Full text of DOI:10.1016/S1352-2310(00)00105-9

Atmospheric Environment 34 (2000) 4511}4523
Atmospheric optical and radiative e!ects of anthropogenic
aerosol constituents from India
M. Shekar Reddy, Chandra Venkataraman*
Centre for Environmental Science and Engineering, Indian Institute of Technology, Bombay, Powai, Mumbai 400 076, India
Received 10 June 1999; accepted 4 January 2000
Abstract
A box model has been used to compare the burdens, optical depths and direct radiative forcing from anthropogenic
PM aerosol constituents over the Indian subcontinent. A PM emission inventory from India for 1990, compiled for
ꢀ
ꢁꢂ
ꢀꢁꢂ
the "rst time, placed anthropogenic aerosol emissions at 12.6 Tg yr\ꢃ. The contribution from various aerosol constitu-
ents was 28% sulphate, 25% mineral (clay), 23% #y-ash, 20% organic matter and 4% black carbon. Fossil fuel
combustion and biomass burning accounted for 68% and 32%, respectively, of the combustion aerosol emissions. The
monthly mean aerosol burdens ranged from 4.9 to 54.4 mg m\ꢀ with an annual average of 18.4$22.1 mg m\ꢀ. The
largest contribution was from #y-ash from burning of coal (40%), which has a high average ash content of 30%. This was
followed by contributions of organic matter (23%) and sulphate (22%). Alkaline constituents of #y-ash could neutralise
rainfall acidity and contribute to the observed high rainfall alkalinity in this region. The estimated annual average optical
depth was 0.08$0.06, with sulphate accounting for 36%, organic matter for 32% and black carbon for 13%, in general
agreement with those of Satheesh et al. (1999). The mineral aerosol contribution (5%) was lower than that from the
previous study because of wet deposition from high rainfall in the months of high emissions and the complete mixing
assumption in the box model. The annual average radiative forcing was !1.73$1.93 W m\ꢀ with contributions of
4
9% from sulphate aerosols, followed by organic matter (26%), black carbon (11%) and #y-ash (11%). These results
indicate the importance of organic matter and #y-ash to atmospheric optical and radiative e!ects. The uncertainties in
estimated parameters range 80}120% and result largely from uncertainties in emission and wet deposition rates.
Therefore, improvement is required in the emissions estimates and scavenging ratios, to increase con"dence in these
predictions. ( 2000 Elsevier Science Ltd. All rights reserved.
Keywords: PM emission inventory; Black carbon; Organic matter; Minerals; Fly-ash; Sulphate; Box model
ꢀꢁꢂ
1
. Introduction
al., 1991, 1992; Kiehl and Briegleb, 1993; Boucher et al.,
998). However, recent global models have identi"ed the
1
Anthropogenic aerosol emissions to the troposphere
importance of carbonaceous aerosols (Penner, 1995; Pen-
ner et al., 1992; Haywood and Ramaswamy, 1998), and
mineral aerosols (Tegen et al., 1996; Sokolik and Toon,
1996). The resultant forcing depends on the relative
source strengths and burdens, which have a strong re-
gional dependence (Tegen et al., 1997). In order to re"ne
global scale predictions, it is of importance to study
aerosol emissions and atmospheric e!ects on a regional
scale.
have increased in recent decades (Houghton et al., 1996)
and their e!ects include scattering and absorption of
incident solar radiation (direct e!ect) and modifying the
microphysical and optical properties of clouds (indirect
e!ect). Much of the work on direct radiative forcing of
aerosols has focused on sulphate aerosols (Charlson et
In previous regional studies of anthropogenic sul-
phate (Venkataraman et al., 1999) and carbonaceous
(Reddy and Venkataraman, 1999) aerosols over India, an
*
Corresponding author. Fax: #91-22-578-3480.
E-mail address: chandra@cc.iitb.ernet.in (C. Venkataraman).
1
352-2310/00/$- see front matter ( 2000 Elsevier Science Ltd. All rights reserved.
PII: S 1 3 5 2 - 2 3 1 0 ( 0 0 ) 0 0 1 0 5 - 9

4
512
M. Shekar Reddy, C. Venkataraman / Atmospheric Environment 34 (2000) 4511}4523
aggregate emissions inventory for these species for 1990
was developed. A box model was used, along with re-
gional meteorological parameters, to simulate atmo-
spheric processes including reaction, deposition and
advection to estimate aerosol burdens and radiative
e!ects. Sulphate and organic matter aerosols con-
tributed in similar magnitude to decrease in radiation
2.2. Emissions
2.2.1. Fossil fuel combustion
The fossil fuel-use data for 1990 were compiled from
Mitra (1992), also previously used for sulphur emission
estimates (Venkataraman et al., 1999) (Table 1). Black
carbon (BC) emission factors are from Bocola and Cirillo
(1989) and USEPA (1996a), used previously by Cooke
and Wilson (1996) for global black carbon emission in-
ventories. Primary organic carbon (OC) aerosols are
emitted from the same combustion sources as black car-
bon, while secondary organic carbon is formed from
atmospheric reactions of gaseous volatile organic com-
pounds (VOCs) (Turpin and Huntzicker, 1991) and is
predominantly sub-micron in size (McMurry and Zhang,
1989). Organic carbon emission factors are developed
from black carbon emission factors multiplied by an
appropriate OC/BC ratio, following previous global or-
ganic matter emission estimates (Liousse et al., 1996). We
use a previously suggested BC/OC ratio of 0.30, based on
the measurements of black carbon and organic carbon
concentrations in aerosols collected near source regions
#
ux (!1.1$1.0 W m\ꢀ from sulphate and !0.69$
0
.55 W m\ꢀ from organic matter), while black carbon
aerosols caused a #0.27$0.17 W m\ꢀ increase in radi-
ation #ux.
The objectives in this study were three-fold: (i) to
develop a PM
emissions inventory for India of par-
ꢀ
ꢁꢂ
ticles smaller than 2.5 lm diameter, (ii) to estimate bur-
dens and radiative e!ects of anthropogenic #y-ash and
mineral aerosols, and (iii) to compare the relative contri-
bution of sulphate, #y-ash, mineral and carbonaceous
aerosols to optical depth and radiative forcing.
