Atmospheric dry deposition to leaf surfaces at a rural site of India

Chemosphere 55 (2004) 1097–1107

www.elsevier.com/locate/chemosphere

Atmospheric dry deposition to leaf surfaces ata rural site of India

Abha Gupta, Ranjit Kumar, K. Maharaj Kumari, S.S. Srivastava *

Department of Chemistry, Faculty of Science, Dayalbagh Educational Institute, Dayalbagh, Agra 282 005, India

Received 4 March 2003; received in revised form 18 August 2003; accepted 27 August 2003

Importance of this Paper: Dry deposition of atmospheric particle plays significant role in transfer of pollutants from the

atmosphere to the earth surface. Vegetation is an important sink as it provides larger surface area. No such study on dry

deposition of major ions (F�, Cl�, NO�3 , SO

2�4 , Na

þ, Kþ, Ca2þ, Mg2þ and NHþ4 ) on natural surfaces has been reported

from this region. This study will help in understanding the processes of dry deposition and it will provide a data set, which

will be helpful in making atmospheric budget, deriving critical loads and in development of model.

Abstract

Dry deposition flux of major ions (Naþ, Kþ, Ca2þ, Mg2þ, NHþ4 , F

�, Cl�, NO�3 and SO2�

4 ) to natural surfaces [guava

(Psidium guyava) and peepal (Ficus religiosa) leaves] are determined at Rampur, a rural site of semi-arid region of India.

Dry deposition flux is the highest for Ca2þ on guava leaves and for NHþ4 on peepal leaves. Overall dry deposition flux is

higher on guava leaves than of peepal leaves. The variation in deposition flux may be due to surface characteristics

(surface roughness) and arrangement of leaves. Peepal leaves are arranged along the axis of the stem, whereas guava

leaves are at right angles to the stem. The deposition flux of cations contributes 66% and 76% of dry deposition of all

major ions on guava and peepal leaves, respectively as soil is major contributor towards dry deposition flux in tropical

regions. ANOVA revealed no significant seasonal difference in deposition, although there is a trend for higher in winter.

Deposition velocities of NHþ4 , NO�

3 and SO2�4 are greater on guava leaves than peepal leaves, which can be attributed to

the rougher surface of the guava leaf.

� 2003 Elsevier Ltd. All rights reserved.

Keywords: Dry deposition flux; Deposition velocities; Leaf surfaces; Major ions

1. Introduction

Atmospheric deposition is an important mechanism

controlling the fate of toxic airborne pollutants and their

transfer from the atmosphere to the natural surfaces.

Atmospheric deposition of particles to ecosystem takes

place via both wet and dry processes. Wet deposition is

removal by precipitation scavenging and, to a lesser

extent, impaction of fog or cloud droplets on vegetation;

*Corresponding author. Tel.: +91-562-212-545; fax: +91-

562-212-226.

E-mail address: [email protected] (S.S. Srivastava).

0045-6535/$ - see front matter � 2003 Elsevier Ltd. All rights reserv

doi:10.1016/j.chemosphere.2003.08.035

and dry deposition includes the uptake of gases at

the surface and the settling and impaction of particles.

For both gases and particles the dry deposition pro-

cess comprises two stages, atmospheric transport and

uptake at the surface. It occurs by several processes,

such as Brownian motion of particles, sedimentation

and impaction (Morselli et al., 1999; Hui-Jung Yun

et al., 2002).

Deposition of particles containing SO2�4 , NO�

3 and

NHþ4 contribute to potent acidification and eutrophica-

tion of ecosystems. Base cation deposition can be

important for nutrient cycling in ecosystems and it can

also neutralize acid inputs (Ruijgrok et al., 1995). De-

spite the importance of this topic dry deposition of

ed.

mail to: [email protected]

1098 A. Gupta et al. / Chemosphere 55 (2004) 1097–1107

particles has received far less attention. Methods used to

assess or predict rates of dry deposition are extremely

diverse, largely because the types of contaminants and

surfaces vary greatly. However, dry deposition fluxes are

difficult to measure directly and instead are often esti-

mated as the product of dry deposition velocity and

corresponding pollutant concentration.

