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Variations in single scattering albedo and Angstrom absorptionexponent during different seasons at Delhi, India

Kirti Soni, Sachchidanand Singh*, Tarannum Bano, R.S. Tanwar, Shambhu Nath, B.C. AryaRadio and Atmospheric Sciences Division, National Physical Laboratory (CSIR), Dr. K.S. Krishnan Road, New Delhi 110012, India

a r t i c l e i n f o

Article history:Received 26 January 2010Received in revised form4 June 2010Accepted 27 July 2010

Keywords:Absorption coefficientScattering coefficientSingle scattering albedoAngstrom absorption exponent

a b s t r a c t

Simultaneous measurements of aerosol absorption and scattering coefficients for the PM2.5 aerosolsparticles were done at Delhi during April 2008eMarch 2009 to estimate the aerosol single scatteringalbedo (SSA) and the Angstrom absorption exponents at the surface. The annual average SSA at 0.55 mmwas found to be 0.70 � 0.07 with only slight variations during the four seasons, summer (0.63 � 0.06),monsoon (0.69 � 0.07), winter (0.74 � 0.03) and spring (0.72 � 0.04). However, large variations inaverage absorption and scattering coefficients were seen during these four seasons. The averageabsorption coefficients during summer, monsoon, winter and spring were found to be 62.47 � 21.27,50.95 � 43.61, 189.65 � 85.94 and 90.65 � 33.06 Mm�1 respectively. The corresponding scatteringcoefficients were 110.46 � 36.15, 95.34 � 49.46, 565.59 � 274.59 and 236.56 � 96.25 Mm�1. TheAngstrom absorption exponent (as(abs)) remained close to unity throughout the year averaging at1.02 � 0.08, 1.02 � 0.10, 1.04 � 0.11, and 1.03 � 0.05 during summer, monsoon, winter and spring seasonsrespectively, strongly indicating that the absorption at Delhi aerosol is mainly due to the abundance ofblack carbon of fossil fuel origin.

� 2010 Elsevier Ltd. All rights reserved.

1. Introduction

Over the last two decades atmospheric aerosols have beenrecognized as one of the important factors in determining globalclimate effects (IPCC 2001, 2007). Aerosols particles suspended inthe atmosphere influence the Earth’s climate in a direct as well asindirect manner. Direct effects refer to the interaction of the sus-pended particles with the radiation field in the atmospherewhereas indirect effects refer to the effects of particles on cloudprocess, which in turn affect climate. Aerosol single scatteringalbedo u, which is the ratio of scattering to extinction, is animportant parameter in climate modeling (Bodhaine, 1995). It isone of the most important factors dictating aerosol radiative effects(Gelencser, 2004) and also determines the relationship betweensatellite measured radiance and aerosol optical depth (Russell et al.,2002). In fact, it has been estimated that a change in SSA from 0.9 to0.8 can sometimes change the sign of radiative forcing fromnegative to positive, depending on the surface albedo and theaerosol optical depth (Hansen et al., 1997). It also influences directlythe diffuse radiation, since it describes the fraction of the scattered

photons in a beam to the total attenuation (scatteringþ absorption)(Bais et al., 2005).

There are several ways in which SSA has been estimated inliterature for column as well as surface and layered aerosols in theatmosphere. Based upon the methods used, these estimates can bebroadly categorized into five groups: (i) using direct solar radiativeflux and broadband downwelling total solar radiation measure-ment (Herman et al., 1975; Zhao and Li, 2007), (ii) using ground andsatellite measurements coupled with the radiative transfer oraerosol model (Devaux et al., 1998; Hignett et al., 1999; Petterset al., 2003; Bais et al., 2005; Lee et al., 2007), (iii) using sun/skyradiance measurements (Nakajima et al., 1996; Dubovik et al.,2000), (iv) using calculations from Mie theory with inputs foraerosol composition, their chemical analysis and size distribution(Ramachandran et al., 2006) and (v) using simultaneous measure-ments of aerosol scattering and absorption (Bodhaine, 1995; Hegget al., 1997; Ganguly et al., 2005). While the flux and sun/skyradiance based measurements have the advantage of estimatingSSA for the column aerosols in its unperturbed state, the methodusing simultaneousmeasurements of scattering and absorption hasthe advantage of providing a more direct way of measuring SSA.The later technique has further advantage that it can be used inflight-based observations to get vertical profiles or layer averagedSSA values in the atmosphere.

* Corresponding author.E-mail address: ssingh@mail.nplindia.ernet.in (S. Singh).

