October) originate predominantly from southwest direction and the other seasons from northeast direction. The measurements have been carried out in the premises of National Remote Sensing Agency at Balanagar (171.280 N and 781.260 E) located well within the urban center. In the

Fig. 1. Location map of the study area.

ARTICLE IN PRESS K.M. Latha, K.V.S. Badarinath / Atmospheric Environment 39 (2005) 4129–4141

study area summer season is from March to May; winter season is from November to February and monsoon season is from June to October. In the study area, the influence of open agricultural fires are negligible at all seasons and pollution from domestic fuels is quite nonexistent as people use natural gas for cooking. The study site is close to the center of the city and two highways pass through east and north of the sampling site at a distance of about 500 m whereas the sampler height from the road level is
7 m.

3. Instrumentation and data analysis MICROTOPS-II sunphotometer has been used to measure aerosol optical depth (AOD) at different wavelengths viz., 380, 440, 500, 675, 870 and 1020 nm (Leckner, 1978). Limited AOD measurements were possible during June–December due to cloudy conditions over the study area. Meteorological parameters like air temperature, relative humidity, wind speed and rainfall have been measured using meteorological station. Continuous and near-real-time measurements of BC aerosol concentrations have been carried out during January–December 2003 using Aethalometer; model AE-21 of Magee Scientific, USA. The instrument aspirates ambient air from an altitude of
3 m above the ground using its inlet tube and its pump. The BC mass concentration is estimated by measuring the change in transmittance of a quartz filter tape based on filtering of air. The instrument has been operated at a time base of 5 min, round the clock with a flow rate of 3 l min1. The instrument has been factory calibrated and errors in the measurements are
72% (Allen et al., 1999; Hansen et al., 1984; Riemer et al., 2004). Meteorological parameters like air temperature, relative humidity, wind speed and rainfall have been measured using meteorological station. Measurements on mass-size distribution of aerosols have been made regularly using a Quartz Crystal Microbalance (QCM) Impactor model PC-2 of California Measurements Inc. QCM has been operated during periods of the ambient relative humidity (RH)o75%. Aerosol samples have been collected every hour from 8.00 to 20.00 h and measurements have been made 4–5 days in every month at weekly intervals from January–December 2003. A total of
700 independent observations of mass concentration during January–December have been used to study the aerosol size distribution over the study area. QCM sucks-in the ambient air and segregates the aerosols in accordance with the aerodynamic diameter into one of its ten size bins. The aerodynamic diameter (Da) and particle diameter (Dp) for spherical particles with a density r are related through Da Dp ¼ pffiffiffi . r

(1)

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QCM provides mass concentration of particles collected in each stage (mci) as a function of particle diameter assuming a value of 2 g cm3 for r. Mean diameter (di) of QCM ten size bins are given in Table 1. QCM has provided reliable information on mass concentration and size distribution during the INDOEX cruises of 1998 and 1999 and at coastal regions (Pillai and Moorthy, 2001). QCM provides total mass concentration (Mt) as well as the size segregated mass concentration for each size bin, for each measurement. Data from QCM has been used to derive physically meaningful parameters describing the aerosols. Total mass concentration (Mt) has been obtained from Mt ¼

10 X

mci ,

(2)

i¼1

where mci is mass concentration for size bin ‘i’. The volume concentration of aerosols in the ith size bin is estimated as V ci ¼

mci , r

(3)

where r has been taken as 2 g cm3 (dividing Vci by the mean particle radius (ri) of the ith size bin). Area of the aerosols (aci) in the ith size bin has been obtained by aci ¼

V ci ; ri

ri ¼

di . 2

(4)

Volume and area estimates have been used to estimate the effective radius of aerosols Reff: P10

Reff ¼ Pi¼1 10

V ci

i¼1 aci

.

