Download - A Study of Aerosol Properties over Lahore (Pakistan) by Using AERONET Data

Asia-Pac. J. Atmos. Sci., 50(2), 153-162, 2014

DOI:10.1007/s13143-014-0004-y

A Study of Aerosol Properties over Lahore (Pakistan) by Using AERONET Data

Muhammad Ali, Salman Tariq, Khalid Mahmood, Asim Daud, Adila Batool, and Zia-ul-Haq

Department of Space Science, University of the Punjab, New Campus, Lahore, Pakistan

(Manuscript received 1 March 2013; accepted 24 July 2013)© The Korean Meteorological Society and Springer 2014

Abstract: It is well established that aerosols affect the climate in a

variety of ways. In order to understand these effects, we require an

insight into the properties of aerosols. In this paper we present a study

of aerosol properties such as aerosol optical depth (AOD), single

scattering albedo (SSA) and aerosol radiative forcing (ARF) over

mega city of Lahore (Pakistan). The data from Aerosol Robotic Net-

work (AERONET) have been used for the period December 2009 to

October 2011. The seasonal average values of AOD, asymmetry

parameter (ASY) and volume size distribution in coarse mode were

observed to be highest in summer. On the other hand, the average

values of Angstrom exponent (AE) and imaginary part of refractive

index (RI) were found to be maximum in winter. The average value

of real part of RI was found to be higher in spring than in all other

seasons. The SSA exhibited an increasing trend with wavelength in

the range 440 nm - 1020 nm in spring, summer and fall indicating the

dominance of coarse particles (usually dust). However, a decreasing

trend was found in winter in the range 675 nm - 1020 nm pointing

towards the dominance of biomass and urban/industrial aerosols. As

far as aerosol radiative forcing (ARF) is concerned, we have found

that during the spring season ARF was lowest at the surface of Earth

and highest at top of the atmosphere (TOA). This indicates that the

atmosphere was warmer in spring than in all the remaining seasons.

Key words: AERONET, aerosol properties, Lahore

1. Introduction

Considerable uncertainties exist in the prediction of global

climate change due to highly variable spatio-temporal distribu-

tion and poor understanding of optical properties of atmospheric

aerosols (IPCC, 2001). Therefore, effects of aerosols on climate

can be better understood if the spatial as well as temporal

distribution and optical properties of aerosols are accurately

known. Aerosols interact directly by scattering and absorbing

solar radiation whereas indirect effects refer to the influence of

aerosols on cloud processes. Atmospheric aerosols influence

the radiation budget and affect the hydrological cycle (Twomey,

1977; Coakley et al., 1983; Charlson et al., 1992; Rosenfeld

and Lensky, 1998; Ramanathan et al., 2001a; Lohmann and

Feichter, 2005). Satellite remote sensing (SRS) has the cap-

ability to measure extremely variable aerosol fields on global

scales for longer periods (IPCC, 1995). However, the surface

reflectance of Earth causes the measurement of aerosol con-

tribution to have low accuracy (Kaufman et al., 1997; King et

al., 1999). Even though the results obtained from satellite

observation of aerosols have been improved by the use of more

sophisticated instruments, the discrepancies between various

satellite products indicate that inaccuracies still exist in SRS

techniques (Zhao et al., 2005). Therefore, a precise and com-

prehensive study of the optical properties and other charac-

teristics of aerosols is not possible only with the available

satellite data. In contrast, the ground based aerosol remote sen-

sing, though does not provide global coverage, yields authentic,

detailed and continuous information about aerosol properties

(Dubovik et al., 2002a). The Aerosol Robotic Network

(AERONET), which is a ground based sun and sky scanning

automated radiometer, measures various properties of atmos-

pheric aerosols (Holben et al., 1998).

Rapid increase in population and urban sprawl has led to

appreciable increase in aerosol loading over Pakistan. Owing

to large anthropogenic emissions, the densely populated areas

of Pakistan experience pollution with high amounts of particu-

late matter. Very few analyses have been conducted over

Pakistan to investigate optical properties of aerosols using

remote sensing techniques (e.g., Alam et al., 2010, 2011a, b,

2012). At present, there exists only one study on Lahore using

AERONET data conducted by Alam et al. (2012) in which

aerosol optical and radiative properties have been discussed

during only summer and winter seasons of 2010-11. These

authors have studied the aerosol optical and radiative pro-

perties by analyzing the measurements (level 1.5) for only six

months (April-June, 2010 and December 2010 to February

2011). However, in terms of climatic studies, we need an im-

proved understanding of aerosol properties and radiative forcing

based on long-term observations that should include variations

in all the four seasons (Yu et al., 2011).