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At any given location or region the value of SSA may be greatlyaffected by the presence of absorbing and scattering aerosolparticles and their variation during different seasons. At Delhi,which is a highly pollutedmega-city, most of the aerosols are eitherlocally produced by extensive urbanization, industrialization,construction activities, increased vehicular pollution, biomassburning or transported from large arid and semi-arid regions innorthewest part of India (Khillare et al., 2004). In the present paperwe have estimated the single scattering albedo from simultaneoussurface measurements of absorption and scattering coefficient atDelhi during the year 2008e2009. The emphasis is on the variationof the SSA during different seasons arising mainly due to the desertdust loading during pre-monsoon and dominance of local pollutionduring winter. Along with the SSA estimation at 550 nm we alsoreport the variation of Angstrom absorption exponent (AAE) overDelhi throughout the year. The behaviors of SSA and AAE duringdifferent weather conditions like, rainy, cloudy, foggy and dustyhave also been discussed.

2. Instrumentations

Two important components of SSA estimation, the absorptionand the scattering coefficients were measured using co-locatedinstruments, Aethalometer (AE-42, Magee Scientific) and Nephe-lometer (NGN-3A, OPTEC Inc, USA) respectively. The Aethalometermodel AE-42 manufactured by Magee scientific, California, USAoperates at seven wavelengths of 370, 470, 520, 590, 660, 880, and950 nm, based upon the principle of differential transmission oflight through the aerosol particles accumulated on a quartz-fiberfilter. The measurement of the attenuation of light beam is linearlyproportional to the amount of BC deposited on the filter strip. Moredetails about the Aethalometer instrument can be found at http://mageesci.com/Aethalometer_book_2009.pdf and also by Hansen(1996). The limitations of the instrument have been discussed indetail by Bodhaine (1995), Weingartner et al. (2003) and Arnottet al. (2005). In the present experiment Aethalometer was runwith a time base of 5 min and a flow rate of 2 l per minute.

The NGN-3A integrating nephelometer measures the scatteringcoefficient of a known volume of air sample at 550 nm. Thisinstrument draws the ambient air with a PM2.5 size-cut spiralsampler inlet to allow particles up to 2.5 m in diameter. The air isdrawn into a temperature-controlled scattering chamber, whichis illuminated by a flash lamp, and the scattered light intensity ismeasured at 550 nm using a photomultiplier tube. This air volumeis illuminated by a near Lambertian diffuser made from an opalacrylic plastic with a cosq fall off. More specially, the diffuserradiates into a 2p steradian (180�) hemisphere, which is truncatedat 5� and 175� in the instrument. The scattering extinction coeffi-cient is thus deduced by measuring the scattered light over 170-degree angle. More details about the instruments are given at(http://www.optecinc.com/visibility/ngn-3a.htm).

In order to ensure that the absorption and scattering coefficientsare estimated for the same ambient air sample from the atmo-sphere, the air was drawn through a glass impinger with one endopening at the free air and the other attached to a low powerexhaust fan. A PM2.5 size-cut filter was also attached with theAethalometer in order to have the scattering and absorptionmeasurements for the similar sized particles. Both the instrumentswere run with the time base of 5 min. Zero air calibration for thenephelometer was done daily once at the start of the experiment orautomatically every 27 h. The accuracy of the scattering coefficientat the measured 550 nmwavelength is �7% of the true value for airnear Rayleigh with 2 min integration time. The measurements ofaerosol absorption coefficient and scattering coefficients thusobtained were used to estimate aerosol single scattering albedo, as

will be described later in Section 4. The measurements of temper-ature, winds, humidity and rain were done throughout the yearusing an automatic weather station, collocated with the othermeasurements.

3. Site location and meteorological conditions

All the measurements were done at the National PhysicalLaboratory (central Delhi; 28.38N, 77.10E, 235 masl), in the mega-city Delhi, the capital of India, in south Asian region. Delhi is situ-ated about 1100 Km from the nearest coast on the North ArabianSea. The area around Delhi falls on the border zone lying betweenthe rich rain-washed Ganges plains to the east and the semi-aridtracts of Rajasthan about 160 Km to the west and southwest. Thesoil around Delhi is dusty (Khemani et al., 1985). It has a semi- aridclimate with extreme weather conditions. During peak summers,temperature rises even beyond 45 �C and in winter temperaturesmay fall to below 3 �C. In the pre-monsoon period (AprileJune),frequent dust storms from western and north to western desertregions cause large scale loading of aerosols over Delhi (Singh et al.,2005; Prasad et al., 2007; Pandithurai et al., 2008). The rainy seasonis from July to September when the climate sometimes becomesvery humid. In the present study, the annual data (from April 2008toMarch 2009) has been classified into four seasons, namely Spring(FebruaryeMarch), Summer (AprileJune),Monsoon (JulyeSeptember)and Winter (OctobereJanuary) on the basis of the existing meteo-rological conditions.