(5)

In estimating Reff, Eq. (5), the summation is made only over stages 1–10. The mass weighted mean radius is

Table 1 Size bins and mean diameters for the QCM Size bin number

1 2 3 4 5 6 7 8 9 10

Particle diameter (mm) At 50% cut-off

Geometric mean di (mm)

25 12.5 6.4 3.2 1.6 0.8 0.4 0.2 0.1 0.05

— 17.58 8.94 4.53 2.26 1.13 0.566 0.283 0.141 0.071

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estimated as P10 i¼1 d pi mci , Rm ¼ P 10 i¼1 mci

4. Results and discussion Fig. 2 shows the diurnal variation of black carbon (BC) aerosols at Hyderabad during January–December 2003. There is a gradual build up of BC concentration in the morning hours between 7:00 and 9:00 h almost an hour after the local sunrise and a broad nocturnal peak from
21:00 to 02:00 h. BC concentration decreases substantially and the diurnal minimum is attained in the afternoon hours (1400–1600 h). The morning peak in BC arises from the combined effects of (i) well-known fumigation effect in the boundary layer, which brings in aerosols from the nocturnal residual layer shortly after the sunrise and (ii) build up of local anthropogenic activities in the urban area. Low values of BC during afternoon hours has been attributed to the dispersion of aerosols, due to increase in boundary layer height in addition to the low traffic density. Analysis of traffic density along with meteorological parameters over the study area suggests that the primary determinant for BC concentration levels and patterns is traffic density (Latha et al., 2004). In addition to the BC measurements, we have conducted experiments on traffic density with respect to the type of vehicles on different days for completeness of the study. Fig. 3 shows the vehicular

(6)

where i is the stage number of the QCM, mci is the measured mass concentration in that stage and dpi is the geometric diameter of each stage. Cut-off diameter at 0.8 mm has been used to demarcate coarse and accumulation mode aerosol particles and details can be found in the literature (Latha and Badarinath, 2004; Pillai and Moorthy, 2001). The concentration in terms of number of particles per cubic centimeter has been calculated using the relation N¼

C , PrD3

(7)

where r is mass density of particles and D is particle diameter and C is mass concentration. The overall uncertainty in mci in each measurement of QCM varies from 5% to 20%, with higher errors for lower mci. Regression analysis between meteorological parameters and aerosol mass concentration has been performed using statistical techniques.

22 20 18

TIME (hrs)

16

ng/m-3 ng/m

14

∧3

36000 12

32000 28000

10

24000 8

20000 16000

6

12000 4

8000 4000

2

0 0 1

2

3

4

5

6

7

8

9

10

11

12

MONTH Fig. 2. Diurnal variation of black carbon aerosols during January–December.

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Four (heavy)

Four (light)

Three

TYPE OF VEHICLES Fig. 3. Variations of traffic density over the study area.

0.80

0.70

AOD

0.60

0.50

0.40

0.30

0.20 380

440

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density during morning, afternoon and evening periods in the study area. The vehicular density for different days suggests that two-fold increase in vehicular density during the weekdays compared to weekends over the study area (Latha and Badarinath, 2004). Spectral variation of monthly mean AOD at different bands viz., 380, 440, 500, 675, 870 and 1020 nm during January to December has been shown in Fig. 4. Spectral variation of AOD shows three peaks at 380, 500 and 875 nm suggesting possibly a multi-modal aerosol size distribution over the study area. Junge’s inverse power law distribution suggests that there should be a gradual decrease in the AOD with increasing wavelength. The observed spectral variation of AOD does not show such a feature indicating that the aerosol size distribution does not fallow the Junge’s power law distribution. High AOD values observed at 380 nm suggest dominance of accumulation mode particle loading over the study area. Similar spectral variation has been observed in other

Morning Noon Evening

Two

NO. OF VEHICLES

K.M. Latha, K.V.S. Badarinath / Atmospheric Environment 39 (2005) 4129–4141

500

675

870

1020

WAVELENGTH (nm) JAN

FEB

MAR

APR

SEP

OCT

NOV

DEC

MAY

JUN

JUL

AUG

Fig. 4. Spectral variation of aerosol optical depth during January–December 2003.