2
. Modelling approach
(Pierson and Russel, 1979; Rosen et al., 1980; Cadle and
2
.1. Model description
Dasch, 1988; Bremond et al., 1989). From the measure-
H
ments of Countess et al. (1981), the ratio of organic
matter (OM) to organic carbon is assumed 1.3, to ac-
count for associated hydrogen, oxygen, and minor
amounts of other species. From the above assumptions,
the ratio of aerosol organic matter to black carbon
(OM/BC) is 4.33.
Estimates of aerosol burden (of sulphate, carbon-
aceous, #y-ash and mineral aerosols), optical depth and
radiative forcing over India are made using regional
emissions and atmospheric parameters. A carbonaceous
aerosol and #y-ash emission inventory is compiled from
aggregate fossil fuel (industrial coal and petroleum) com-
The black carbon and organic matter emission factors
developed above correspond to particles smaller than
2 lm diameter. Fly-ash emission factors, in particles
smaller than 2.5 lm diameter, are obtained by subtract-
ing the sum of BC and OM from PM emission factors
bustion and biomass burning (previously used for a SO
emissions inventory) along with appropriate emission
ꢀ
factors. An estimate of anthropogenic mineral aerosol
emissions from disturbed soils is made from reported
mineral emission #uxes over India (Tegen and Fung,
ꢀꢁꢂ
for all the fossil fuels. This follows from our assumption
that PM emissions from fossil-fuel combustion consist
1
995). Aerosol lifetimes and burdens are calculated using
ꢀꢁꢂ
a box model considering aerosol transport and removal
mechanisms including advection, wet deposition and dry
deposition. This follows from the previous study of
formation and direct radiative forcing from sulphate
aerosols over the Indian subcontinent (Venkataraman et
al., 1999). The box model used covers an area (¸;=) of
of black carbon, organic matter and #y-ash. Basu and
Chakrabarti (1990) report the ash content of coal used
in di!erent Indian industrial sectors and this was used
to generate PM
(1996a) compilation as a function of coal ash-content.
emission factors from the USEPA
ꢀꢁꢂ
For liquid and gaseous fossil fuels, PM emission fac-
ꢀꢁꢂ
7
.3;10ꢃꢀ mꢀ (8}363N and 70}923E), including the land-
tors were given as mass of pollutant per mass of fuel
burnt (USEPA, 1996a; Bocola and Cirillo, 1989).
mass of India and surrounding oceans, with an average
mixing height of 0.5}2.0 km (Charlson et al., 1992) and
with uniformly mixed constituents. The Fourier ampli-
tude sensitivity test (FAST) (Cukier et al., 1973; McRae et
al., 1982) is used to average monthly mean meteorologi-
cal data from 18 stations spread uniformly over India to
obtain spatially averaged aerosol lifetime, burden, optical
depth and radiative forcing. The meteorological para-
meters are normally distributed about their monthly
means with an additive search curve for small monthly
range or uncertainty and an exponential search curve for
a range exceeding an order of magnitude.
2.2.2. Biomass burning
Biomass burning in India includes wood, agricultural
residue and dung-cakes used as fuel in cooking stoves
as well as forest and grassland "ring (Joshi, 1991).
1989}1990 estimates of biomass burning (Kaul, 1993;
Kaul and Shah, 1993; Sinha and Joshi, 1997) are used for
carbonaceous aerosols and #y-ash emission estimates.
Measured total particulate matter (PM) emission factors
for fuelwood, agricultural residue and dung-cakes burned
in cooking stoves are from Joshi et al. (1989, 1991).

M. Shekar Reddy, C. Venkataraman / Atmospheric Environment 34 (2000) 4511}4523
4513
Table 1
Fuel use data and emission estimates of carbonaceous aerosols and #y-ash for 1990
Source
Consumption Mean emission factors (g kg\ꢃ)
Aerosol emissions (Tg yr\ꢃ)
(MT yr\ꢃ)
PM
!
BC!
OM!
PM
ꢀꢁꢂ
BC
OM
Fly-ash
ꢀꢁꢂ
Fossil fuels
Coal
Steel
Power
22.3"
135.7
6.5
11.5
1.0
5.5
3.5
31.7
11.0
8.840#
17.160
10.400
13.000
13.000
10.400
20.800
15.600
5.860
1.000$
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
4.333%
4.333
4.333
4.333
4.333
4.333
4.333
4.333
4.333
0.197
2.329
0.068
0.150
0.013
0.057
0.073
0.495
0.064
0.022
0.136
0.007
0.012
0.001
0.006
0.004
0.032
0.011
0.097
0.588
0.028
0.050
0.004
0.024
0.015
0.137
0.048
0.078
1.605
0.033
0.088
0.008
0.028
0.054
0.325
0.006
Railways
Cement
Sponge iron
Fertiliser
Coke
Others
Lignite
Petroleum
LPG
Kerosene
H S Diesel
Fuel oils
Motor Gas.
Aviation gas
Sub-total
2.3
8.2
20.7
8.8
3.5
1.8
0.060
0.300
3.050
2.776
1.800
1.800
0.060
0.300
0.700
0.100
0.000
0.000
0.260
1.300
3.033
0.433
0.000
0.000
0.000
0.002
0.063
0.024
0.006
0.003
3.345
0.000
0.002
0.014
0.001
0.000
0.000
0.247
0.001
0.011
0.063
0.004
0.000
0.000
1.069
-
-
-
0.020
0.006
0.003
2.255
$
0.229&
$0.990&
$1.336'
Biomass
Wood
Dung-cakes
Agr. Res.