The main objective of the present work is to study the aerosol

properties by analyzing the AERONET measurements over

mega city of Lahore for a relatively longer period (~2 years)

by considering variations in all the four seasons. In this study

we have used all the available AERONET data (level 2.0) for

the period December 2009 to October 2011 to analyze the

aerosol optical depth (AOD), Angstrom exponent (440/870)

(AE), volume size distribution, single scattering albedo (SSA),

real and imaginary parts of refractive index (RI), asymmetry

parameter (ASY) and aerosol radiative forcing (ARF). We

have also compared the AERONET data with satellite based

Corresponding Author: Salman Tariq, Department of Space Science,University of the Punjab, New Campus, 54590 Lahore, Pakistan.E-mail: [email protected]

154 ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES

measurements over Lahore, a location in the central region of

Pakistan.

2. Site and instrumentation

a. Site description

Pakistan is situated in South Asia having an area of about

796,100 sq. km. It shares its borders with India to the east,

Afghanistan and Iran to the west and People’s Republic of

China to the far northeast. The southern part of the country is

bounded by a coastline of about 1046 km along the Arabian

Sea and gulf of Oman. Geographically, Pakistan is divided into

three main areas: the northern highlands, the Indus river plain

and the Baluchistan plateau. Pakistan is a sub-tropical and

semi-arid country with a mid-summer monsoon from July to

September. This region has a unique weather on account of

monsoon and associated winds that reverse direction seasonally

(Satheesh and Moorthy, 2005).

Lahore (31o 32'N; 74o 22'E) is the capital of province of

Punjab and the second largest city of Pakistan with a popu-

lation of almost 10 million. It lies in the central region of the

Punjab province, which is the most thickly populated area in

Pakistan. It is situated along the river Ravi and covers an area

of about 2000 square kilometers (see Fig. 1). The major in-

dustries in and around Lahore include iron, chemicals, textile,

thermal power plants and automobiles. The main sources of air

pollution include automobile emissions, road dust and biomass

burning (Biswas et al., 2008; Alam et al., 2012). Out of the

four provinces, Punjab has about 26 percent of total area, yet

contains more than 50% of the total population and produces

more than 65% of the country’s food grain. The neighboring

Indian state of Punjab also produces two thirds of the India’s

total food grain and is often referred to as the country’s “bread

basket” (Sharma et al., 2010). In short, Lahore is surrounded

by a fertile land, both in Pakistan and across the border in

India, famous for producing wheat and rice.

b. Weather characteristics of the study area

The climate of Lahore can be classified as a semi arid

climate with rainy, long and very hot summers and usually dry

and cool winters. During the months of May, June and July the

weather of Lahore is extremely hot and it receives dust storms

followed by rainfall events. The monsoon starts with heavy

rainfall from late June to early September. The highest maxi-

mum temperature recorded so far is 48oC (in June) while the

lowest temperature recorded is −2oC (in January). The weather

of Lahore is very hot during the months of May, June and July,

when the average highest temperature is 41oC, while during

the months of December and January the average lowest tem-

perature is 5oC. The average seasonal temperature is minimum

during winter (13.8oC), while it is maximum in summer

(31.3oC). For spring and fall, we have moderate temperatures.

It has an annual rainfall of 489 mm with heavy rainfall occurring

during the monsoon season i.e., from late June to September.

Mean annual relative humidity is 37.9% and on monthly basis,

it ranges from 20% in May to 58% in August. Keeping in view

the existing meteorological conditions at Lahore, four dominant

seasons have been defined according to the following months:

Fig. 1. Map of Lahore showing the AERONET site, major roads and its location in Pakistan.

28 February 2014 Muhammad Ali et al. 155

winter (December to February), spring (March to May), sum-

mer (June to August), fall (September to November). The

seasonal characteristics of Lahore weather for the study period

have been summarized in Table 1, except for the dust storm

frequency that has been deduced from available data of 60

years (1951-2010). The atmospheric pressure is minimum in

summer (1000.3 hPa) with maximum rainfall (176.3 mm) occur-

ring during this season. The dust storm frequency is highest in

summer (48.3%), while during winters it is negligibly small

(1.5%).

c. Instrumentation

AERONET instrument provides the spectral data of direct

sun and sky radiances within spectral ranges of 340 nm -

1020 nm and 440 nm - 1020 nm respectively (Holben et al.,

1998). The particle size distribution, SSA, and RI have been

acquired from sky radiance measurements (Dubovik and King,

2000). The details of AERONET instrument and data regis-

tration have been given by Holben et al. (1998), while a brief

description can be found in Eck et al. (2003). The AERONET

data are available at three levels i.e., level 1.0 which is un-

screened, level 1.5 which is cloud screened and level 2.0

which is quality assured (Holben et al., 1998; Smirnov et al.,

2000). In the present study quality assured data (level 2.0)

have been used from both direct sun (AOD and AE) and

inversion products (SSA, ASY, RI), for the period December

2009 - October 2011.