Several techniques of measuring deposited material

have been reported in the literature. Attempts have been

made to estimate dry deposition by leaf washing tech-

nique, micrometerological method, throughfall method,

and watershed mass balance method and inferential and

surface accumulation methods. Surrogate surfaces allow

better control over exposure times, sample extraction

and other parameters than can be provided by natural

vegetation. As a result a variety of surrogate designs

have been reported in the literature. Examples include

dustfall buckets, filter paper, petri dishes and Teflon

plates (Krey and Toonkel, 1974; Huntzicker et al., 1975;

Volchok and Graveson, 1975; Servant, 1976; Davidson

and Friedlander, 1978; Pierson and Cawse, 1979; Lind-

berg et al., 1982).

Surrogate surfaces provide accurate measurements

for rapidly falling particles (Hales et al., 1987) and also

gain credibility as particle size increases (Davidson et al.,

1985) but the performance of these devices to measure

deposition of small particles, like SO2�4 , which lies in the

submicron range (Altshuller, 1983) is often questioned

(Dasch, 1983; Davidson et al., 1985). One of the major

drawbacks of surrogate surfaces is that they are unable

to realistically simulate the processes of gas exchange

between the atmosphere and biological systems (Hicks

et al., 1980). However, theoretical and practical difficul-

ties have limited the number of direct measurement of

atmospheric dry deposition on natural surfaces, and only

a few measurements have been carried out on natural

Fig. 1. Map showing

surfaces, e.g. snow (Ibrahim et al., 1983; Cadle et al.,

1985; Davidson and Wu, 1990; Conklin et al., 1993),

surfaces of building materials (stone, metal, glass etc.)

(Lovett and Kinsman, 1990; Cobourn et al., 1993; Saiz-

Jimnez, 1993; Kumar et al., 2001, 2002), grass (Allen

et al., 1991), leaves (Lindberg et al., 1990; Bytnerowicz

et al., 1991; Granat and Richter, 1995; Kumar et al.,

2000), and coniferous forest (Johansson, 1987; Erisman

et al., 1997; Altimir et al., 2002; Pryor et al., 2002).

Few studies on dry deposition have been reported in

urban, semi-urban and rural areas of India using sur-

rogate surface, although dry deposition is the major

deposition process in this region, (Tripathi et al., 1991;

Rao et al., 1992; Saxena et al., 1992; Pandey et al., 1995;

Singh et al., 1999; Kumar et al., 2002), and no studies of

dry deposition on natural surfaces have been done. The

aim of the present investigation is to characterize dry

deposition of major ions on leaf of guava (P. guyava)

and peepal (F. religiosa) and to determine the deposition

velocity.

2. Materials and methods

2.1. Site description

Rampur is located south east of Agra city (27�100 N,

78�050 E) at a distance of about 75 km. The population

density is about 100 people km�2. There are no major

cities or towns within a radius of 35 km. The sampling

site is located on the top of a sand dune about 25 m in

height, which is sparsely covered with bushes and Acacia

trees. The immediate vicinity of sampling site has only

Acacia trees. River Yamuna is on the northern periphery

of the sampling site at Rampur. The NE, N, NW

directions of the sampling site are totally barren up to

sampling site.

Table

1

Data

ofmeteorologicalparametersduringthestudyperiod

Months

Tem

perature

(�C)

Relativehumidity(%

)Solarradiation(W

/m2)

Windspeed(kmh�1)

Wind

direction

Minim

um

Maxim

um

Average

Minim

um

Maxim

um

Average

Minim

um

Maxim

um

Minim

um

Maxim

um

Average

January

7.9

18.1

13.0

68

96

82

1.2

7.5

10

15

12.5

NW,N

February

10.1

22.6

16.3

49

90

69.5

1.5

8.3

10

15

12.5

W,NW

March

15.4

29.4

22.4

39

82

60.5

1.7

9.0

15

20

17.5

W

April

22.5

36.8

29.6

21

58

39.5

1.8

9.1

10

28

19.0

NW

May

28.6

38.5

33.5

29

59

44

2.0

9.7

22

30

26.0

W,NW

June

27.9

34.3

31.1

56

82

69

1.9

9.8

20

30

25.0

NW

July

26.9

31.8

29.4

71

92

81.5

1.6

7.5

15

25

20.0

E,SW

August

26.7

32.4

29.5

66

90

78

1.3

5.3

10

15

12.5

W

September

25.1

33.5

29.3

50

85

67.5

1.4

6.6

15

20

17.5

W

October

20.6

31.7

26.1

44

84

64

1.5

8.4

710

8.5

NW

Novem

ber

14.0

25.8

19.9

47

85

66

1.6

7.0

10

10

10

N,NW

Decem

ber

8.8

20.5

14.7

59

91

75

1.2

6.2

310

6.5

NE,N

A. Gupta et al. / Chemosphere 55 (2004) 1097–1107 1099

15 km distance and agricultural fields are present at a

distance of 2 km in the S, SE and SW directions (Fig. 1).