Forest
252.1)
106.1
99.2
26.7
5.2
2.112*
6.512
4.048
18.000ꢂ
18.000
0.285ꢀ
0.326
0.457
1.530
1.530
1.290ꢁ
3.979
2.473
12.402
12.402
0.532
0.691
0.402
0.481
0.094
2.199
0.072
0.035
0.045
0.041
0.008
0.201
0.325
0.422
0.245
0.331
0.064
1.388
0.135
0.234
0.111
0.109
0.021
0.610
Grassland
Sub-total
489.3
$
0.117ꢃ
0.45 $0.26
$0.777ꢃ
2.46 $1.26
$0.367ꢃ
2.86 $1.39
Total
5.74
!
"
#
$
%
PM : emissions of particulate mass smaller than 2.5 lm diameter, BC: black carbon, OM: organic matter.
ꢁꢂ
Fossil fuel use data (Mitra, 1992).
ꢀ
PM emission factors for fossil fuels (USEPA, 1996a); coal ash content (Basu and Chakrabarti, 1990).
ꢁꢂ
BC emission factors for fossil fuels (Bocola and Cirillo, 1989; USEPA, 1996a).
ꢀ
OM emission factors for fossil fuels average BC/OC"0.3 (Pierson and Russel, 1979; Rosen et al., 1980; Cadle and Dasch, 1988;
mond et al., 1989); OM/OC"1.3 (Countess et al., 1981).
Assumed uncertainty in emission factors of BC and OM from coal and lignite are 100%.
Assumed uncertainty in emission factors of PM from coal and lignite are 60% and hence uncertainty in emission factors of #y-ash
Bre
&
H
'
ꢀꢁꢂ
are 60%.
)
Biomass use data (Kaul, 1993; Kaul and Shah, 1993; Sinha and Joshi, 1997).
*
PM emission factors for biomass fuels: PM emission factors (Joshi, 1989, 1991); average PMꢀꢁꢂ/PM"0.80 (Dasch, 1982; Jenkins et
ꢀ
ꢁꢂ
al., 1993; Radke et al., 1988, 1991).
ꢀ
BC emission factors for biofuels, forest and grassland burning: BC/PM
(Liousse et al., 1996).
ꢀ
ꢁꢂ
OC/PM "0.45 (Patterson and McMahon, 1984; Dasch, 1982; Cooper, 1980); OM/OC"1.3 (Countess et al., 1981).
ꢁꢂ
ꢂPM emission factors for forest and grassland burning (Ward et al., 1991; Patterson and McMahon, 1984; Patterson et al., 1986).
ꢁꢂ
ꢃAssumed uncertainty in emission factors of PM from biofuels are 75% and hence uncertainty in emission factors of BC, OM and
ꢁ
ꢀ
ꢀ
#
y-ash are 75%. Assumed uncertainty in emission factors of PM from forest "ring and grassland burning are 56% and uncertainty in
ꢀꢁꢂ
emission factors of BC, OM and #y-ash are 56%.
PM
emission factors are calculated from these using
Jenkins et al., 1993; Radke et al., 1991). PM emission
factors for forest and grassland "ring are taken from
Ward et al. (1991), Patterson and McMahon (1984) and
ꢀ
ꢁꢂ
a PM /PM ratio of 0.80 reported from wood and
ꢁꢂ
agricultural residue burning experiments (Dasch, 1982;
ꢀꢁꢂ
ꢀ

4
514
M. Shekar Reddy, C. Venkataraman / Atmospheric Environment 34 (2000) 4511}4523
Patterson et al. (1986). Emission factors for black carbon
are calculated from BC/PM ratios compiled by
Liousse et al. (1996) for di!erent biomass types (Table 1).
Table 2
Mineral aerosols emission estimates
ꢀ
ꢁꢂ
Parameter
Value
OC/PM ratios are taken for burning of fuel wood,
ꢀ
ꢁꢂ
agricultural residue, forest and grasslands as 45% (Pat-
terson and McMahon, 1984; Dasch, 1982; Cooper, 1980)
and assumed the same for burning of dung-cakes. Once
again, the ratio of organic matter to organic carbon is
assumed 1.3 (Liousse et al., 1996). Fly-ash emissions from
biomass burning are estimated as for fossil fuels, by
deducting the sum of black carbon and organic matter
Emission #ux! (kg mꢀ yr\ꢃ)
0.00}0.05
4.50
2.46;10ꢃꢃ
6.16
%
of continental area as a source
Source area (mꢀ)
Total emissions (1}10 lm) (Tg yr\ꢃ)
PM emissions" (Tg yr\ꢃ)
3.142 (0.0}6.16)#
ꢀꢁꢂ
!Tegen and Fung (1995).
fraction from the PM
emissions. While, emissions
"PM /total emissions"0.51 (Tegen and Lacis, 1996).
ꢀ
ꢁꢂ
ꢀꢁꢂ
from the biomass burning vary seasonally, as a "rst
estimate, it is assumed that emissions are uniformly dis-
tributed throughout the year.
#Value in the parenthesis is range of mineral aerosol emissions.
(d'Almeida, 1986; Tegen and Fung, 1994, 1995; Duce,
1
995). We have developed an estimate for mineral aero-
sols of size fraction less than 2.5 lm (PM ) from an-
thropogenic activities. This is based on the reported
2
.2.3. Anthropogenic carbonaceous and yy-ash emissions
Estimated black carbon emissions from India for 1990
ꢀꢁꢂ
mineral aerosol #uxes (Table 2) over the Indian region
multiplied by appropriate land area which includes culti-
vated eroded soils, uncultivated eroded soils, recently
cultivated areas and recently deforested areas (Tegen and
Fung, 1995). The reported mineral #uxes over India are
are 0.45 Tg yr\ꢃ, with 55% from fossil fuel combustion
and 45% from biomass burning. These are larger than
previous estimates of black carbon emissions from India
of 0.26 Tg yr\ꢃ (Cooke, 1999) for the base year
1
984}1985 (these exclude agricultural "res) from increase
0
}0.05 kg m\ꢀ yr\ꢃ and the area a!ected by anthropo-
in fuel use between 1984}1985 and 1990. For compari-
son, there are three previous estimates of global black
carbon emission inventories for the base year 1984}1985
genic disturbance is estimated at 1.11;10ꢃꢄ mꢀ. This
gives annual mineral aerosol emissions of 6.16 Tg yr\ꢃ,
distributed 51 and 49% between the 0}2.5 and 2.5}10 lm
size fractions (Tegen and Lacis, 1996). The seasonal vari-
ation in mineral aerosol emissions over India is taken
from GCM estimates of Tegen (1999). Anthropogenic
mineral aerosol emissions were highest in June and July
(Cooke and Wilson, 1996; Liousse et al., 1996; Penner
et al., 1993). These range 12.3}13.5 Tg yr\ꢃ with 2.22}
5
2
.28 Tg yr\ꢃ from Asia.