The meteorological parameters like wind speed, temperature,relative humidity and rainfall were measured at the site using anautomatic weather station. Fig. 1 represents the annual variation ofabove meteorological parameters plotted as monthly means. Thevertical bars denote the �1s standard deviations from the monthlymean. Themonthly averagewind speed during the observationwasfound to be generally below 1 m s�1 except for the months of Apriland May when it reached above 1.5 m s�1. The lowest wind speedwas observed during post-monsoon (October and November)season. Apart from the monsoon season, winds are mostly fromwesterly or north-westerly direction. Easterly and South Easterlywinds are more common in the monsoon season. The relativehumidity was always more than 35% during the study, mostly lyingin the range 40e80% during summer and above 85% during

Fig. 1. Variation of monthly averaged Wind Speed, Temperature, Relative humidity,and the total monthly rainfall during the April 2008eMarch 2009 over Delhi.

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monsoon season. In winters RH increased up to 80% and in spring itreduced to about 50%. The average temperature varied between12 �C and 33 �C and total annual rainfall over Delhi was about800 mm. Most of the rains occurred during JulyeAugusteSeptember and OctobereMarch was almost dry. Average monthlytemperature decreased gradually from October to reacha minimum in January and again started rising till April. Sucha variation in weather condition has a strong bearing on the SSAobserved over Delhi, as we will see later in the text.

4. Methodology

Scattering coefficient (ssca) was obtained directly at 550 nmusing the Nephalometer instrument described earlier. As the directmeasurement of absorption coefficient (sabs) is not available at550 nm so the seven channel aethalometer data was used to esti-mate the sabs at 550 nm. In order to do this the absorption coeffi-cients obtained at seven wavelengths 0.37, 0.47, 0.52, 0.59, 0.66,0.88 and 0.95 mm were used to estimate the Angstrom absorptionexponent (as(abs)) employing Angstrom relation (Anderson et al.,2005).

asðabsÞ ¼ �dlogðsabsÞdlogðlÞ (1)

Where, as(abs) is the Angstrom absorption exponent (AAE), l iswavelength in mm, and sabs is absorption coefficient in Mm�1. Theas(abs) thus obtained is used in the Angstrom relation(sabs(l) ¼ babs l�a) to obtain the absorption coefficient at therequired 550 nm. On the basis of the absorption coefficient,sabs(0.52), measured at 520 nm and the Angstrom absorptionexponent as(abs) estimated above, the absorption coefficient at550 nm, sabs(0.52), was calculated, as

sabsð0:52Þsabsð0:55Þ

¼ ð0:52Þ�a

ð0:55Þ�a (2)

Thus we have obtained the aerosol absorption coefficient (sabs)and scattering coefficient (ssca) at the same wavelength of 550 nm.The scattering and absorption coefficients were measured every5 min and the hourly averaged data sets were used to estimate thesingle scattering albedo (SSA) at 550 nm. The SSA was estimatedusing the standard relation

u ¼ sscaðlÞsscaðlÞ þ sabsðlÞ

(3)

It is important to note that the estimation of absorption coeffi-cients from the filter based attenuation measurements has somelimitations (Bodhaine, 1995; Weingartner et al., 2003; Arnott et al.,2005; Corrigan et al., 2006). They arise mainly due to (i) ‘shadowingeffect’ that refers to the reduction in the optical path in theAethalometer filter with an increasing filter load, and (ii) multiplescattering of light in the fiber matrix of the filter. Due to this thetrue aerosol absorption coefficient sabs may be different from theobserved absorption coefficients by Aethalometer, sABS. To accountfor these effects, Weingartner et al. (2003) have given an empiricalrelation

sabs ¼ sABSð1=C*RABSÞ (4)

where, C is the calibration factor greater than unity taking care ofthe multiple scattering of the light beam at the filter fibers in theunloaded filter and RABS is the empirical function due to the‘shadowing effect’ caused bymultiple deposition of aerosol layer onthe filter fiber. In the present case, manufacturer supplied value ofC ¼ 1.9 has been used to estimate sabs at 550 nm. Similar value of

C ¼ 1.9 was also obtained by Bodhaine (1995) at this wavelength(550 nm). Weingartner et al. (2003) have also found this value toagree well with their experiments on different kinds of aerosols inthe laboratory. However, it is to be noted that in order to directlyobtain the absorption coefficients at 520 nm from the Aethalometerinstrument a correction has been applied in the value of C based onBodhaine (1995). This was obtained by fitting the values of C atdifferent wavelengths and then finding the corresponding value at520 nm. The mapping function obtained after the fit is given byC ¼ 4.4305e5.6722*exp (�l/0.6814), where l is the wavelength inmicrometer. The value of C(520 nm)was thus found to be 1.79. Thusthe effect of multiple scattering in estimating absorption coefficientat 550 nm has been taken care of in this study.