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studies over Indian region (Badarinath et al., 2004; Latha et al., 2003; Pandithurai et al., 1997). AOD observed to be minimum in January and February, which can be due to weak generation mechanisms and gas-to-particle conversion processes and also due to the less possibility of hygroscopic growth of aerosols due to low water vapor content. Maximum AOD observed during April and has been attributed to increased aerosol input due to increased surface heating and resultant vertical mixing, dry surface conditions and wind blown dust. High temperature during April–May (summer) plays an important role in heating and lifting the loose soil with association of wind speed. Decrease in AOD values has been observed during May compared to April because of dispersal of aerosols due to stronger upper winds prevails during May. Low AOD has been found after May because of washout of particles during rainy (monsoon) season. Seasonal variations of AOD suggest high values during summer and low values during winter and monsoon seasons. The seasonal variations of AOD showed similarities with other studies for different environments reported in literature (Niranjan et al., 1995; Pandithurai et al., 1997; Devara et al., 1996). Diurnal variations of accumulation mass loading (Ma) and coarse mode mass loading (Mc) on a typical day (16th January, 2003) over the study area have been shown in Fig. 5. Diurnal variation of Ma showed a primary peak at 03:00 local time (LT) and then a secondary peak at 8:00–9:00 LT followed by a sharp increase at 20:00 to reach nocturnal peak. During 11:00–16:00 LT, Ma and Mc remains more or less steady with minimum values of 1 and 10 mg m3, respectively, followed by a gradual increase till 20:00 LT. Enhancement in aerosol mass concentration during morning and evening hours has been attributed to the increase in vehicular traffic and related human activities in the study area. As night advances due to drastic reduction in the urban activities leads to reduction in aerosol generation. The solar heating of land during the day

increases convective activity leading to increase in boundary layer height. This increases the ventilation coefficient resulting in faster dispersion of aerosols due to which lower aerosol concentration has been observed during noon hours. Solar forcing is reduced during evening hours and boundary layer height decreases resulting in increased particle concentration. Similar observations have been reported in other regions over India (Parameswaran et al., 1999). Fig. 6 shows monthly average variation of total aerosol mass concentration (Mt) during January–December over the study area. Monthly average variations of air temperature, relative humidity, rainfall and wind speed have been shown in Figs. 7 and 8. Total aerosol mass concentration has been observed to be high during summer and has been attributed to high air temperature, which plays an important role in heating and lifting the loose soil with association of wind speed. Reduction in aerosol total mass concentration has been observed during monsoon season due to scavenging effects of rainfall and also due to reduction in the continental features conducive for aerosol generation by shifting the air mass. Fig. 9 shows monthly variation of coarse mode (Mc) and accumulation (Ma) mode particles loading measured using QCM particle analyzer during January–December over the study area. Coarse mode particles observed to be high during summer and accumulation mode particles observed to be high during winter. Fig. 10a–c depicts the relationship between total aerosol mass concentrations and air temperature, relative humidity and wind speed. Total aerosol mass concentration showed positive correlation with air temperature (R2 ¼ 0:70), wind speed (R2 ¼ 0:72) and negative correlation with relative humidity (R2 ¼ 0:72). The observed variations in particle loading seems to be influenced by meteorological parameters over the study area. The association between aerosol optical properties and meteorological parameters can be better explained

250

100 90 80 70 60 50 40 30 20 10 0

MA

200

Mc (ug/m-3)

MC

150 100 50

22:00

20:00

18:00

16:00

14:00

12:00

10:00

8:00

6:00

4:00

2:00

0:00

0

TIME (hrs)

Fig. 5. Diurnal variation of accumulation and coarse mode particles.

Ma (ug/m3)

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120

Mt (ug/m-3)

100 80 60 40 20

DEC

NOV

OCT

SEP

AUG

JUL

JUN

MAY

APR

MAR

FEB

JAN

0

MONTH Fig. 6. Monthly variation of total aerosol mass concentration.

350

120 Rainfall

300 250

80

200 60

150

DEC

NOV

OCT

SEP

AUG

APR

JUL

0 JUN

0 MAY

50 MAR

100

20 FEB

40

JAN

TEMP(C), RH(%)

100

RH

RAINFALL (mm)

Temp

MONTH Fig. 7. Monthly variation of air temperature, relative humidity and rainfall.