Organic matter emissions from India are estimated at
.46 Tg yr\ꢃ for 1990, with fossil fuel combustion and
(
&56%) with an additional 23% in April and May. This
biomass burning contributing 43 and 57%, respectively
Table 1). In comparison, estimates of global organic
is expected because agricultural activities coincide with
the dry season during this period in India.
(
matter emissions are 73.20 Tg yr\ꢃ from the above sour-
ces for 1984}1985, with fossil fuel and biomass contribu-
ting 39 and 61%, respectively (Liousse et al., 1996). From
the Cooke and Wilson (1996) estimates of BC discussed
earlier, using the appropriate OM/BC ratios the global
organic matter emissions would be 80.70 Tg yr\ꢃ with
Asia contributing 10.40 Tg yr\ꢃ, in agreement with that
of Liousse et al. (1996).
Fly-ash emissions from India are 2.86 Tg yr\ꢃ, with
fossil fuels and biomass burning accounting for 79 and
2
from coal combustion (2.23 Tg yr\ꢃ), with the power
sector alone contributing 1.61 Tg yr\ꢃ. This is because of
the high ash content of coal (33%) used in this sector
Total anthropogenic combustion PM
ꢀꢁꢂ
diameter range of 0}2.5 lm) of carbonaceous, #y-ash
emissions
(
and sulphate (calculated assuming sulphur dioxide to
sulphate conversion ratio of 0.61 from Venkataraman et
al., 1999) from India for 1990 are 9.4 Tg yr\ꢃ, assuming
no emission control. Including the PM mineral aero-
ꢀꢁꢂ
ꢀꢁꢂ
sol emissions, this gives a total PM
emissions of
1
2.6 Tg yr\ꢃ for India for 1990 (Fig. 1) with the largest
contribution from sulphate aerosols (28%), mineral aero-
sols (25%) and #y-ash (23%). We compared our estimate
1%, respectively. The major contribution to #y-ash is
with a previous PM emission estimate (Hidy and Wolf,
ꢃꢄ
1
995) from a similar combustion source enumeration for
India. They assumed a 10% ash content of coal (against
our average of about 30%) and a 10% emission control
(Basu and Chakrabarti, 1990) which accounts for 59% of
(against our assumption of no emission control) and
total coal consumption (Mitra, 1992).
estimated PM of 12.5 Tg yr\ꢃ for 1990. Assuming
ꢃꢄ
a PM /PM ratio of 0.58 (USEPA, 1996b, c), our
ꢀꢁꢂ
ꢃꢄ
2
.2.4. Anthropogenic mineral aerosols
A number of global mineral aerosol emission estimates
estimated PM emissions would be 16.2 Tg yr\ꢃ. Our
ꢃꢄ
estimate is about 30% higher than that of Hidy and Wolf
have been made from both natural (wind-blown dust)
and anthropogenic (land disturbance) origin, with more
recent estimates signi"cantly larger than earlier estimates
(1995) and is based on a realistic ash-content for coal and
an assumption of no emissions control, which represents
worst-case emissions.

M. Shekar Reddy, C. Venkataraman / Atmospheric Environment 34 (2000) 4511}4523
4515
where k is the advection removal rate (s\ꢃ), k is the wet
!
ꢅ
deposition rate (s\ꢃ) and k is the dry deposition rate
(
$
s\ꢃ). k , k and k are given as
! ꢅ $
1
k!"
,
(2)
v cos h v sin h
#
A
¸
=
B
where v is the surface wind speed (m s\ꢃ), h is the average
wind direction, ¸ is the length of the box (m) and = is the
width of the box (m);
Fig. 1. Relative contribution of aerosol constituents to PM
ꢀꢁꢂ
aerosol emissions from India for 1990 (total 12.6 Tg yr\ꢃ). Emis-
sions from fossil-fuel combustion and biomass burning (in par-
enthesis) contribute to sulphate, organic matter (OM), black
carbon (BC) and #y-ash; mineral aerosols are the clay-fraction
from anthropogenic land disturbance.
RSoꢅ!ꢄ%ꢆ
Ho!*ꢆ
kꢅ"
,
(3)
where R is the monthly mean rainfall (m s\ꢃ), S is the
scavenging ratio, o is the density of water (g cm\ꢅ)
and o!*ꢆ is the density of air (g cm\ꢅ);
ꢅ!ꢄ%ꢆ
2
.2.5. Uncertainties in emissions
Recent measurements of the emission of sub-micron
k "v /H,
(4)
$
$
light absorbing particles from lignite power plant (Bond
et al., 1998) suggest an emission factor, for sub-micron
black carbon, of 0.05 g kg\ꢃ, which is a factor 20 lower
than that assumed here. Further, emissions uncertainties
have shown to have a signi"cant e!ect on the predicted
single-scatter albedo (Heintzenberg et al., 1997). In order
to account for these e!ects, we have included an uncer-
tainty of 100% in BC emissions from fossil fuels (which
includes the reduced emission factor suggested). In addi-
tion, a 75 and 55% uncertainty was assumed (Joshi et al.,
where v is the dry deposition velocity of aerosols (m s\ꢃ)
$
and H is the mixing height (m).
Advection of aerosols out of the box is assumed to
occur by monthly mean horizontal surface winds, with
surface wind speed data for 1990 obtained from 18 me-
teorological stations spread across India, run by Indian
Meteorological Department (IMD). An average dry de-
position velocity of 0.1 cm s\ꢃ (Table 3) is used for black
carbon and organic matter aerosols, consistent with
earlier carbonaceous aerosols transport models (Liousse
et al., 1996; Cooke and Wilson, 1996; Penner et al., 1993).
