Indian Journal of Radio & Space Physics Vol. 32, October 2003, pp. 306-3 1 1

Atmospheric aerosols and air pollution

N V Raju City Engineering College, Vasanthapura, Bangalore 560 061

and

B S N Prasad & B Narasimhamurthy Department of Studies in Physics, University of Mysore, Manasagangothri, Mysore 570 006

Received 29 July 2002; revised 24 February 2003; accepted 21 April 2003

Multiwavelength radiometer measurement of aerosol optical depth (AOD) at ten wavelengths in the visible and near I R is an ongoing programme since 1 988 a t Mysore ( l2°N, 76°E), a semi-urban continental area with a population o f about I million. The analysis of l O-yr data indicates an increase in the spectral AOD which is attributed to the increased air pollution resulting from anthropogenic activities. The pollution related aerosol turbidity parameters a and 13 are determined graphically from AOD. The size-dependent parameter a shows a decrease initially and later on an increase. The number density parameter 13 remains almost a constant throughout the data period. Aerosol size spectrum is retrieved by numerical ly inverting the AODs, and the aero.sol characteristics are estimated. These indicate that a depends on the number of accumulation mode particles, and 13 on the mass loading.

Keywords : Aerosol, Optical depth, Air pollution

1 Introduction Various amounts of contaminants continuously

enter into the atmosphere through anthropogenic processes such as coal or gas based heavy industries, bio-mass burning and emissions from petrol and diesel vehicles, thereby enhancing the atmospheric aerosols. Interacting with the solar radiation, aerosols give rise to changes in irradiance of earth . A quantitative measure of this change is expressed by aerosol optical depth (AOD) which is the attenuation/extinction of solar radiation by unit cross­section vertical column of atmospheric aerosols. By collecting the solar radiation on the earth, AOD can be determined. Scattering of solar radiation by aerosols is referred to as turbillity t which is a function of both the number and size of the aerosols. From the measured AODs, the number- and size-dependent turbidity parameters can be obtained. Thus, turbidity can be used as an index of atmospheric pollution. Since the total particulate load influences the energetics of the atmosphere, the turbidity is an important input to climate models, whereby the sensitivity of climate to aerosol changes can be studied. Several studies have focussed2-7 on the influence of meteorological factors and the atmospheric pollutants on the turbidity making it a location-specific.

Pollutants give rise to aerosols of varied number and size. Accordingly, the aerosol size distribution is determined by the relative strengths of different production and removal mechanisms. The turbidity can be understood in relation to the size distribution parameters. This means that the study of size distribution of aerosols is an important area for examining the effects of air pollution. While the total number and mass concentration may play an important role in exposure and health-risk assessment analysis, often an understanding of the particle size distribution provides more information on the type of atmospheric processes resulting in the distributions8.<J .

In meteorology, the term visibility, also called meteorological range, is used to indicate how far it is possible to see in the horizontal direction. McClatchey and Selby to developed an equation relating visibility with the turbidity parameters a and f3. A strong correlation between visibility and extinction coefficient is observed by Trier and Horvathl l .

The present work is a study of l O-yr data of AOD of a low latitude station, Mysore ( l 2°N, 76°E). On time scales of month, season and year, the variation in AOD, the turbidity parameters and visibility are examined. These are explained in terms of pollutants S02, NOx and suspended particulate matter (SPM).

RAJU et al. : AEROSOLS & AIR POLLUTION 307

Further, the dependence of turbidity parameters on the aerosol size characteristics is reported.

The measurements made in this study, though relate to Mysore, are broadly indicative of a low latitude, continental and semi-urban location of the subcontinent. Under the ISRO-Geosphere Biosphere Programme, Aerosol Climatology and Effects project operates a network of solar radiometers, of which Mysore has one. Accordingly the present work is a part of developing an aerosol climatology for the Indian region.