3. Results

a. Aerosol optical depth, Angstrom exponent and water vapor

content

The aerosol optical depth (AOD) is the most important

variable to remotely estimate the atmospheric aerosol loading

from ground-based instruments (Holben et al., 2001). Figures

2a-c show monthly mean values of AOD, AE and WVC ob-

tained over Lahore for the period December 2009 to October

2011. The general trend indicates an appreciable seasonal

variability in all the three parameters. The maximum AOD

value of 1.02 ± 0.41 was observed in July, and the next highest

value of 0.85 ± 0.42 occurred in June (Fig. 2a). On the other

hand, the minimum value of AOD at Lahore was observed to

be 0.47 ± 0.26 in February, indicating that the atmosphere over

Lahore was cleanest during this month. This is well justified

by the fact that with the rise in temperature, there is substantial

reduction in heating fires during February. Thus, the fraction of

fine mode particles decreases over Lahore and a small decrease

in the average value of AE for the month of February supports

this explanation (Fig. 2b). The gradual increase in AOD from

March to June (spring) is associated with the pre-monsoon

dust activity. During this period the gradual increase in tem-

perature, windspeeds and dust storm frequencies (Table 1) is

responsible for increased AOD loading over Lahore. The con-

tinuous decrease in AE during the period March-May (Fig. 2b)

is attributed to the increase in dust (coarse particles) loading.

Thus, during the spring season the AOD increases gradually

from March to May while the AE decreases. As the summer

season (June-August) starts the AOD further increases (due to

increase in temperatures and dust storm frequency, as indicated

in Table 1), reaching a maximum value of 1.02 in July and

Table 1. Meteorological conditions over Lahore.

Season Temperature oC Dew Point

oC Humidity MSL Pressure (hPa) Wind Speed (Km h

-1) Rain mm Dust Storm frequency

Winter 13.8 7.1 68.0 1016.1 12.1 8.8 1.5%

Spring 28.9 14.3 51.6 1006.7 26.6 7.4 37.7%

Summer 31.3 23.6 66.3 1000.3 16.5 176.3 48.3%

Fall 26.0 17.7 62.7 1009.8 4.6 40.5 12.6%

Fig. 2. Monthly average variations in the (a) AOD, (b) AE (440/870nm) and (c) WVC over Lahore during December 2009-October 2011along with the standard deviations.


then decrease to 0.71 in August. This abrupt decrease in the

mean AOD values in August is due to washout process by

rainfall events in the monsoon. A similar trend was observed by

Alam et al. (2010, 2011a) using MODIS data, while studying

seasonal variations in AOD for many selected cities of Pakistan

including Lahore. However, our results do not agree with those

of Alam et al. (2012) who obtained highest AOD over Lahore

in December (0.76 ± 0.35). This discrepancy has occurred

probably because, in their analysis, Alam et al. (2012) have

used the level 1.5 data for only six months and the data of July

2010, in which we obtained the maximum values of AOD, was

not included in their study period. In their previous analyses

over Pakistan using MODIS data for the periods 2001 - 2006

(Alam et al., 2010) and 2002 - 2008 (Alam et al., 2011b), it

was found that among all the cities studied, including Lahore,

the highest mean values of AOD were obtained during the

season of summer. Prasad et al. (2007), while investigating the

variations in aerosol loadings over Indo-gangatic plain, also

reported higher AOD values in summer than in all other

seasons. In recent studies of Eck et al. (2010) and Wang et al.

(2011) over another Asian site (Beijing, China) AERONET

AOD measurements were found to be maximum during sum-

mer and minimum during winter.

In Fig. 3, we have compared the seasonal AOD values over

Lahore obtained by us using AERONET data (converted to

550 nm) with those obtained by Alam et al. (2010) for the

period 2001-2006 and Alam et al. (2011b) for the period 2002-

2008 using MODIS data. We notice that all the three results

agree with the common trend having lower AOD values during

winter and spring than summer and fall. We attribute the minor

disagreements to the annual variabililties of aerosol loadings

over Lahore, because we used the AERONET data for the

period December 2009 to October 2011, while Alam et al.

(2010, 2011b) used the MODIS data from 2001 to 2008.