The dry deposition velocity of mineral aerosols depends
upon particle size (Tegen and Fung, 1994). For the sub-
micron fraction, the mean dry deposition velocity was
1
989, 1991; Ward et al., 1991; Patterson et al., 1986;
Patterson and McMahon, 1984) for BC emissions from
biofuels (fuelwood, agricultural residue and dung-cakes)
and forest "res, respectively. This gave a black carbon
emission range of 0.45$0.26 Tg yr\ꢃ (Table 1). Organic
matter (OM) emissions are derived from BC and have
the same uncertainties resulting in OM emissions of
.46$1.26 Tg yr\ꢃ. Assumed uncertainties in emission
factors of #y-ash from coal and lignite are 60% (USEPA,
996a) and 75% for biofuel combustion (Joshi et al.,
989, 1991) and 56% for forest "res and grassland "ring
0
0
.018 cm s\ꢃ, corresponding to a mean e!ective radius of
.73 lm (assuming size distribution of dN/dlog rJr\ꢅ)
and assumed here for PM
mineral aerosols.
2
ꢀꢁꢂ
Wet deposition is parameterised using scavenging ra-
tios which, for black carbon and organic matter, are 18 to
1
1
(
6
50 (mean 180$170) and 35 to 1900 (mean 340$430),
respectively (Dasch and Cadle, 1989). Scavenging ratios
for organic matter are higher than black carbon from the
greater solubility of organic matter in rainwater. Scav-
enging ratios used are 18 to 350 and 35 to 770 for black
carbon and organic matter, respectively (Table 3). Scav-
enging ratios for clay-sized mineral aerosols varied from
Ward et al., 1991; Patterson et al., 1986; Patterson and
McMahon, 1984). Estimated annual #y-ash emissions
range 2.86$1.39 Tg yr\ꢃ. These uncertainties in the
aerosol emissions are propagated in the model calcu-
lations and a sensitivity analysis carried out to assess the
in#uence of di!erent input parameters on the estimated
radiative forcing.
5
3
00 to 1000 and for larger mineral particles were about
00 (Buat-Menard and Duce, 1986) in the tropical Paci"c
H
Ocean. We use scavenging ratios of 500}1000 for PM
mineral aerosols following Tegen and Fung (1994, 1995)
ꢀꢁꢂ
2
.3. Removal mechanisms and deposition parameters
(
Table 3). Fly-ash particles are the mineral component of
combustion-derived aerosols, are assumed to follow the
PM mineral aerosols deposition characteristics and
The transport and removal mechanisms considered
are advection, dry deposition and wet deposition. The
ꢀꢁꢂ
lifetime (¸ ) of aerosols in the box is given as
have the same deposition parameters (dry deposition
velocity and scavenging ratios).
Aerosol burden (B), which is an area concentration
integrated from the surface of the earth to the top of the
ꢄ
1
¸ꢄ" "
k
1
1
1
#
#
,
(1)
k! k$ kꢅ

4
516
M. Shekar Reddy, C. Venkataraman / Atmospheric Environment 34 (2000) 4511}4523
Table 3
Table 4
Aerosol deposition properties
Parameter
Constants used in the direct radiative forcing calculations
Range of values
Symbol
Parameter
Value
Dry deposition velocity, v (cm s\ꢃ)
Black carbon, organic mater
Mineral aerosols
Fly-ash
F (W m\ꢀ) Top of atmosphere radiative #ux
1370
0.76
$
ꢄ
0.1
0.018
0.018
¹
Fraction of light transmitted by the
atmospheric layer above the aerosol
layer
!
Rꢇ
Fractional albedo of underlying
surface
Backscatter fraction
0.15
0.29
Scavenging ratio, S
Black carbon
Organic matter
Mineral aerosols
Fly-ash
18}350
35}760
500}1000
500}1000
b
b is the globally averaged fraction of the upscattered
radiation (Table 4), q is the optical depth and u is the
single-scattering albedo (ratio of mass scattering coe$-
cient to mass extinction coe$cient):
atmosphere (mixing height), is given by (Charlson et al.,
1
991, 1992)
Optical depth is a product of the aerosol burden (B),
and the mass extinction coe$cient (a "a #a ) relating
Q¸
A
R ,
B"
(5)
%
ꢇ
!
to the mass scattering coe$cient (a ) and mass absorp-
ꢇ
tion (a ) coe$cient of the aerosols (Charlson et al., 1992):
where Q is the aerosol emission rate (g day\ꢃ), ¸ is the
aerosol lifetime (day) and A is the area of the box (mꢀ).
!
ꢄ
q"aB,
(8)
2
.4. Optical properties and direct radiative forcing
Black carbon absorbs the incoming solar radiation,
whereas organic matter scatters it. Results from the sev-
eral measurements and theoretical estimates using Mie
theory have shown that the mass absorption coe$cient
of black carbon ranges from 6 to 10 mꢀ g\ꢃ at visible
wavelengths (Rossler and Faxvog, 1979; Jennings and
Pinnick, 1980). Black carbon aerosols may also scatter
radiation and the measured mass scattering coe$cients
vary from 1.5 to 3.0 mꢀ g\ꢃ (Sloane et al., 1981). Here we
use black carbon mass absorption and scattering coe$-
cients of 7}9 mꢀ g\ꢃ and 1.75}2.0 (Table 5), respectively,
consistent with the previous studies (Liousse et al., 1996;
Penner et al., 1992, 1995; Tegen et al., 1997). Organic
matter contributes only to scattering and measured mass
scattering coe$cients range from 2.5 to 5.0 mꢀ g\ꢃ
(Sloane, 1991; Tangren, 1982; Patterson and McMahon,
1984). We use an organic matter mass scattering coe$c-
ient of 3}5 mꢀ g\ꢃ (Table 5) for low relative humidity
conditions, consistent with the previous studies (Liousse
et al., 1996; Penner, 1995; Tegen et al., 1997).