Weingartner et al. (2003) also describes a method of parame-terization for the ‘shadowing effect’ (RABS), but it involves twoconcurrent aethalometers for measurements. Due to lack of otherinstrument this correction has not been attempted here presently.However, using a moderate value of fitting parameter f, used todescribe the shadowing effects (in equation (8)) of Weingartneret al. (2003) for the real aerosols as f ¼ 1.3, will lead to a reduc-tion in sabs value by w23%. As in the present case we are usingaverage of 1-h observation of every 5 min data the actual differencein sabs and sABS will be further minimized. Thus, as the uncertaintyof measurement in ssca is about 7% and assuming uncertainty insabs due to shadowing effects as w23%, the maximum uncertaintyin the SSA (u) calculation is estimated to be around 36%.

5. Results and discussion

5.1. Single scattering albedo and its variability

As a first step, the absorption coefficient (sabs) at 550 nm wasdeduced using the method described above. Then the scatteringcoefficients (ssca) observed at 550 nm were used to find the SSA at550 nm. A typical diurnal variation of these parameters has beenplotted in Fig. 2. Fig. 2a, b and c show the 24 h variation of sabs, sscaand SSA respectively, at Delhi on 31 March, 2009. The averagevalues of sabs, ssca and SSA during the whole day was found to be43.08 � 23.98 Mm�1, 78.77 � 41.06 Mm�1, and 0.65 � 0.07 Mm�1

respectively. The maximum values of scattering (163.6 Mm�1) andabsorption coefficients (103.8 Mm�1) prior to noonwere caused bylow mixing height resulting in high concentration of aerosols. Thesharply decreasing scattering and absorption coefficients pointedto the abruptly increasing vertical dispersion of pollutants due tointense solar heating. The minimum values of scattering(23.0 Mm�1) and absorption coefficients (9.5 Mm�1) during after-noon may be due to the fact that the mixing height becomes high

Fig. 2. Diurnal variation of scattering coefficient (a), absorption coefficient (b) andsingle scattering albedo (c) on a clear-sky day (31 March, 2009).

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and vehicle density becomes low during this period. The increasingtendency of scattering and absorption coefficients towards eveningwas due to decreasing mixing height in consequence of decreasingsolar intensity and increasing vehicular emission. On the otherhand, the scattering and absorption coefficients in the eveningwere much lower than those in the morning. This was due to thehigher ambient air temperature and thus, higher mixing height inthe evening than those in the morning.

The daily average values of sabs, ssca and SSA during the wholeyear of observation (Apr 1 2008eMar 31 2009) have been shown inFig. 3. The gap during September 27eNovember 3 was due to thebroken glass impinger that prevented simultaneous measurementsof Aethalometer and Nephelometer for the same air sample. Fig. 3indicates that the values of scattering and absorption coefficientsare low from April to September and increase from November toFebruary next year. The increase in SSA is however only marginal,which increases from 0.66 to 0.73 in terms of average values duringthe two periods.

In order to see the variation of SSA during the year in detail wehave divided the whole year into four dominant seasons e summer(AprileJune), monsoon (JulyeSeptember), winter (Novem-bereJanuary) and spring (FebruaryeMarch). Fig. 4 shows the dailyaverage variations of sabs, ssca and SSA in these four seasons. Thevertical bars denote the �1s standard deviations from the dailymean values. The average values of scattering coefficients duringthe four seasons, summer, monsoon, winter and spring were foundto be 110.46 � 36.15, 95.34 � 49.46, 565.59 � 274.59 and236.56 � 96.25 Mm�1 respectively. The corresponding values forthe absorption coefficients during the four seasons were 62.47 �21.27, 50.95 � 43.61, 189.65 � 85.94 and 90.65 � 33.06 Mm�1

respectively. The present observation shows that though theabsorption coefficient from summer to winter increased by almostthree times (from 62.47 to 189.65 Mm�1), the increase in scatteringcoefficient was much more, almost five times (110.46e565.59

Mm�1), giving rise to an increase in SSA value during winters. Inthis study, the average SSA at 550 nm at Delhi during the fourseasons, summer, monsoon, winter and spring were found to be0.63 � 0.06, 0.69 � 0.07, 0.74 � 0.03 and 0.72 � 0.04 respectively. Itis obvious from above that the highest values of scattering andabsorption coefficients along with SSA are observed in the winterseason. These values decrease gradually during spring, summer andmonsoon seasons.