During the months of December and January the wind speed

and dust frequency are lowest at Lahore and hence dust

particles originating from distant sources do not contribute to

AOD. Also local vehicular and industrial/urban aerosols settle

down quickly resulting in low AOD values. Nevertheless, due

to cold season, people normally use heating fires of wood,

dung and coal that produce substantial amount of smoke/black

carbon. Thus, during winter the atmosphere of Lahore is do-

minated by fine aerosol particles. The occurrence of highest

values of AE during December and January confirms this fact.

It is also evident from Fig. 3 that there is little variation in

AOD between winter and spring. After spring, it rises and

becomes maximum in summer and then drops in the fall

season. The occurrence of peak AOD values over Lahore

during the summer seasons can be well justified by many

factors. The well-known traditional sources of aerosol loadings

in this region include mineral dust transported from Thal,

Dasht (Iran) and Thar (India) deserts. In the central Punjab the

wheat harvesting starts usually by the end of April and it is in

the full swing during May. Thousands of harvesting machines

and wheat threshers run day and night so that the farmers may

get the crop collected and marketed as early as possible. The

fine particles of dust and crop residue are lifted by high-speed

winds and are driven to large distances, resulting in higher

AOD values. Thus during May, one can usually feel the pre-

sence of very fine particles of dust and wheat crop residue by

smelling the ambient air, even in the urban areas, far from

countryside. Due to certain economical reasons, the open

burning of crop residue has become popular and there is a gap

of roughly two months between the harvest of wheat and

cultivation of rice and hence during the months of May and

June a substantial agricultural land is left bare. Therefore,

during hot, dry and windy summer the dust and ash (from crop

residue burning) also contribute to the AOD at Lahore. In

addition, the local industrial and urban (vehicular, road dust

etc.) emissions are also lifted high by speedy winds. During

the summer monsoon, a significant contribution to the aerosol

burden comes from humidification. As far as aerosol loading

variations are concerned, our results agree with those obtained

by Holben et al. (2001) for northern mid-latitude continental

sites showing seasonal cycles of warm season peaks and cool

season low values of AOD.

The Angstrom exponent (AE), which is a measure of the

wavelength dependence of AOD and therefore, a qualitative

indicator of particle size (Kaufman et al., 1994), has been

computed from AOD measurements at 440 nm and 870 nm.

The value of AE decreases as the particle size increases; for

coarse mode soil particles AE ≈ 0, while for fine mode anthro-

pogenic pollutants it varies from 1 to 3 (Kaskaouties and

Kambezidies, 2006). The monthly average values of AE over

Lahore obtained from AERONET data are shown in Fig. 2b.

During the study period, the monthly average values of AE

varied from 0.52 ± 0.23 in June to 1.27 ± 0.07 in December. In

terms of seasonal variations, we obtained the highest value of

AE in winter (1.20) indicating the dominance of fine particles,

which could have resulted from vehicular, industrial and bio-

mass burning emissions. On the other hand, the minimum value

of AE was found to be 0.68 in spring, the Asian dust season,

indicating a relatively higher concentration of coarse mode

aerosols originating from regional and continental sources. As

pointed out earlier in this section, the two highest values of

AOD over Lahore have been found in the months of June

(0.85 ± 0.42) and July (1.02 ± 0.41) and corresponding AEFig. 3. Comparison of seasonal AOD values obtained by us with Alamet al. (2010) and Alam et al. (2011b).


values of 0.52 ± 0.23 and 0.84 ± 0.28 respectively. This in-

dicates that relatively large sized aerosol particles (such as

dust) dominated the atmosphere of Lahore in the month of

June. Alam et al. (2011b, 2012), also found similar results over

Karachi. We find minimum value of AOD to be 0.47 ± 0.26 in

February with corresponding AE value of 1.11 ± 0.25, indi-

cating dominance of fine mode anthropogenic aerosols over

Lahore. As far as seasonal values of AE are concerned, we

obtained its maximum value in winter (1.20) attributed to the

dominance of fine aerosol particles and minimum value in

spring (0.68) indicating that coarse aerosol particles dominated

the atmosphere over Lahore. In summer and fall, average

values of AE were observed to be 0.76 and 1.03 respectively.

Thus, the atmosphere over Lahore was dominated by coarse

particles (mineral/desert dust) during spring and summer. It is

well justified by the meteorological conditions prevailing at

Lahore (Table 1), where an accumulated frequency of desert

dust events during these two seasons is almost 86%.