Direct radiative forcing is estimated assuming an op-
tically thin layer of aerosol, where multiple re#ections
within the aerosol layer are neglected (Charlson et al.,
1
991, 1992). The change in radiative forcing in a column
of air integrated from the surface of the earth to top of the
atmosphere (mixing height), as a result of the change in
planetary albedo occurring in the cloud-free area of the
atmosphere, is given by (Charlson et al., 1991, 1992)
*
F"!ꢃF (1!A )¹ꢀ*R ,
(6)
ꢆ 2
#
!
!
where *F is the change in forcing (W m\ꢀ), (1/4)F is the
2
incident top of the atmosphere radiative #ux and ¹ is
!
the fraction of light transmitted by the atmospheric layer
above the aerosol layer (Table 4), A# is the fractional
areal cloud cover, and *R is the change in planetary
albedo. While this assumes that planetary albedo is en-
hanced only in cloud-free regions, it has been recently
shown (Boucher and Anderson, 1995) that direct radi-
ative forcing in cloudy regions may be 25% as e!ective as
in cloud-free regions. The assumption of an optically thin
aerosol layer allows *R to be related to the aerosol
transmissivity and re#ectivity (Twomey, 1977)
!
The mass extinction e$ciency of black carbon aerosols
is independent of relative humidity, whereas that of or-
ganic matter increases with increasing relative humidity
because of its hydrophilic nature (Ducret and Cachier,
!
1
992; Novakov and Penner, 1993). Heintzenberg et al.
tꢀR
*
R!"r#
ꢇ !R ,
(7)
(1997) point out the importance of accounting for relative
1!R r
ꢇ
ꢇ
humidity e!ects on aerosol single-scatter albedo. We use
an enhancement factor of 1.7 for increasing relative hu-
midity from 30 to 85% as suggested by Kiehl and Brieg-
leb (1993) for sulphate aerosols and used previously for
where R is the albedo of the surface, r is the re#ectivity
r"(1!e\O)ub] and
t"e\O#(1!b)(1!e\O)u] of the aerosol layer. Here,
ꢇ
[
[
t
is the transmissivity

M. Shekar Reddy, C. Venkataraman / Atmospheric Environment 34 (2000) 4511}4523
4517
organic matter aerosols (Liousse et al., 1996; Penner,
the estimated aerosol lifetime, burdens, optical depth and
direct radiative forcing (Table 6). The uncertainties in all
input parameters are propagated into an estimated un-
certainty in the output variables for each aerosol con-
1
995).
Mineral aerosols both absorb and scatter radiation
depending upon size, with smaller particles scattering
more e$ciently than larger ones. Tegen et al. (1997)
derived the mass extinction coe$cients for sub-micron
mineral aerosols to be 1.0}2.0 mꢀ g\ꢃ, from previous
measurements of sub-micron particles near source re-
stituent and the total PM
aerosol (120% for aerosol
ꢀꢁꢂ
burden, 80% for optical depth and 115% for direct
radiative forcing). The variance in the direct radiative
forcing from the total aerosol is explained by the emis-
sion terms of each constituent, in the proportion of its
burden. The variance in the direct radiative forcing for
each constituent is explained largely by the rates of emis-
sion and wet deposition (in terms of rainfall and scaveng-
ing ratio). Dry deposition was assumed to occur based on
a single deposition velocity for each aerosol constituent.
Uncertainties in regional cloud cover, surface wind vel-
ocities and assumed optical parameters and albedo do
not signi"cantly a!ect the estimated direct radiative forc-
ing. Therefore, improvement is required in the emissions
estimates and scavenging ratios, to increase con"dence in
these predictions.
gions (Gomes et al., 1990; d'Almeida and Sch uK tz, 1983;
Patterson and Gillette, 1977). The single-scattering al-
bedo (ratio of mass scattering coe$cient and mass extinc-
tion coe$cient) of mineral aerosols ranged from 0.91 to
0
.96 for sub-micron mineral aerosols (Tegen et al., 1996).
We use the sub-micron mineral aerosol optical properties
for PM mineral aerosols. Fly-ash optical properties
ꢀ
ꢁꢂ
are assumed the same as those of the mineral aerosols.
3
. Results and discussion
3
.1. Sensitivity analysis
3
.2. Aerosol lifetime
A sensitivity analysis was carried out using the Fourier
amplitude sensitivity test (FAST) of input variables on
The lifetime of aerosols depends on transport and
removal mechanisms (advection, dry deposition and wet
deposition). Calculated lifetimes of black carbon and
organic matter are low in May to October with e$cient
wet deposition, and high in November to April (Figs. 2a
and b). The annual average of monthly mean lifetimes is
Table 5
Aerosol optical properties
Symbol
Parameter
Value
5
.5$4.4 day for black carbon and 4.2$3.9 day for
organic matter. These are in good agreement with the
globally averaged lifetimes of 3.9}7.8 and 3.9}4.5 day,
respectively for black carbon and organic matter (Cooke
and Wilson, 1996; Liousse et al., 1996; Cooke et al., 1999).
Organic matter lifetimes are lower than black carbon,
because of its hydrophilic nature (higher scavenging
ratios) and consequent greater wet deposition. Organic
matter lifetimes are comparable to previously estimated
sulphate lifetimes, with wet deposition being the pre-
dominant removal mechanism (Venkataraman et al.,
aꢇ (mꢀ g\ꢃ)
Mass scattering coe$cient
Black carbon
Organic matter
Mass absorption coe$cient
Black carbon
Mass extinction coe$cient
Mineral aerosols
Fly-ash
1.75}2.00
3.00}5.00
a! (mꢀ g\ꢃ)
a% (mꢀ g\ꢃ)
7.00}9.00
1.0}2.0
1.0}2.0
u (a /a #a )
Single scattering albedo
Mineral aerosols
Fly-ash
ꢇ
ꢇ
!
0.907}0.964
0.907}0.964
1
999).