2 Site description Mysore is a tropical continental station in the

Indian subcontinent with a mean height of about 767 m above mean sea level. It is situated on the Deccan plateau of peninsular India. Arabian sea is at a distance of 200 km on the west, Bay of Bengal 400 km away on the east and the Indian Ocean is about 500 km away in the south. In north of Mysore lies a vast land-mass of Asian continent.

3 Aerosol optical depth A multi wavelength radiometer (MWR) is used to

collect the solar radiation. The construction of the radiometer is based on the principle of filter-wheel photometry. Collecting the radiation through 10 narrow band wavelength filters in the range 400- 1 025 nm (visible and near infrared), and analyzing by Langley technique the total optical depth is obtainedI2. 1 3 . Subtracting the contributions due to molecular scattering, absorptions of ozone and water vapour, the spectral AODs are determined.

The MWR data collection at Mysore is generally not possible during May/June to August/September in any year because of the prevailing monsoon conditions of rains and extensive cloud cover. Thus, the data coverage is restricted to the period September/October of any year to AprillMay of the succeeding year and this is considered as an observational year.

For studying the seasonal variations, the year is divided into three seasons keeping monsoon as the most important weather phenomenon. The period from June to November of a year account for about 73% of the average annual rainfall at Mysore, and these months together are considered as forming the monsoon (M) season. The dry months, December of the year to February of the following year, characterized by reduced land temperaturel4 (27-28 0c) and near-absence of rainfall (- 3% of annual),

constitute the winter (W) season. The period from March to May of a year when the land temperature i s high (33-34°C) and the rainfall is moderate (- 24% of annual) is considered as the summer (S) season. It may be noted that, for winter season, data for three months in two consecutive years are grouped together. For example, winter of 1 989 (W89) corresponds to individual daily AOD for December 1 988 and January-February 1 989. It is seen that the data for the months September, October and November (monsoon months) for the period 1992-1994 are limited to a few days, and from 1995 onward these are almost absent. Thus, the seasonal data presented here correspond to winter and summer for the period 1 989- 1 999.

The study on the enhancement in AOD due to Pinatubo volcanic eruption ( 1 99 1 - 1 992) is not included here. With the daily values of AOD (Tp'..) ,

mean values for the month (TpM), season (Tps) and year (Tpy) are established. These results are used for further analysis.

4 Angstrom turbidity parameters and visibility To describe the attenuation of solar radiation by

aerosol, Angstroml5 introduces two parameters a and � which depend on the size and number, respectively. These are related to AOD by the equation

. . . ( 1 )

in which wavelength A is expressed in micrometres . The wavelength exponent a indicates the ratio of small to large particles, and has a value between 0.5 and 2.5. The Angstrom coefficient � is an index representing the amount of aerosol present in the atmosphere in the vertical dimension. Its value varies from 0.0 to 0.5 or even higher. A plot of 'tpA versus A. both on logarithmic scale, produces a linear graph. By least squares fitting, a and � are determined by slope and intercept, respectively. This method is the most appropriate onel6• In the present work, monthly. '

seasonal and yearly values of a and � are determined using TpM, Tps, Tpy.

The parameters a and � are related to the atmospheric visibility (VIS) through the relation 10 :

� = (0.55)Cl (3.9 1 2NIS - 0.0 1 1 62)[0.02472(VIS - 5) + 1 . 1 32 ] . . . (2)

The visibility is determined using the values of a and � in an iterative procedure with a as input and the

308 INDIAN J RADIO & SPACE PHYS, OCTOBER 2003

visibility (VIS) in km is varied until the corresponding � is reproduced to an accuracy of 10-3.