We have also plotted the monthly average values of water

vapor content (WVC) over Lahore by using the AERONET

data as shown in Fig. 2c. The AERONET measures simul-

taneous columnar water vapor along with aerosol properties at

three wavelengths of 675 nm, 870 nm and 940 nm. The total

transmission for 675 nm and 870 nm is computed using Rayleigh

and AODs and extrapolated to obtain the total transmission at

the nominal 940 nm wavelength, which is then subtracted from

the measured transmission at 940 nm. This resultant would give

us the transmission due to water vapor. The columnar water

vapor (in centimeters) are thus retrieved by using AERONET

version 2.0 algorithm and data quality criteria (Smirnov et al.,

2000; Dubovik et al., 2006; Holben et al., 2006). The accuracy

of AERONET cimel for WVC retrievals is estimated to be

within 10% (Schmid et al., 2001; Smirnov et al., 2004). Prasad

and Singh. (2009) have shown that high correlation (~0.95)

exits between WVC retrieved from AERONET and Global

Positioning System (GPS) over Kanpur (India). We observe a

strong seasonality in the WVC variabililties over Lahore i.e.,

high values in summer (4.305) and low in winter (1.068) with

moderate values in spring (1.977) and fall (2.823) in agree-

ment with the usual synoptic pattern of the region (see for

example Singh et al., 2004; Alam et al., 2012). Its highest value

was observed in August (4.80). Obviously, this result can be

explained by the fact that greater rainfall in August increases

the amount of water vapors in the atmosphere. Due to

relatively dry weather, the lowest value of WVC was observed

in December (0.88).

b. Size distribution

The volume size distribution of aerosols is influenced by the

mixture of different aerosol types present at a certain location

which depends upon factors influencing the strength of aerosol

sources, upon the trajectories of the air masses arriving at that

location and upon meteorological dispersion and scavenging

mechanisms (Eck et al., 2001). The volume size distribution of

aerosol particles dV/d ln r (µm3 µm-2) for each mode is given

by:

,

where Cv is the columnar volume of particles per unit cross

section of atmospheric column, r is the particle radius, rv is the

volume geometric mean radius and σ is the standard deviation.

Figure 4 shows the retrieved AERONET aerosol volume size

distribution over Lahore for different seasons during the study

period. These size distributions have been derived from the

algorithm developed by Dubovik and King. (2000) from sun/

sky radiometer measurements. A two mode lognormal distri-

bution is observed with fine mode particles having radii less

than 0.7 µm and coarse mode particles with radii greater than

0.7 µm. The bimodal structure of volume size distribution may

occur due to several reasons. For example, mixing of two air

masses with different aerosol types (Hoppel et al., 1985),

homogenous nucleation of heteromolecules into fine particles

or heterogeneous nucleation and condensation of gas phase

reaction into larger particles (Yu et al., 2011). The peak value

of fine modes occurred at a radius of ~0.15 µm in summer, fall

and winter and at a radius of ~0.11 µm in spring. The peak

values of the coarse mode occurred at a radius of ~2.9 µm in

spring, summer and fall and at a radius of ~3.8 µm in winter.

The volume size distribution at coarse mode during spring and

summer seasons have been found to be three times as compared

to that during winter. A large difference in dust storm

frequencies (~86% in spring and summer as compared to 1.4%

in winter) is responsible for this increase. However, for the fine

mode particles we do not find any substantial difference in

volume concentrations during all the four seasons. A similar

trend was observed by Dey et al. (2004) while analyzing the

effect of dust storms on seasonal optical properties in this

region. The volume concentration at the coarse mode possesses

a moderate value (~0.13) during the fall season, similar to the

result found by Dey et al. (2004) for the fall season. These

higher volume concentrations during fall (~2 times) as com-

pared to that of winter must be due to large scale crop residue

burning during this season. Some recent studies over Lahore

(Alam et al., 2012), Karachi (Alam et al., 2011a, 2012) and

dV d rln⁄ Cv σ 2π⁄( ) 1

2---–

r rv

⁄( )ln

σ------------------⎝ ⎠⎛ ⎞

2

exp=

Fig. 4. AERONET retrieved volume size distribution in different sea-sons for the period December 2009- October 2011 along with thestandard deviations.


Kanpur (India) (Wang et al., 2011) show similar trends regard-

ing the particle size distributions in coarse and fine modes.

c. Single scattering albedo

Single scattering albedo (SSA) is defined as the ratio of the

scattering coefficient to the extinction coefficient and is an

important parameter that describes the effect of aerosols on

radiative forcing. It depends upon the refractive index and size

of aerosols and there are many ways in which SSA can be

estimated for column as well as surface and layered aerosols

(Soni et al., 2010). In the present work, SSA has been obtained

using sun/sky radiance measurements for column aerosols in

the atmosphere (Nakajima et al., 1996; Dubovik et al., 2000)

and is derived from almucantar retrieved aerosol properties

such as complex index of refraction and aerosol size distri-

bution (Dubovik and King, 2000; Dubovik et al., 2002 ). The

SSA exhibits different spectral behavior for different types of

aerosols: increasing with wavelength for desert dust aerosols

and decreasing for biomass and urban/industrial aerosols

(Dubovik et al., 2002).