Table 6
Annual averages of aerosol lifetime, burden, optical depth and direct radiative forcing
Aerosol
constituent
Lifetime
(day)
Burden
(mg m\ꢀ)
Optical depth
Direct radiative forcing
(Wm\ꢀ)
Sulphate!
Organic matter
Black carbon
Fly-ash
Mineral
Total
3.60$2.30
4.22$3.92
5.49$4.39
6.11$10.33
6.11$10.33
4.02$3.98
4.28$5.81
1.01$1.24
7.23$14.61
1.91$4.13
18.4$22.1
0.026$0.026
0.025$0.034
0.010$0.012
0.012$0.023
0.003$0.008
0.08 $0.06
!1.11$1.06
!0.58$0.87
0.26$0.32
!0.25$0.59
!0.06$0.20
!1.73$1.93
!
Venkataraman et al. (1999).

4
518
M. Shekar Reddy, C. Venkataraman / Atmospheric Environment 34 (2000) 4511}4523
Fig. 2. (a) Black carbon aerosol lifetimes range 3}12 day. Removal is not e$cient either by dry deposition (small particle size and low
deposition velocity) or by wet deposition (hydrophobic and low scavenging ratios of 18}350). (b) Organic matter aerosol lifetimes range
2
}11 day. Wet deposition is more e$cient than for black carbon because of hydrophilic nature (scavenging ratios 35}760). (c) Fly-ash
and mineral aerosol lifetimes range 0.4}26 day. Fly-ash and clay-mineral aerosols were assumed to have the same dry deposition
(0.018 cm s\ꢃ) and wet deposition (scavenging ratios 500}1000).
The #y-ash and mineral aerosols (0}2.5 lm diameter)
lifetimes are governed by wet deposition, because of their
low dry deposition velocity (0.018 cm s\ꢃ). The resulting
lifetimes range from 0.4 to 26.0 day (Fig. 2c) with an
annual average of 6.1$10.3 day, in reasonable agree-
ment with the global average lifetime (13 day), calculated
from the detailed dust transport models (Tegen and
Fung, 1995; Tegen et al., 1997).
3
.3. Aerosol burden
The integrated column burden of aerosols is propor-
tional to the lifetime and emission strength. Total
monthly mean aerosol burdens are high, 14.2}
Fig. 3. Monthly mean aerosol burdens range (5}54 mg m\ꢀ)
with lows in monsoon months and highs in the dry season.
5
4
4.4 mg m\ꢀ during November to April, and low,
.9}10.0 mg m\ꢀ during May to October (Fig. 3). Annual
average of total aerosol burden is 18.4$22.1 mg m\ꢀ.
The highest relative contribution to the total aerosol
burden is from #y-ash (40%), followed by organic matter
the spatial distribution of aerosol emissions and rainfall.
Mineral aerosol #uxes are higher in desert regions in
north India, where the monsoon does not set in until
late-July. Our model imposes spatially averaged rainfall
over the entire Indian region, which was high in 1990
from May to August during the monsoon. A large part of
the mineral aerosol emissions (80%) occur during this
period, thus over-estimating wet deposition and under-
estimating burden.
(23%) and sulphate (22%) (Fig. 4). While #y-ash emis-
sions contribute only 23% of total aerosol emissions, its
longer lifetime results in a 40% contribution to the total
burden. Mineral aerosol emissions are higher (25% of
total emissions), but their contribution to total burden is
only 10%. The box model in its present form would under-
estimate mineral aerosol burdens, because of neglecting

M. Shekar Reddy, C. Venkataraman / Atmospheric Environment 34 (2000) 4511}4523
4519
Fig. 4. Relative contribution to annual average aerosol burden
(
18.4$22.1 mg m\ꢀ) is highest from #y-ash followed by organic
Fig. 5. Monthly mean aerosol optical depth ranges 0.04}0.19
with monsoon lows and dry season highs.
matter and sulphate. The mineral aerosol burden is under-
estimated in this model because of neglecting the spatial distri-
bution of emissions and rainfall.
3
.4. Aerosol optical depth
Optical depth of aerosol constituents, calculated as the
product of the burden and the mass extinction coe$cient
Table 5), assume that aerosol species do not interact
(
with each other. The total monthly mean aerosol optical
depths are low during May}October (0.04}0.05) and high
during November}April (0.07}0.19), with an annual aver-
age of 0.08$0.06 (Fig. 5).
These compare well with the measured optical depths
of 0.07}0.17 (at 0.55 lm) at Kaashidhoo (4.9653N,
Fig. 6. Relative contribution to annual average aerosol optical
depth (0.08$0.06) is greatest from sulphate and organic matter
followed by #y-ash and black carbon.
7
3.4663E, which falls just outside the southwest corner of
the box-model area of 8}363N and 70}923E), during the
February and March, 1998 (Satheesh et al., 1999). The
Indian subcontinent was identi"ed as the major source of
aerosols from long-range transport. The estimated op-
tical depth is in the lower part of the range of the
measured total aerosol optical depth at "ve stations in
India (0.10}0.80 during 1986}1989) (Krishna Moorthy et
al., 1993). Our estimate does not include the contribution
from natural mineral aerosols, sea salt, water vapour,
other secondary aerosols (e.g. nitrate, ammonium) and
gases to total optical depth and would therefore be lower
than the measurements. Our model is unable to replicate
the seasonal variation of a measured summer maximum,
which has been attributed to the increased mechanical
production of natural aerosols, and a winter low to
aerosol removal from NE-monsoon rains. The seasonal
variation is not replicated because our model neglects the
spatial distribution of aerosol emissions and rainfall and
imposes a spatial average rainfall over the entire Indian
region. A large part of the mineral aerosol emissions
occur during May}August, and the high monsoon rain-
fall over-estimates wet deposition and under-estimates
the resulting burdens and atmospheric e!ects. A spatially
resolved model would estimate these e!ects more accu-
rately.
accounting for 82% of aerosol optical depth. This
is attributed due to higher burdens and higher mass
extinction coe$cients of these aerosols as compared to
the mineral aerosols. Though, mineral aerosols contrib-
ute 25% of the total emissions, their contribution to
optical depth is only 4%, because of the underestimated
burdens.