5 Aerosol size distribution The changes in the spectral vanatlOn of 'tp;\. are

indicative of changes in size distribution. This is because the spectral variation of aerosol optical depth depends on the nature of the size distribution through the scattering equation :

rh

'tpA = I nr2Qe.t (m, A, r)nc (r) dr . . . (3)

where, Qe.t is the Mie extinction efficiency parameter which is a function of the particle radius r, wavelength A and the complex index of refraction m, and Ilc(r) is the columnar size distribution (CSD) function giving the number density of aerosols in a vertical column of unit cross-section, within a small radius range dr centred at r. The lower and upper limits of integration are such that the particles with sizes within ra and rb contribute significantly to the integrand and their values depend on the extreme values of A used in estimating 'tpA' Different values have been tried for ra and rb and the range 0. 1 -3 )lm has been found to be the optimal value. The wavelength-dependent index of refraction values as given by Shettle and FennJ7 are used.

U sing the aerosol optical depths at nine wavelengths (excluding 940 nm) the columnar (height integrated) size distribution functions of aerosols nc(r)dr have been determined by numerical inversion of the integral equation (Fredholm integral). The solutions of nc(r)dr have been obtained following the iterative method described by Kingl8. From the derived size distribution profiles, total columnar content NT. effective radius Reff and mass loading m, can be computed. These are defined by the following equations :

. . . (4)

where, dp is the density of the aerosols.

For continental aerosols, the density of aerosols is given'9 to be 2.5 g cm-3. It may be noted that the effective radius, a measure of the ratio of total volume to area, of aerosols represents the radius of the monodisperse aerosols which have the same scattering characteristics as those of polydisperse particles of distribution. The number of aerosols in the size range ra to rb contained in a unit volume of the column, and their total mass are given by NT and 111 , . respecti vely.

From the monthly and seasonal AODs, the corresponding monthly and seasonal aerosol size distribution and hence the aerosol size parameters are determined. The monthly aerosol size parameters are averaged to obtain the yearly parameters.

6 Results and discussion The long-term ( 1988- 1999) varIatIOn of the

monthly, seasonal and yearly AODs (TpM, Tps and Tpy) at 400 and 1025 nm are shown in Fig. 1 . For the sake of clarity, error bars on the monthly TpM are not shown. It is seen that there is a weak decreasing trend in AODs during 1 988- 1 99 1 . The effect of Pinatubo induced aerosols is clearly seen in 1991/ 1992. There is an obvious increasing trend in the AODs after 1992 for shorter wavelengths and at wavelengths such as 1025 nm, there has been no increasing trend as is

rt ��: : ; : ; ; : : >1 1 0.0 L---L---L_L---L---1_-L...-----L_L---L---'-_"---'

i :: t '��!1 0.0 L-----L.-1_.L.----L--.l_...l----L_L---L--1_-L-----.J

i :: t�� I :t;;;;;;;;� 0.0 �.L...L'__'_w...........L'--'-LL-.L...L'__'_LL.L...L'--'-.L......-'-L_'__'___L..... "--'

� :: t'� 1 F t '�5 -; ; : : ; ; : ; ; : 1 0.0 88/89 Il919O 90191 91/92 92193 93I!M 114/95 95/96 96/97 97/98 98/99

YEARS

Fig. 1-Long-term variation of aerosol optical depth (monthly, seasonal and yearly variations at 400 and 1 025 nm).

RAJU et al. : AEROSOLS & AIR POLLUTION 309

evident from Table 1 . The tabulated results are obtained from the analysis of annual AOD data. As a part of IMAP network activity, the MWRs are operated at Trivandrum(9°N) and Visakhapatnarn ( 1 8° N) for atmospheric aerosol studies20• The AODs at these stations over the years also show an increasing trend. The annual increases are - 9% at shorter wavelengths and - 3% at longer wavelengths for both Trivandrum and Visakhapatnarn2o.