Table 1 shows the monthly meteorological conditions

during the study period at Rampur.

2.2. Sample collection

2.2.1. Dry deposition collection

Dry deposition samples (n ¼ 85) were collected from

eight leaves of guava (P. guyava) and four leaves of

peepal (F. religiosa). The leaves while attached to living

tree were marked and washed with deionised water using

a sprayer and air dried prior to exposure. The dry

deposition samples were collected after 72 h exposure.

The surface washing method was employed to collect the

dry deposition (Davidson and Wu, 1990), the leaf sur-

face was washed off into polyethylene bottle at the site

and the volume was made up to 100 ml with deionised

water. The collected samples were centrifuged and

supernatant was divided into two parts, one part was

treated with chloroform and preserved for anions and

ammonium analysis while other part was preserved with

1% nitric acid (v/v) for the cations analysis. All the

samples were stored in the refrigerator till analysis.

2.2.2. Aerosol and gas phase collection

Aerosol samples were collected using SKC, PCXR8

battery operated universal pump with programmable

start/stop timer while gaseous SO2, NH3 and HNO3

samples were collected using SKC Anasorbent sampling

tubes, details of which can be found elsewhere (Gupta

et al., 2003). The size of collected aerosol particles was

0.95 lm.

2.3. Chemical analysis

A dionex DX-500 ion chromatograph system equip-

ped with guard column (AS 11A), separator column

(AS11 ASC), self regenerating suppressor (SRS) and

conductivity detector (CD-20) was used for the analysis

of major anions (F�, Cl�, NO�3 and SO2�

4 ) using 10 mM

NaOH as eluent at flow rate of 1.0 mlmin�1. NHþ4 was

analyzed by UV–VIS Spectrophotometer (Shimadzu

Model-1601) using the indophenol blue method (Harri-

son and Perry, 1986). The major cations (Naþ, Kþ, Ca2þ

and Mg2þ) were analyzed by double beam atomic

absorption spectrophotometer (Perkin Elmer-2380) with

an air acetylene flame. Naþ and Kþ were measured in

the emission mode while Ca2þ and Mg2þ were measured

in the absorption mode.

The ion chromatograph was calibrated daily with a

standard solution of 2 mg l�1 prepared daily from 1000

mg l�1 stock standard solutions of F�, Cl�, NO�3 and

SO2�4 . Variation in standard peak heights and peak areas

was found to be less than 5% between calibrations which

were carried out after every five samples. Field blanks


were collected by sampling for 1 min. The concentra-

tions of ions in blanks were below detection limits.

3. Results and discussion

3.1. Dry deposition

Arithmetic mean and standard deviation of dry

deposition flux of major ions on the surfaces of both leaf

types were presented in Table 2. The deposition flux was

highest for Ca2þ and it decreased in the order of

Kþ > NHþ4 > Mg2þ > SO2�

4 > Naþ > Cl� > NO�3 > F�

on guava leaves. In the case of peepal leaves the highest

deposition flux was for NHþ4 and decreased in the order

of Kþ > Ca2þ > Naþ > Mg2þ > SO2�4 > Cl� > F� >

Table 2

Annual (N ¼ 85) dry deposition flux (mgm�2 d�1) on natural

surfaces

Species Guava leaf Peepal leaf

AM±SD AM±SD

F� 0.7± 0.4 0.3 ± 0.2

Cl� 1.2± 1.1 0.3 ± 0.2

NO�3 0.7± 0.6 0.2 ± 0.1

SO2�4 1.5± 0.9 0.5 ± 0.2

Naþ 1.2± 0.8 0.8 ± 0.5

Kþ 1.9± 1.1 0.9 ± 0.5

Ca2þ 1.9± 1.1 0.9 ± 0.5

Mg2þ 1.6± 0.9 0.5 ± 0.4

NHþ4 1.7± 1.2 1.0 ± 0.6

Note: AM¼ arithmetic mean, SD¼ standard deviation.