1.20

WINDSPEED (m/s)

1.00 0.80 0.60 0.40 0.20

DEC

NOV

OCT

SEP

AUG

JUL

JUN

MAY

APR

MAR

FEB

JAN

0.00

MONTH Fig. 8. Monthly variation of wind speed.

by taking a closer look at the size distribution of aerosols and possible origin of the particles. The coarse mode particles originate from mechanical processes like

wind erosion and resuspension. The accumulation mode aerosol abundance during winter months (November– February) has been attributed to the passage of

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70

40 35

Mc

Ma

60

Mc,Ma (ug/m-3)

30

50

25 40 20 30 15 20

10

DEC

NOV

OCT

SEP

JUL

MAY

MAR

FEB

AUG

0 JUN

0 APR

10

JAN

5

MONTH Fig. 9. Monthly variation of accumulation and coarse mode particles. 160

120

80 60 40 20 0 25

(a)

TOTAL AEROSOL MASS CONC (ug/m-3)

TOTAL AEROSOL

MASS CONC (ug/m-3)

140 100

120 100 80 60 40 20 0

27

29

31

33

35

0

37

10

20

(b)

AIR TEMPERATURE (deg)

30

40

50

60

70

RH (%)

170 TOTAL AEROSOL MASS CONC (ug/m-3)

150 130 110 90 70 50 30 10 0

(c)

0.2

0.4

0.6

0.8

1

1.2

WINDSPEED (m/s)

Fig. 10. (a) Scatter plot of day average air temperature vs. total aerosol mass concentration. (b) Scatter plot of day average relative humidity vs total aerosol mass concentration. (c) Scatter plot of day average wind speed vs. total aerosol mass concentration.

continental air masses from Northeast over the study area (Latha and Badarinath, 2004). The nature of variation of effective radius (Reff) and mass mean radius (Rm) are similar during January–December (Fig. 11). Reff and Rm observed to be high during summer

(March–May) suggesting relative abundance of coarse mode aerosols over the study area. Aerosol mass concentration and AOD at 500 nm showed moderate correlation with correlation coefficient of 0.56 (Fig. 12). The value of correlation coefficient reveals the extent to

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12

14

10

Reff

12

Rm

8 6 6 4

Rm (um)

10

8

4

DEC

NOV

OCT

SEP

AUG

JUL

JUN

MAY

0 APR

0 MAR

2 FEB

2

JAN

Reff (um)

4137

MONTH Fig. 11. Monthly variation of effective radius and mass mean radius.

120 100 ug/m3

80 60 40 20 0 0

0.2

0.4

0.6

0.8

1

1.2

AOD (500nm) Fig. 12. Aerosol optical depth (500 nm) vs. total aerosol mass concentration.

which the near surface sub micron aerosol mass concentration influences the AOD (Latha and Badarinath, 2004). The coefficient is not very high, even though it is quite significant, because of other contributors to AOD such as size distribution, altitude distribution and composition etc. Monthly variation of aerosol mass size distribution (dM/dR) and number density (dN/dR) over the study area have been shown in Figs. 13 and 14 respectively. The fine mode (ro0:15 mm) and accumulation mode (0:15oro1:5 mm) particle loading has been observed to be high during winter and monsoon whereas coarse mode(r41:5 mm) particles observed to be high during summer season. The mass size distribution derived from particle analyzer showed more than two peaks indicating possibly a multi-modal aerosol size distribution with minimum one mode each in the sub micron, accumulation and coarse size regions in all the seasons over the study area. Fig. 15 shows monthly variations of BC aerosol loading during January–December 2003 over the study area. Seasonal variations suggest large concentrations of

BC (
10 mg m3) during the dry months (November– April) and low BC concentrations (o
4 mg m3) during the monsoon months (June–October). These observations have been found to be higher than the mean BC levels reported for the urban sites in literature (Allen et al., 1999; Chen et al., 2001; Bhugwant et al., 2001; Leon, 2001; Babu et al., 2002). Over the study area, November–April is generally under the influence of a continental air mass while during May–September the air mass changes to clean marine associated with the monsoon. The observed seasonal changes are associated with synoptic meteorology and longrange transport in addition to local sources as the study area is purely urban and industrialized. High BC values during summer months of March and April has been attributed to the transport of air mass from continental regions in addition to the increase in fossil fuel consumption for power generation purposes. Further BC emissions particularly from heavy-duty diesel engines of trucks increase with increase in ambient air temperature (Chen et al., 2001) and this would also be important during dry months (Latha et al., 2004).