Figure 5 exhibits spectral variations of SSA during the four

seasons over Lahore. We observe a reasonable dependence of

SSA over wavelength such that in all the four seasons SSA

increased substantially in the range 440 nm - 675 nm and then,

except for the winter, there was a mild increase in the range

675 nm - 1020 nm. During winter, SSA decreases with increase

in wavelength beyond 675 nm, which can be attributed to the

dominance of absorbing industrial/urban aerosols over Lahore,

because lower SSA values at longer wavelength are obtained

due to minimum probability for interaction between solar radi-

ation and absorbing aerosols (Singh et al., 2004). Yu et al.

(2009) found a similar trend in SSA variabililties over Beijing

during all the four seasons, which they attributed mainly to the

dominance of absorbing urban aerosols. While studying aerosols

optical properties in a northwestern city of Yinchuan with high

industrial pollution, Liu et al. (2008) also found a decreasing

trend in SSA with increase in wavelength during all seasons

except spring (due to influence of dust events). Meteorological

conditions (Table 1) indicate dominance of absorbing aerosols

over Lahore during winter. For the winter season, similar

results were found by Alam et al. (2011a, 2012) over Lahore

and Karachi, Singh et al. (2010) over Delhi and Singh et al.

(2004) over Kanpur. During spring, summer and fall SSA

shows an increasing trend with wavelength (Fig. 5), indicating

the dominance of coarse particles over Lahore during these

seasons. However, a slight increase in SSA values in the range

675 nm to 1020 nm during spring, summer and fall shows that

a combination of absorbing aerosols and dust prevailed of

Lahore with dust dominating over urban/industrial aerosols.

During the period of high concentrations of WVC i.e., June -

September (Fig. 2c), the water-soluble aerosols grow hygro-

scopically and thus contribute to SSA values at higher wave-

lengths (Singh et al., 2004). It can also be noted that the

maximum increase occurred in the spring season. Yu et al.

(2006) also found similar results at Chinese sites due to dust

events. In winter, decreasing trend in SSA values in the range

675 nm - 1020 nm is indicative of the fact that absorbing

aerosols such as biomass and urban/industrial aerosols were

dominant over Lahore. As compared to other seasons, rela-

tively high SSA values were obtained in summer i.e., 0.909,

0.935, 0.943 and 0.944 at 440 nm 675 nm, 870 nm and 1020

nm respectively. In monsoon and pre-monsoon seasons, hygro-

scopic growth of particles causes SSA values to be higher

(Singh et al., 2004). Alam et al. (2011a) have reported a

similar trend over Karachi. The average SSA values between

440 nm and 1020 nm in winter, spring, summer and fall were

observed to be 0.906, 0.892, 0.933 and 0.917 respectively.

d. Refractive index

The index of refraction is a complex quantity with n(λ) and

k(λ) as its real and imaginary parts respectively. It is an im-

portant optical property of aerosols that highly depends upon

their chemical composition (Dey et al., 2004). The real part of

refractive index represents scattering such that its higher values

indicate higher scattering, and its imaginary part represents

absorption (Yu et al., 2009). The real and imaginary parts of

complex refractive index depend upon retrieved particle size

distribution and SSA of aerosols and different patterns may be

obtained because of different types of aerosols present in the

study area (Dubovik et al., 2002). Several models have shown

that for dust, the real part of index of refraction is 1.53 in the

visible spectrum (Shettle and Fenn, 1979; WMO, 1983;

Koepke et al., 1997). However, due to difference in measure-

ment techniques and in the dust composition, the value of n

may deviate within a range of ± 0.05 (Sokolik et al., 1993;

Sokolik and Toon, 1999). Similarly, the imaginary part of

refractive index, as suggested by different models of visible

spectrum, is found to be 0.006 (Shettle and Fenn, 1979; WMO,

1983), while lower values of 0.003 and 0.001 have also been

suggested by Levin et al. (1980) and Otterman et al. (1982) re-

spectively.