Fig. 2. Percentage contribution of each ion towards total dry

deposition on guava leaves.

NO�3 . Overall dry deposition fluxes were higher on

guava leaves. This may be due to surface characteristics

(surface roughness) and arrangement of leaves. Peepal

leaves are arranged along the axis of the stem, whereas

guava leaves are at right angles to the stem. This results

in higher deposition of coarser particles on guava leaves

in comparison to peepal leaves. In addition, deposition

on peepal leaves may be inhibited because of its waxy

surface and metabolic characteristics (transpiration

and guttation) (Haberlandt and Drummond, 1928).

ANOVA revealed no significant variation in deposition

flux of each ion, however numerical values were different

on both leaves.

The percentage contribution of each ion towards

total dry deposition on both leaves is shown in Figs. 2

and 3. The dry deposition flux of cations contributed

66% and 76% of dry deposition on guava and peepal

leaves, respectively at the present site. It is well known

that air borne soil particles are major contributor to-

wards dry deposition flux at tropical sites (Saxena et al.,

1997; Satsangi et al., 2002). Ca2þ is considered as soil

tracer in this region, so to investigate the possible

sources of dry deposition, the ratios of various ions with

respect to Ca2þ were calculated and compared with ratio

of local soil (Table 3). In the case of guava leaf the dry

deposition ratio of NHþ4 /Ca

2þ, Kþ/Ca2þ, Naþ/Ca2þ and

Mg2þ/Ca2þ were 54–93%, similar to that in local soil

while in peepal leaf 42–77% ratios were similar to local

soil suggesting an influence of soil.

The deposition flux of SO2�4 , NO�

3 and NHþ4 are

contributed by both particulate sulphate, nitrate and

ammonium and their gaseous species sulphur dioxide,

nitric acid and ammonia. To determine the percentage

Fig. 3. Percentage contribution of each ion towards total dry

deposition on peepal leaves.

Table 3

Ratios with respect to Ca2þ in soil and dry deposition

Naþ Kþ Mg2þ NHþ4

Guava leaf 0.66 1.04 0.88 0.99

Peepal leaf 0.98 1.24 0.65 1.39

Soil 0.82 1.02 1.27 0.80

Percentilea (guava) 61% 88% 93% 54%

Percentilea (peepal) 56% 76% 77% 42%

aPercentile indicates the percentage of ratios in dry deposi-

tion which matches with ratios of soil.


contribution of particulate and gaseous species towards

total deposition on leaf surface, deposition flux of par-

ticulate SO2�4 , NO�

3 and NHþ4 was calculated theoreti-

cally by multiplying their atmospheric concentrations

measured during the study period with their reported

deposition velocity (0.15, 0.41 and 0.44 cm s�1 for SO2�4 ,

NO�3 and NHþ

4 , respectively) on leaves of Ceanothus

crassifolius (Bytnerowicz et al., 1987). On subtracting

the obtained deposition flux of particulate sulphate, ni-

trate and ammonium from experimentally measured dry

deposition flux, the dry deposition flux of gaseous SO2,

HNO3 and NH3 are obtained (Table 4). Gaseous SO2,

HNO3 and NH3 flux contribute about 77%, 51% and

75% towards total dry deposition flux of SO2�4 , NO�

3 and

NHþ4 on guava leaves.

Table 4

Atmospheric concentration (lgm�3) and calculated dry deposition flux

HNO3 and NH3 on guava leaves

Species

(I)

Particulate

concentration

(II)

Theoretical

Vda (III)

Calculated

of particula

(IV¼ II� I

SO2�4 2.7 ± 1.6 0.15 0.35

NO�3 1.1 ± 1.3 0.41 0.39

NHþ4 1.1 ± 0.4 0.44 0.42

a Bytnerowicz et al. (1987).