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100000

10000

dm/dr (ug m-3 um)-1

1000

100

10

1

0.1

0.01 0.01

0.1

1

10

100

PARTICLE DIAMETER (um) JAN

FEB

MAR

APR

MAY

AUG

SEP

OCT

NOV

DEC

JUN

JUL

Fig. 13. Monthly variation of aerosol mass size distribution (dM/dR).

Fig. 15 indicates BC washout during the monsoon months. Even though BC contributes only a few percent in the total aerosol mass, it can produce significant radiative effects. Jacobson (2001) mentioned that magnitude of the direct radiative forcing due to BC could exceed that due to methane, thereby making it an important species contributing to global warming. Apportionment of BC is thus very important in modeling aerosol radiative properties (Latha and Badarinath., 2004). Such estimates are virtually limited over Indian region. We have used the total aerosol mass loading (Mt) obtained using the QCM particle analyser in conjunction with BC measurements during January–December to understand the BC contribution in total aerosol mass concentration over the study area. Analysis of total mass concentration and BC aerosol mass concentration suggests that the share of BC to total aerosol mass concentration observed to be
15%. The results are in agreement with other studies reported in literature (Hess et al., 1998; Babu et al., 2002; Satheesh et al., 2002; Podgorny et al., 2000). Such a large share of BC can have serious

implications on surface and atmospheric radiative forcing. A mere 6% of soot contributes 11% to the AOD (Satheesh et al., 2002); a 35% reduction in total solar radiation over the ocean surface and an increase of
50% in atmospheric heating (Podgorny et al., 2000).

5. Conclusions Seasonal variation of aerosol total mass concentration and BC aerosol mass concentration has been measured at tropical urban area of Hyderabad, India. The analysis of results suggests that: 1. There is a gradual build up of BC concentration in the morning hours between 7:00 and 9:00 h almost an hour after the local sunrise and a broad nocturnal peak from
21:00 to 02:00 h. 2. Seasonal variations of BC aerosol showed high concentrations during dry season and low concentrations during the monsoon season.

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1.00E+13 1.00E+12 1.00E+11

dn/dlog (DP) (m-3)

1.00E+10 1.00E+09 1.00E+08 1.00E+07 1.00E+06 1.00E+05 1.00E+04 1.00E+03 0.01

0.1

1

10

100

PARTICLE DIAMETER (um) JAN

FEB

MAR

APR

MAY

AUG

SEP

OCT

NOV

DEC

JUN

JUL

Fig. 14. Monthly variation of aerosol number size distribution (dN/dR).

12

8

∧

BC(ug/m 3)

10

6 4 2 0 JAN FEB MAR APR MAY JUN

JUL AUG SEP OCT NOV DEC

MONTH Fig. 15. Monthly average variation of black carbon aerosol concentration.

3. Monthly average AOD values gradually increased from January to April and then decreased after May. 4. Total aerosol mass concentration showed positive correlation with air temperature, wind speed and

negative correlation with relative humidity and rainfall. 5. Diurnal variations of coarse mode and accumulation mode particles showed a nocturnal high and daytime low.

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6. Aerosol size distribution derived from particle analyzer showed possibly a multi-modal size distribution over the study area. 7. Coarse mode particle loading observed to be high during summer and accumulation mode particles observed to be high during winter. 8. The average share of BC to the total aerosol mass concentration has been estimated to be 15%.

Acknowledgments Authors are grateful to Director, NRSA and Dy. Director (RS&GIS-AA), NRSA for their help and encouragement and ISRO-GBP for funding support.

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