Figures 6a and 6b show real and imaginary parts of refrac-

tive index (RI) respectively at Lahore during December 2009

Fig. 5. Seasonal variations in SSA in the wavelength range 440 nm -1020 nm during December 2009- October 2011 along with the standarddeviations.


to October 2011. The real part of refractive index (n) exhibits a

higher sensitivity to wavelengths for the interval 440 nm to

870 nm than the interval 870 nm to 1020 nm. It increases in the

range 440 nm - 870 nm and then slightly decreases in the range

870 nm - 1020 nm during all the four seasons. An increase in

the real part of RI indicates an increase in total scattering

(Bohren and Huffman, 1983). A similar result was found by Yu

et al. (2009) over Beijing during spring and summer seasons,

and Yu et al. (2011) over Taihu during spring, summer and fall.

However, Singh et al. (2004) found, in general, an increasing

trend in n with wavelength during all the four seasons. During

the seasons of winter and fall, average values of real part of RI

were found to be 1.48, while in spring and summer the

corresponding values were 1.53 and 1.49 respectively. The real

part of RI remained higher in spring than during all other

seasons indicating the dominance of highly scattering type of

aerosols such as desert dust. The lower value of n during

summer (1.49) may possibly occur due to high relative humidity

and resultant hygroscopic growth of aerosols (Dubovik et al.,

2002). Its value considerably decreases in the wavelength

range 440 nm - 675 nm and then it remains almost constant in

the wavelength range 675 nm - 1020 nm. This low wavelength

dependence of k was also found by Yu et al. (2009) over

Beijing. The spectral variation of imaginary part of RI is shown

in Fig. 6b for each season. The imaginary part of RI remained

higher in winter than during all other seasons pointing towards

the dominance of absorbing aerosols such as black carbon. The

highest average value of k was observed in winter (0.0100)

and lowest in summer (0.0045). During summer, the decrease

in the k, coupled with an increase in SSA (Fig. 5), indicates

higher concentration of aerosols of non-absorbing nature

(usually desert dust). The lowest value in summer can likely be

due to the hygroscopical growth of particles (Yu et al., 2011).

The imaginary part of RI showed moderate average values of

0.0070 and 0.0066 in spring and fall respectively and these

values have occurred because of comparable contribution of

different types/origins of aerosols present over Lahore.

e. Asymmetry parameter

Asymmetry parameter (ASY) is average cosine of scattering

direction weighted by the phase function and thus describes

the preferred direction of scattering for the light interacting

with the aerosol particles. If the scattering is symmetric, ASY

is taken to be zero, while for purely forward scattering it is

considered to be +1 and for complete backward scattering it is

taken to be −1. For cloud free conditions the ASY varies from

~0.1 in very clean conditions to ~0.75 for polluted atmos-

pheres (Zege et al., 1991). Figure 7 shows the spectral vari-

ations of asymmetry parameter (ASY) at 440 nm, 675 nm,

870 nm and 1020 nm over Lahore during the studied period.

The seasonal averages show a decreasing trend for wavelengths

between 440 nm - 870 nm and then remain nearly constant for

the wavelength range 870 nm - 1020 nm in all the four seasons.

The seasonal averages of ASY are larger during summer

(0.70) and spring (0.69) as compared to winter (0.65) and fall

(0.68). These higher values were obtained due to dominance of

coarse particles (usually dust) over Lahore. A similar trend

was observed at Yangtze River Delta in China (Yu et al., 2011)

at Gwangju, Shirahama and Noto during dust episodes in

spring season (Yu et al., 2006) and at Beijing (Yu et al., 2009).

f. Aerosol radiative forcing

The aerosol radiative forcing (ARF) due to atmospheric

aerosols is defined as the difference in the net fluxes (down-

ward minus upward) with and without aerosols, i.e.,

∆F = (F↓a − F↑a) − (F↓o − F↑o),

where ∆F is the radiative forcing (W m−2), arrows indicate the

directions of global fluxes and Fa and Fo represent the fluxes

with and without aerosols, respectively. Radiative forcing is a

Fig. 6. The seasonal variation in AERONET derived (a) real and (b)imaginary parts of the RI during December 2009- October 2011 in thewavelength range 440 nm - 1020 nm over Lahore along with the stand-ard deviations.

Fig. 7. The seasonal variation in AERONET derived ASY duringDecember 2009- October 2011 in the wavelength range 440 nm - 1020nm over Lahore along with the standard deviations.


strong function of SSA, ASY and AOD. The atmospheric ARF

is the difference of ARF at TOA and surface, and its large

values indicate higher absorption of solar radiation within the

atmosphere, causing a warming effect on it. Resultantly, the

surface of the Earth will have a cooling effect (Miller and

Tegen, 1999; Ge et al., 2010). This phenomenon can substan-

tially alter the dynamic system and stability of the atmosphere

(Li et al., 2010). The AERONET network provides obser-

vations for direct solar effects produced by atmospheric aerosols

including ARF. These measurements are derived by making use

of aerosol properties retrieved from direct sun and diffuse sky

radiances in solar almucantar. In order to validate the radiative

parameters obtained from AERONET, Garcia et al. (2008) com-

pared the AERONET solar downward fluxes at surface with

the observed ground based measurements from solar databases.