Table 5

Correlation matrix of dry deposition fluxes on guava leaves

Species F� Cl� NO�3 SO2�

4 N

F� 1.00

Cl� 0.65�� 1.00

NO�3 0.05 0.23� 1.00

SO2�4 0.50�� 0.64�� 0.65� 1.00

NHþ4 0.25� 0.25� 0.25� 0.57�� 1

Naþ 0.12 0.24�� 0.30�� 0.20 0

Kþ 0.08 0.12 0.34�� 0.23�� 0

Ca2þ 0.25�� 0.35�� 0.60�� 0.73�� 0

Mg2þ 0.09 0.20 0.39�� 0.63�� 0

* p ¼ 0:05.** p ¼ 0:01.

3.2. Source interpretation

Dry deposition fluxes for guava and peepal leaves at

Rampur were examined using correlation matrix to

predict potential precursor ions. Correlations between

ions suggest likely sources of pollutants (Tables 5 and 6).

It is evident from correlation matrices that SO2�4 and

NO�3 are highly correlated (r ¼ 0:65, p ¼ 0:01), which

indicates their likely origin from similar sources. Ca2þ

and Mg2þ deposition fluxes were correlated on both

guava (r ¼ 0:85, p ¼ 0:01) and (r ¼ 0:75, p ¼ 0:01) on

peepal leaves, which implies their association and

probable origin from soil. Mg2þ and SO2�4 (r ¼ 0:63,

p ¼ 0:01), Ca2þ and NO�3 (r ¼ 0:60, p ¼ 0:01) were also

correlated indicating that SO2�4 and NO�

3 are partly

contributed by soil. Meanwhile correlations of NHþ4

with NO�3 and SO2�

4 were 0.33 and 0.57, respectively,

which indicates that NHþ4 is associated more with SO2�

4

than NO�3 . An earlier study on surrogate surfaces at the

same region showed similar correlation of NHþ4 with

NO�3 and SO2�

4 (Singh et al., 1999).

Factor analysis was also used to detect common

variability and imply source identity between deposition

and specific sources. Using principle component analysis

(SPSS version 3.0), the factors with eigenvalues greater

than one were considered for varimax rotation to obtain

(mgm�2 d�1) of particulate SO2�4 , NO�

3 , NHþ4 and gaseous SO2,

flux

tes

II)

Experimentally observed flux

(V)Flux of gases

(VI ¼ V� IV)

Surface type Flux SO2

Guava leaves 1.5± 0.9 1.15

Guava leaves HNO3

0.8± 0.7 0.41

Guava leaves NH3

1.7± 1.2 1.28

Hþ4 Naþ Kþ Ca2þ Mg2þ

.00

.30�� 1.00

.53�� 0.62�� 1.00

.44�� 0.72�� 0.72�� 1.00

.48�� 0.42�� 0.63�� 0.84�� 1.00

Table 6

Correlation matrix of dry deposition fluxes on peepal leaves

Species F� Cl� NO�3 SO2�

4 NHþ4 Naþ Kþ Ca2þ Mg2þ

F� 1.00

Cl� 0.28�� 1.00

NO�3 )0.03 )0.01 1.00

SO2�4 0.28� 0.55�� 0.65�� 1.00

NHþ4 )0.11 0.15 0.16 0.12 1.00

Naþ 0.18 0.44�� )0.09 0.40�� 0.22 1.00

Kþ 0.16 0.31�� )0.08 0.33�� 0.09 0.40�� 1.00

Ca2þ 0.03 0.31�� )0.03 0.74�� 0.29�� 0.54�� 0.42�� 1.00

Mg2þ 0.07 0.16 0.12 0.50�� 0.38�� 0.24� 0.24� 0.75�� 1.00

* p ¼ 0:01.** p ¼ 0:05.


the final factor matrix. In case of guava leaves, 72% of

variance was explained by three factors, the remaining

28% of the variance being unique to individual variables

(Table 7). The first factor accounted for 42.9% of the

total variance and included Naþ, Kþ, Ca2þ, Mg2þ and

NHþ4 , which may indicate a soil source. The second

factor which explained 19.6% of the total variance and

included F�, Cl� and SO2�4 , indicates a source attribut-

able to biomass combustion. The third factor accounted

for 9.6% of the total variance and included NO�3 , indi-

cating the contribution of atmospheric HNO3 deposi-

tion.

In the case of peepal leaves, the corresponding pro-

portion of the total variance related to the three factors

was 63.3% (Table 8). The first factor accounted for

34.1% of the total variance and grouped Kþ, F�, Cl�

and SO2�4 , again indicating biomass combustion sources.