The SSA at 550 nm not only shows strong seasonal and day-to-day variations over Delhi but also a large fluctuationmay be noticedduring the daytime. Fig. 5 shows the daytime average hourly vari-ation of sabs, ssca, and SSA during morning 09:30 h to evening21:30 h during the whole season. Each point in the graph repre-sents an average of 1 h during the whole season centered at thetime shown on x-axis. It can be noticed that during almost all theseasons the scattering and absorption coefficients had high valuesbefore noon which gradually decreased and became minimumduring the afternoon. The scattering and absorption coefficientsagain showed an increasing tendency in the late afternoon. Similardiurnal variations in scattering and absorption coefficient have alsobeen observed at Kathmandu valley (Sapkota and Dhaubhadel,2002) and at Ahamdabad (Ganguly et al., 2006a). It is observedfrom Fig. 4 that starting from a high in early hours, absorptioncoefficient (sabs) and scattering Coefficient (ssca) decreasedcontinuously as the day advanced and again started increasingduring late afternoon around 16:30 h in all the four seasons. On theother hand opposite trends were observed in SSA in all the fourseasons. The diurnal variation of sabs, ssca and SSA seems to belargely controlled by the mixing layer height variation and thevehicular concentration. It may also be affected by the generation ofsecondary aerosols like SO4

2�, and NO3� released by the anthropo-

genic sources (SO2 and NO2) during daytime. Both NO3� and non-sea

salt SO42� may be mainly produced as secondary aerosols in the

process of coal combustion, biomass burning and vehicular

Fig. 3. The daily average values of sabs, ssca and SSA during the whole year of observations (Apr 1 2008eMar 31 2009).

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emissions (Seinfeld and Pandis, 1998; Rastogi and Sarin, 2005)which may contribute to the variation in SSA during daytime.

It can also be noticed from Figs. 4 and 5 that the scattering andabsorption coefficients both are comparatively very high duringwinters and go on decreasing gradually during spring, monsoonand summer seasons. There are several reasons for higher

scattering and absorption coefficients of aerosols over Delhi duringwinters. During winters the atmospheric boundary layer and windspeed is low (Fig. 1), at the same time the wood, waste and coalburning increases (Khillare et al., 2004). Also the concentration ofSO4 and NH4 increases duringwinters due to transport of pollutantsfrom thermal power plants due to prevailing north westerlies. It is

Fig. 4. Seasonal variation of sabs, ssca and SSA during summer, monsoon, winter and spring. The vertical bars denote the �1s standard deviations from the daily mean values.

Fig. 5. Daytime variation of sabs, ssca and SSA during summer, monsoon, winter and spring seasons. The vertical bars denote the �1s standard deviations from the mean values.

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estimated that the total amount of fly ash from three power plantsis about 6000 tonnes per day (Srivastava and Jain, 2007). Also, theair masses reaching the area during this period have to travel longerover land than the monsoon season. In addition the occurrence ofrain is infrequent as compared with the monsoon season anda higher level of aerosol content is maintained in the atmosphere(Khemani et al., 1985). Thus the concentration of both, scatteringand absorption components of the aerosol increases during wintersleading to high scattering and absorption coefficients. Moreoverduring dry seasons (October 2008eMarch 2009) average concen-trations of Naþ, Mgþ and Cl� decreases and non-sea salt compo-nents of Kþ, Mg2þ, Ca2þ and SO4

2�, which have scattering nature,increases (Rastogi and Sarin, 2005), therefore in winter scatteringcoefficient increases more than the absorption coefficient. Asa result SSA increases in dry winter seasons in comparison to otherseasons.