In Fig. 2(a) is shown a typical plot of 'tpA VS A, both on logarithmic scale for obtaining a. and (3. The seasonal and yearly values of a. and (3 are plotted in

Table I-Annual increase in AOD

A Increase in AOD nm %

400 6

450 5.2

500 4.2

550 5.2

600 5.8

700 5.7

750 4. 1

800 3.9

935 0.5

1025 0

.;,,-0.8 r(a) £ -1 . 6 _

L-__ � __ L-__ � __ L-__ � __ �� -1.2

� i :: �" ) ���0-<-:�: J ;;. 88189 89190 90191 91192 92/93 93/94 904/95 95/96 96/97 97/98 98199 YEARS

Fig. 2--{a) Log-log plot of TpA vs A for determining a and 13. (b) Seasonal variation of a. (c) Seasonal variation of 13. (d) Yearly variations of a and 13. and (e) Yearly visibility over different years

Fig. 2 [(b), (c) and (d)]. It is seen that the a values show a weak decreasing trend during pre-Pinatubo years and an increasing trend of about 1 6% in post­Pinatubo period. No significant variation is seen in 13 values. Seasonal values of a. show a decrease initially. but in the later years there is a continuous increase during both winter and summer. Turbidity coefficient is generally higher in summer than in winter. ]n summer, the high temperatures would result in enhanced dust loading and also increased photochemical processes. The combined effect of significant wet removal during monsoon and the decreased production of aerosols in winter result in lower (3 in winter as compared to summer values. As seen from Fig. 2(c), the turbidity coefficient (3 does not show any large variation during pre-Pinatubo years. From 1993 onward, though there is an increase till 1996 and thereafter a small decrease during summer, the overall trend is seen to be nearly a constant during 1 993- 1999. In winter also an increase in (3 is observed during 1992- 1 993, but remains nearly a constant till 1997, after which a small decreasing trend is seen. The long-term trend in the seasonal values of a. and (3 are also reflected in the inter-annual variations of a. and (3.

Figure 2(e) shows the variation in the visibility over the years. It is evident that a. has a larger influence on the computed visibility values (larger a values resulting in reduced visibility). Since a depends on the ratio of small particles to large ones, the size spectrum is divided into two parts; i.e., Nil and Ne separated at 0.5 �m so that

0.5 Na = f nc (r) dr

o

and 4

Nc = f nc (r)dr 0.5

which are considered as accumulation and coarse mode particulate content in a vertical column of unit cross-section and hence are expressed in the units of particles/m2• Figure 3 [(a), (b), (c) and (d)] shows the variations in Na, Ne, Reff and ml through the years. The accumulation mode particles Na being larger than the coarse mode particles Ne by an order of magnitude, the ratio NJNe is mainly determined by Na. Similarly ml is determined largely by the coarse mode particles. As such the variation in a. can be compared with that

3 10 INDIAN J RADIO & SPACE PHYS, OCTOBER 2003

i J";--�-:-::-2-�-! ] i l';-;-��-l-� l l : : � (,';���_;�:_�: 1

7 300 e (d) e 200

i 1 00

88189 89/90 90191 91192 92/93 93/94 94/95 95196 96197 97198 98/99 YEARS

Fig. 3-Long-term variation of (a) Na, (b) Nc, (c) Reffand (d) nI,

of Na [Figs 2(d) and 3(a)] and � can be compared with ml [Figs 2( d) and 3 { (b) and (d» ) ] . Effective radius Reff increases during pre-Pinatubo period and a decrease afterwards as shown in the Fig. 3(c). Thus, it shows an inverse relation with that of a. The long-term variations of the AODs at lower wavelengths, and the parameters a and Na indicate an increase in the accumulation mode (submicron size) particles and hence pollution due to anthropogenic activities over the years. However, the total aerosol mass load (ml) does not show any large increase over the years since submicron particles do not add to the aerosol load of the atmosphere. The aerosol load (ml) is largely controlled by Nc, the coarse mode particles and these do not show any marked increase over the years.