These authors found that the AERONET estimates of solar

broadband fluxes and radiative forcing show a convincing

agreement with the surface measurements for different aerosol

types and loading conditions. Alam et al. (2011a), while dis-

cussing the radiative forcing over mega-city of Karachi,

computed ARF by using Santa Barbra Discrete ordinate

Atmospheric Radiative Transfer (SBDART) model (Ricchiazzi

et al., 1998). They found that there was an overall convincing

agreement for radiative forcing at surface and TOA from

AERONET derived and SBDART calculated measurements.

Alam et al. (2012) also found a good agreement over Karachi

and Lahore in AERONET retrieved and SBDART calculated

radiative forcing at the surface. In the present work, we have

used the ∆F values provided as an operational product of

AERONET network (http://aeronet.gsfc.nasa.gov). The ∆F

values provided by AERONET at the surface have been

corrected by a term (1- SA), where SA is the surface albedo.

Table 2 shows AERONET retrieved seasonal averages of

ARF at TOA, surface and within the atmosphere during the

study period at Lahore. Among all the four seasons the ARF at

the surface is found to be highest in winter (−92.28 W m−2) and

lowest in spring (−100.36 W m−2), while at TOA, ARF is high-

est in spring (−26.31 W m−2) and lowest in summer (-36.11

W m−2). The seasonal atmospheric forcing is found to be 58.33

W m−2 (winter), 74.04 W m−2 (spring), 64.23 W m−2 (summer)

and 56.55 W m−2 (fall). The highest value of ARF occurring in

spring indicates that the atmosphere is warmer in spring than

in the other seasons. The corresponding value obtained by

Alam et al. (2012) is 64.3 W m−2 (winter) which is comparable

to the result obtained by us, while for the summer season these

authors obtain a value of 82.6 W m−2, which is about 25%

higher than our result for summer. For the whole study period

(December 2009 to October 2011), the average AERONET

retrieved radiative forcing at the TOA is −32.57 W m−2, while

its value at the surface is −96.48 W m−2, leading to an

atmospheric forcing of 63.29 W m−2 over Lahore.

4. Conclusions

Aerosol optical properties have been studied from both direct

sun (AOD and AE) and inversion products (SSA, ASY, RI),

for the period December 2009 - October 2011. The monthly

average AOD values over Lahore were generally greater than

0.47. The maximum monthly average AOD occurred in July

(1.02) and minimum in the month of February (0.47). The high

AE value during winter (1.20) indicates the dominance of fine

aerosol particles and low AE value in spring (0.68) indicates

the dominance of coarse particles. The maximum water vapor

content was found in August (4.80 cm). A two mode lognormal

structure for the aerosol volume size distribution was ob-

served. The peak value of fine modes occurred at a radius of

~0.15 µm in summer, fall and winter and at a radius of ~0.11

µm in spring. The maximum value of coarse mode occurred at

a radius of ~2.9 µm in spring summer and fall and at a radius

of ~3.8 µm in winter. The SSA values showed a significant

increasing trend in the wavelength range 440 nm - 675 nm in

all the seasons. The highest average value was observed in

summer (0.933) and the lowest in spring (0.892). The real part

of RI showed highest value in spring (1.53) and lowest value

(1.48) in the seasons of winter and fall. The highest average

value of imaginary part of RI was observed in winter (0.0100)

and lowest in summer (0.0045) and moderate values in spring

(0.0070) and fall (0.0066) indicating that the atmosphere in the

winter had relatively high absorbtivity. The average values of

ASY were 0.65 (winter), 0.69 (spring), 0.70 (summer) and

0.68 (fall). In case of ARF, we observed that the atmosphere

was warmer in spring than in all the remaining seasons.

Acknowledgments. We are grateful to the two anonymous re-

viewers and editor for their useful comments to improve the

manuscript. We greatly acknowledge NASA and Institute of

Space Technology for installing and maintaining Lahore AERO-

NET site and for providing the data (http://aeronet.gsfc.nasa.

gov/). We are also thankful to Pakistan Meteorological De-

partment (Lahore center) for providing meteorological data.

Edited by: Rokjin Park

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