The concentration of aerosol during the summer (AprileJune) ischaracterized by continental westerlies and in this period,a thermal low is located at the surface in northwest India andadjoining Pakistan. As a result, aerosols of local and land origin arecontinuously lifted up and a high level of aerosol concentration ismaintained in the atmosphere. Rainfall occurs occasionally but theoccurrence of dust storms is frequent during this period. Thesefeatures account for the high aerosol concentration in summerseason .The concentrations of soil-oriented components (Ca and Kwhich have absorbing nature) increase by 20e70% (Khemani et al.,1985) during summer owing to the high level of total suspendedparticulate (TSP). As a result the scattering coefficients and the SSAare low during summer season. During monsoon the concentra-tions of sea salt (Na, Cl, Mg) are found to increase slightly by about10e18% due to the flow of maritime air into the region. Furthermore, during monsoon period trough line runs close to Delhi andthough some aerosol is picked up while passing over relatively dryregions, the air masses becomes washed-out of aerosols beforereaching Delhi. Also the occurrence of rain is frequent and washouteffects are highest. Therefore, aerosols and soil-oriented elementsare on the average very low during the monsoon (Khemani et al.,1985). As we know that water-soluble inorganic compounds suchas sulphates, nitrates etc. and some organic carbon (OC) mainlyscatter radiation and black carbon and dust particles haveabsorbing nature (Charlson et al., 1992; Penner et al., 1994). Thecomplex combination of water soluble, insoluble and BC aerosolsduring this season may be giving rise to SSA that is comparativelyless than that during winter but slightly higher than that in thesummer season.

When compared with other Indian cities, the SSA values overDelhi are slightly low. It can be compared with clean sites likeManora Peak in Himalayas which had SSA in the range 0.87e0.94(Pant et al., 2006) and over Bay of Bengal where it was in the range0.84e0.96 (Nair et al., 2008). However, our values are comparablewith the SSA obtained in the Indo-Gangetic plain at Kanpur (0.76),a city about 200 km from Delhi (Tripathi et al., 2005a). These valuesare slightly lower than the values of SSA obtained during differentseasons at another Indian city Ahmedabad reported by Gangulyet al. (2006a). They have reported SSA at 0.525 mm to be0.73 � 0.1, 0.84 � 0.04, 0.81 � 0.03 and 0.73 � 0.08 during dry, pre-monsoon, monsoon and post-monsoon seasons, respectively. A fewprevious estimates of SSA over Delhi during summer (pre-monsoon) by Singh et al. (2005) and Pandithurai et al. (2008) havealso indicated low SSA values of the order of 0.67 and 0.79respectively. The absorbing nature of the Indian desert dust has alsobeen reconfirmed recently by Moorthy et al. (2007) who concludedthat the dust over Indian desert is of more absorbing naturecompared with the pure dust. During winters of December 2004,Ganguly et al. (2006b) have also estimated SSA at 0.525 mm at Delhi

using similar surface measurements and fount it to be in the range0.6e0.8 with an average value close to 0.68.

The SSA estimated presently with the surface measurements ofabsorption and scattering coefficients when compared with theother SSA estimates using column measurements shows variedresults. For example, the sky-radiometer (manufactured by PREDELtd.) estimation of SSA over Delhi by Pandithurai et al. (2008)shows the monthly average SSA values to be 0.84, 0.78, 0.75 and0.74 for March, April, May and June 2006, respectively. The valueswe have measured for these months during the year 2008e09 are0.71, 0.67, 0.63 and 0.62 respectively. In a recent study, Singh et al.(2010) have also estimated the SSA over Delhi during the year 2006using the OPAC model and the surface observations. They havefound SSA for these months (MarcheJune) to be 0.82, 0.77, 0.78 and0.78 respectively. When these values are compared with the Kan-pur AERONET monthly average values for the same months, April,May, June 2008 and March 2009 then these values at 558 nm (forthe wavelengths averaged at 441 nm and 676 nm) are compara-tively higher at 0.89, 0.90, 0.90 and 0.89 respectively. Previousobservations with the AERONET at Kanpur by Dey et al. (2004) havealso shown nearly similar values during 2001 and 2002. The AER-ONET derived SSA is also available at Delhi for the three monthsJanuaryeMarch 2009 which has an average value of 0.93, 0.89 and0.90 respectively. Our surface measured values for these monthsaverage at 0.75, 0.74, and 0.74 respectively. The AERONET Kanpurand Delhi monthly average SSA was downloaded from http://aeronet.gsfc.nasa.gov/ for version 2 inversion products. Thus it isgenerally found that the SSA estimated at 550 nmwith the surface

Fig. 6. Mean spectra of aerosol absorption coefficient as observed during differentseasons of the year.

Fig. 7. Daily variation of average Angstrom absorption exponent (AAE) at surface alongwith the column AOD at 500 nm and a during the study period April 2008eMarch2009.