In the absence of any coal or gas burning heavy industries in and around Mysore, and the region being free from any large scale biomass burning, pollution produced by vehicles is a likely cause for the observed trends in a and Na. Vehicular exhaust depends on the number of petrol and diesel vehicles on the road. Figure 4(a) shows the total number of vehicles registered over the period November 1 990-December 1999. The principal pollutants emitted by these vehicles are suspended particulate matter (SPM), nitrogen oxides NOx and varying amounts of sulphur dioxide S02 depending on the fuel used.

7e 40

r--.--'-"---.-r--.--..,.�-=_cr----r-"---'--� - . - • \ -lni-/l ,J"'· '" .. (e) • l' '.J� A .t': n • • .I� -:1': i�",. ",,: . =: 20 ,.A . .� . · . . :� �.\� U • • • • o "�I' 2�J-� � ·� J • .J � ;Z · '1, 1Ai \� . . .

7 I " , , , .-��� e • • • #tM-."; � 100 (d) . .�' • ��� � iI Ji ,-.\ • i . p . ..... :. - . � Jt' )I .\ i." !I. .. �l ;. \.1 ... . .... J .� .. \ :M V f A � rt ", "'� ;t-�� '1I")J �: ' - ', J�" � ,� � . .

O · • • � _ I - -

� r: f ('�.; , ,-)----\/-:"1 � SOD [ ; .� , , , , , , , -I a; 68/89 89/90 90191 91192 92/93 93/94 94195 95196 96/97 97198 98199

YEARS

Fig. 4-Variation of (a) Total no. of vehicles. (b) SO� concentration, (c) NOx concentration, (d) SPM and (e) Total rainfall over Mysore.

These pollutants · are continuously monitored in Mysore by Kamataka State Pollution Control Board (KSPCB). A high volume sampler is used to measure the concentration of SPM and the analyses of the gaseous pollutants are carried out using standard chemical methods using spectrometric techniques . Jacob and Hochheiser (modified) method i s used in the measurement and analysis of No.p Similarly, West and Gaeke method is used for the sampling and analysis of S02 (Private communication, KSPCB). The parameters S02, NOx and SPM are shown in Fig. 4[(b), (c) and (d)]. It is observed that there is an increase in these pollutants over the years. The overall increases in S02, NOx and SPM are, respectively, 22%, 15% and 26% per year. Apart from the other factors, the increased number of vehicles ( 1 3% per year) may be linked to the increased pollution. From the available rainfall data for Mysore, the annual/total rainfall is shown in Fig. 4(e) which indicates an increase of 25% over the years . Inter-annual variations in aerosol parameters like AODs, a, Na, etc. are controlled by meteorological and anthropogenic influences. The increasing trend in the rainfall would decrease the AODs, while the pollution contributes to

RAJU et al. : AEROSOLS & AIR POLLUTION 3 1 1

the enhancement in AODs significantly at lower wavelengths, and other related parameters. The interplay between these two influences on the observed aerosol parameters over Mysore is a net increasing trend over the years and hence the pollution related submicron size aerosols.

7 Conclusions The influence of anthropogenic and natural sources

on the long-term trends on atmospheric aerosol characteristics for a continental, semi-urban and non­industrial location Mysore ( 1 20 N) is examined. The striking feature of the results is an increase in the submicron particles over the years rather than the total aerosol load. This can be attributed as largely due to anthropogenic influences such as vehicles (exhaust) which are on the increase over the years. The increase in the number density of small aerosols is regarded as a major health hazard in urban locations.

Acknowledgements The authors thank the Indian Space Research

Organisation, Bangalore, for funding the project through its Geosphere Biosphere Programme. They thank Dr K Krishna Moorthy of the Space Physics Laboratory, Vikram Sarabhai Space Centre, Thiruvananthapuram, for many useful discussion. The authors are also thankful to the Kamataka State Pollution Control Board (KSPCB) for the supply of data on S02. NOx and SPM; and to the Regional Transport Officer (RTO), Mysore, for providing the data on number of vehicles registered in Mysore.

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