We compare our estimates of relative contribution to
optical depth for February and March to that from an
aerosol model for the tropical Indian Ocean (Satheesh et
al., 1999). Using average aerosol mass concentrations at
Kaashidoo for sea salt, nitrate, nss-sulphate and am-
monium, dust and ash, measured optical depth and radi-
ation #ux, Satheesh et al. (1999) estimated the relative
contribution of these species and black carbon to visible
aerosol optical depth, and assigned the balance to `miss-
inga or unaccounted organic matter. Their estimated
contributions were organic matter (24%), nss-sulphate#
ammonium (35%), black carbon (13%), ash (10%) and
dust/mineral aerosol (18%). Our estimates for these
species, organic matter (35%), anthropogenic sulphate
(28%), #y-ash (17%) and black carbon (15%) are in
reasonable agreement with the previous study. Our esti-
mate of dust/mineral aerosol contribution to optical
depth (5%) is much lower than that of Satheesh et al.
(1999) (18%). This results from our under-estimate of
The highest relative contribution to annual average
aerosol optical depth is from sulphate (36%) followed
by organic matter (33%) and black carbon (14%) (Fig. 6),

4
520
M. Shekar Reddy, C. Venkataraman / Atmospheric Environment 34 (2000) 4511}4523
Fig. 8. Relative contribution to annual average direct radiative
forcing (1.73$1.93 W m\ꢀ) is highest from sulphate. Signi"cant
scattering from organic matter and #y-ash aerosols has been
estimated. Absorption by black carbon results in a positive
forcing of 0.26$0.32 W m\ꢀ.
Fig. 7. Monthly mean direct radiative forcing ranges #0.1 to
#
0.7 W m\ꢀ from black carbon and !0.8 to !4.8 W m\ꢀ
from other aerosol constituents.
mineral aerosol burdens, because of neglecting the spatial
distribution of emissions and rainfall. Our estimate of
organic matter contribution to optical depth is 35% and
would be revised downward once the mineral aerosol
estimate is corrected. This estimate, made from a
source/sink mass balance, corroborates the likely large
contribution of organic matter and #y-ash aerosols to
atmospheric optical e!ects.
emissions (PM ) from India for 1990 are 9.4 Tg yr\ꢃ,
ꢀꢁꢂ
with fossil fuel combustion and biomass burning ac-
counting for 62 and 38%, respectively. Adding the an-
thropogenic mineral aerosols from land disturbance
(0}2.5 lm diameter) to the above results in total aerosol
emissions of 12.6 Tg yr\ꢃ. The contribution from various
aerosol constituents is 28% sulphate, 20% organic mat-
ter and 4% back carbon. Coarse fraction aerosols were
not included, as they would not contribute to regional
aerosol burdens and atmospheric e!ects.
3
.5. Direct radiative forcing
The monthly mean aerosol burden ranges from 14.2
to 54.4 mg m\ꢀ with an annual average of 18.4$
The estimated monthly mean direct radiative forcing
2
2.1 mg m\ꢀ, with the largest contribution from #y-ash
is low during May}October (!0.27 to !0.86 W m\ꢀ)
and high during November}April (!1.61 to !4.64
W m\ꢀ) with an annual average of !1.73$
from high ash-content coal burning (40%), followed by
organic matter (23%) and sulphate (22%). The alkaline
constituents of #y-ash could neutralise rainfall acidity
and contribute to the observed high rainfall alkalinity in
this region (Parashar et al., 1996).
1
.93 W m\ꢀ (Fig. 7). The direct forcing from all aerosol
constituents except black carbon aerosols is negative
resulting in net cooling. Organic matter aerosol forcing
Aerosol optical depths vary from 0.04 to 0.19, with an
annual average of 0.08$0.06, sulphate accounting for
(
!0.58$0.87 W m\ꢀ) is negative and comparable to
that from sulphate (!1.10$1.00 W m\ꢀ). The radi-
ative forcing from the mineral aerosols is negligible
3
6%, organic matter for 33% and #y-ash for 14%, in
agreement with the source contribution estimates of
Satheesh et al. (1999). The mineral aerosol contribution
(!0.06$0.20 W m\ꢀ) as compared to other aerosol
constituents. Annual average forcing from black carbon
is #0.26$0.32 W m\ꢀ resulting in net heating. Sul-
phate aerosols contribute 49% of the total forcing,
followed by organic matter (26%) and #y-ash (11%)
(5%) is much lower than the previous estimate (18%)
because of wet deposition from high rainfall in the
months of high emissions and the complete mixing as-
sumption in the box model. Our model results corrobor-
ate the potentially large contributions of organic matter
and #y-ash aerosols to atmospheric optical e!ects in the
Indian region.
(Fig. 8). Once again, the importance of organic matter
and #y-ash aerosols to atmospheric e!ects is indicated.
The annual average radiative forcing is !1.73$
1.93 W m\ꢀ. The major contributors are sulphate aero-
sols (49%) followed by organic matter (26%), black
carbon (11%) and #y-ash (11%). Once again, the im-
portance of organic matter and #y-ash to atmospheric
radiative e!ects is indicated.
The uncertainties in estimated parameters (aerosol life-
time, burden, optical depth and direct radiative forcing)
resulting from uncertainties in input parameters (emission
4
. Conclusions
A box model has been used to compare the estimates
of burden, optical depth and direct radiative forcing from
anthropogenic PM aerosol constituents over the
Indian subcontinent. An aggregate estimate of PM
emissions was made, for the "rst time, for this region.
The total anthropogenic combustion derived aerosol
ꢀ
ꢁꢂ
ꢀ
ꢁꢂ

M. Shekar Reddy, C. Venkataraman / Atmospheric Environment 34 (2000) 4511}4523
4521
rates, deposition and optical parameters) range 80}120%.
The uncertainties in emission and wet deposition rates
contribute signi"cantly to this variance. Therefore, im-
provement is required in the emissions estimates and
scavenging ratios, to increase con"dence in these pre-
dictions.
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