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measurements of scattering and absorption coefficient is about20e30% less than the column measured SSA values. This may beprimarily due to the fact that SSA in the present case is limited toPM2.5 aerosols only and also due to the relatively high concentra-tion of BC near the surface.

5.2. Absorption coefficient and Angstrom absorption exponent

As the aethalometer AE-42 gives absorbance data at the sevenwavelengths 370, 470, 520, 590, 660, 880, and 950 nm, it can beused to study the wavelength dependence of absorption coeffi-cients. It is usually investigated using the power lawsabs(l) ¼ babs l

�a, where a or more precisely, as(abs) in this case, isthe Angstrom absorption exponent (AAE) and is a measure ofspectral dependence of aerosol absorption. In the present case allthe wavelengths i.e., 370e950 nm have been used to estimate theAAE. The absorption coefficients have been estimated at the sevenwavelengths using the aethalometer absorbance data following themethod of Bodhaine (1995). Fig. 6 shows the average spectral

variation of absorption coefficients during four seasons for all thedata during the study period. The vertical lines indicate the �1sdeviation from the mean value during the season. Fig. 6 clearlyshows that the absorption coefficients at all the wavelengths arehighest during winters, which gradually decrease as the spring,summer, and monsoon seasons follow. This variation in theabsorption coefficient is in line with the BC mass concentration (at880 nm) in the aerosol. In addition, it also shows that the absorbingcapacity of the aerosol in general increases at shorter wavelengths,particularly during the winter season. Ganguly et al. (2006a) havealso reported similar observations from Ahmedabad.

The spectral and seasonal behavior of the absorption coefficientcan be more effectively characterized by the Angstrom absorptionexponent, as(abs) which is estimated by fitting the Angstrom powerlow into the spectral variation of absorption coefficient. Fig. 7shows the average daily variation of Angstrom absorption expo-nent (AAE) during the whole year of observation along with theAOD (500 nm) and the column Angstrom exponent (a). TheAngstrom exponent awas retrieved by least square fit on a logelogscale plot of the observed AOD versus wavelength following theAngstrom power law for variation of AOD with wavelength. In thepresent case AODmeasurements at 340, 500, 675, and 870 nm havebeen used to estimate a. The AOD at 1020 nmmay be contaminateddue to the absorption of water vapor in the column and therefore ithas been excluded in the calculation of a. It is to be noted that theAngstrom exponent is a rough indicator of the size distribution ofthe aerosol particles in the column whereas the AAE which givesthe wavelength dependence of absorption tells about the nature ofabsorbing aerosols (BC, organic matter and dust). A low a value(<1) indicates dominance of bigger-size particles and a high a (>1)

Table 1Optical properties (Mean � Standard deviation) at Delhi for different weatherconditions during April 2008eMarch 2009.

SSA (Surface) AAE (Surface) AOD a

Rainy (23) 0.62 � 0.07 0.94 � 0.08 e e

Cloudy (58) 0.70 � 0.07 1.03 � 0.07 e e

Clear Sky (26) 0.72 � 0.04 1.08 � 0.09 0.56 � 0.18 0.75 � 0.22Foggy (21) 0.76 � 0.03 0.99 � 0.10 0.98 � 0.35 0.96 � 0.10Dusty (8) 0.71 � 0.04 1.04 � 0.07 0.84 � 0.13 0.85 � 0.08

Fig. 8. Daytime variation of Angstrom absorption exponent (AAE) averaged over the four seasons of the year.

K. Soni et al. / Atmospheric Environment 44 (2010) 4355e4363 4361

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indicates dominance of smaller-size particles (Dubovik et al., 2002).Similarly, AAE value close to unity indicates BC from the fossil fuelburning and a large AAE value indicates absorbing aerosols frombiomass/biofule burning (Kirchstetter et al., 2004; Russell et al.,2010).

Annual mean value of AAE during the whole period of obser-vation is found to be 1.03� 0.09, which is more or less same duringall the four seasons. It can be seen from the Fig. 7 that the AAEremains generally close to unity throughout the year but showsslight enhancements during AprileMay and early November.During AprileMay, the summer season, AOD values are high andare associated with very low a values due to abundance of dustaerosols. During November AOD is again high but coupled withhigh a values, indicating abundance of fine mode smoke particlesthat dominate during this period due to bursting of fire crackersduring festival season. Slight enhancements in AAE duringAprileMay may be due to the increase in absorbing dust and inNovember it may be due to increased smoke in the atmosphere. TheJuneeAugust period was largely cloudy during which the sky wasnot clear enough for the column AOD measurements usingMICROTOPS.

Apart from the seasonal variabilityof the SSA, AAE, AOD and a,all these optical parameters showed considerable variation duringdifferent weather conditions as well. These parameters for clear-sky conditions have been comparedwith the rainy, cloudy (no rain),foggy and dusty weathers and summarized in Table 1 as average�1s standard deviations. The numbers in bracket indicate thenumber of days the averaging was done. AOD and a were notpossible during rainy and cloudy conditions. It can be seen that theSSA during rainy and cloudy conditions are less than the SSA duringclear-sky conditions whereas, during foggy and dusty conditionsSSA is more than the clear-sky SSA. This suggests that moreabsorbing particles exist under rainy and cloudy conditions thanthose under foggy and dusty conditions. Similar observations havealso been reported from Beijing, China by Wang et al. (2009). Anincrease in SSA due to dust has also been observed by Tripathi et al.(2005b) at a nearby location Kanpur.

Fig. 8 shows the daytime variation of AAE averaged over the fourseasons separately. The seasonal AAE values are close to unity withaverage values being 1.02 � 0.08, 1.02 � 0.10, 1.04 � 0.11, and1.03 � 0.05 during summer, monsoon, winter and spring seasonsrespectively. The close to unit value of AAE shows a weak spectraldependence (l�1) for the absorption of aerosols. This is typical fora mixture of aerosol in which absorption is mainly due to BC fromthe fossil fuel burning (Jacobson, 2000; Bond, 2001; Bergstromet al., 2002). On the other hand a strong spectral dependence inabsorption (l�2.5) indicates the dominance of biomass or firewoodgenerated aerosols (Kirchstetter et al., 2004).

The value of AAE close to unity can be seen in the light of the factthat the vehicular pollution totally dominates among all the sour-ces (thermal power plant, solid waste, industries, soil etc) in all theseasons over Delhi (Srivastava and Jain, 2007). This is different fromAhmedabad, where the AAE values were reported to be 2.2, 2.0, 1.9,and 2.1 during dry, pre-monsoon, monsoon and post-monsoonseasons respectively (Ganguly et al., 2006a). These high values theyhave attributed to the biomass/biofuel burnings in all the seasonsthere. On the other hand the weak spectral dependence of l�1 atDelhi throughout the year shows that the absorption is mainly dueto the BC in the aerosol. In a study Kirchstetter et al. (2004) havealso shown that the extraction of organic carbon from the aerosolsample by removing biomass burning aerosol reduced the spectraldependency in absorption and reduced the AAE value to close tounity. Thus, a close to unity value of AAE over Delhi indicates thatthe aerosols are by and large deficient in OC and abundant in BCcontent, perhaps mainly originated from the fossil fuel burning.

6. Summary and conclusions

The yearlong study of aerosol single scattering albedo at the midvisible wavelength 550 nm and the Angstrom absorption exponentin the PM2.5 aerosols over Delhi has revealed many interestingfeatures. The annual averaged value of SSAwas 0.70� 0.07 and onlyslight variations were seen in the average value during the fourseasons, summer (0.63 � 0.06), monsoon (0.69 � 0.07), winter(0.74 � 0.03) and spring (0.72 � 0.04). The absorption and scat-tering coefficients at the same wavelength however showedconsiderable variations. The average absorption coefficient duringthese four seasons were 62.47 � 21.27, 50.95 � 43.61,189.65 � 85.94 and 90.65 � 33.06 Mm�1 respectively whereas thecorresponding values for the scattering coefficients were found tobe 110.46 � 36.15, 95.34 � 49.46, 565.59 � 274.59 and 236.56 �96.25 Mm�1 respectively. In addition to seasonal variability, SSA,sabs and ssca also showed considerable diurnal and intra-dayvariations. The SSA generally had a tendency to decrease in theevening. The annually averaged value of SSA in the present case forthe whole observation was found to be at 0.70 � 0.07, this meansabout 70% scattering and 30% absorption. The average SSA studiedduring different weather conditions also suggests that moreabsorbing particles exist under rainy and cloudy conditions thanthose under foggy and dusty conditions. One of the most inter-esting results of this study is the value of Angstrom absorptionexponent, which was found close to unity throughout the year,strongly indicating that the absorption at Delhi aerosol is mainlydue to the abundance of black carbon of fossil fuel origin.

Acknowledgements

We thank the PIs B.N. Holben & S.N. Tripathi and PhilippeGoloub and their staffs for establishing andmaintaining the Kanpurand New Delhi AERONET sites used in this investigation. We arealso thankful to the two anonymous reviewers for their valuablesuggestions and comments in improving the manuscript.

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