The second factor explained 15.7% of the total variance

and included Naþ, Ca2þ, Mg2þ and NHþ4 , which may

have been contributed by soil. The third factor ac-

counted for 13.6% of the total variance and included

Table 7

Rotated factor matrix for dry deposition on guava leaves

Variables Factors loading

I II

F� 0.11 0.85

Cl� 0.13 0.88

NO�3 0.21 0.09

SO2�4 0.16 0.78

Naþ 0.77 0.13

Kþ 0.89 )0.03Ca2þ 0.86 0.24

Mg2þ 0.72 0.06

NHþ4 0.57 0.23

Eigenvalue 3.86 1.76

Proportion of variance (%) 42.9 19.6

Cumulative % 42.9 62.5

Source indicated Soil Biomas

NO�3 , again indicating the contribution of atmospheric

HNO3 deposition. Although biomass combustion is

known to contribute Kþ, the greater amount of coarse

particle (soil) deposition as is evidenced by higher flux to

guava than peepal, might have offset the contribution of

Kþ from biomass combustion in case of guava leaves.

3.3. Seasonal variation

Average dry deposition flux of all major ions for

summer, monsoon and winter season is shown in Fig. 4.

Two-way analysis of variance (ANOVA) revealed no

significant seasonal variation, however fluxes tended to

be higher in winter, intermediate in summer and lowest

during the monsoon for cations, while variation in an-

ions was less pronounced. The particulate concentra-

tions (Table 9) were higher in summer as compared to

winter; however, the variation in particulate concentra-

tions was slight and statistically not significant. The

variation in flux may be due to variations in meteoro-

logical conditions. The low monsoon fluxes are evidently

Communality

III

)0.14 0.76

0.13 0.82

0.90 0.88

0.23 0.68

)0.12 0.61

0.17 0.83

0.02 0.80

0.40 0.67

0.06 0.44

0.86

9.6

72.1

s combustion Atmospheric reactions

Table 8

Rotated factor matrix for dry deposition on peepal leaves

Variables Factors loading Communality

I II III

F� 0.66 )0.26 )0.01 0.76

Cl� 0.75 0.17 )0.003 0.82

NO�3 0.08 0.12 0.90 0.88

SO2�4 0.77 0.23 0.33 0.68

Naþ 0.56 0.45 )0.30 0.61

Kþ 0.50 )0.35 )0.34 0.83

Ca2þ 0.31 0.77 )0.22 0.80

Mg2þ 0.10 0.77 0.08 0.67

NHþ4 )0.09 0.70 0.06 0.44

Eigenvalue 3.06 1.41 1.22

Proportion of variance (%) 34.1 15.7 13.6

Cumulative % 34.1 49.8 63.4

Source indicated Biomass combustion Soil Atmospheric reactions

Fig. 4. Seasonal variation of dry deposition flux (mgm�2 d�1) on natural surfaces (guava and peepal leaves).


due to washout effects of frequent rain showers and

damping down of soil surfaces. On the contrary, in

winter temperature is low and calm conditions prevail

promoting stagnation of pollutants which is further

enhanced by frequent temperature inversions. More-

over, the persistent of humid and foggy conditions

during the winter would tend to maximize deposition

rates through deposition by fog and checking resus-

pension due to moistening of the collector surface

(Saxena et al., 1997). Additionally, the alkaline nature of

deposited material and moistening of surface would fa-

vour absorption of gases and particles. Previous studies

on deposition to surrogate surfaces in this region have

also reported highest fluxes in winter followed by sum-

mer and monsoon for major ions (Saxena et al., 1997;

Satsangi et al., 2002).

Table 9

Concentrations (lgm�3) of major ions in aerosol

Species Summer Monsoon Winter

NHþ4 0.9± 0.4 1.1± 0.3 1.1 ± 0.4

Naþ 1.3± 0.4 0.6± 0.6 1.1 ± 1.1

Kþ 3.0± 1.5 0.3± 0.3 2.2 ± 0.9

Ca2þ 1.4± 0.4 1.2± 0.5 1.0 ± 0.6

Mg2þ 0.5± 0.3 0.3± 0.1 0.2 ± 0.1

F� 1.0± 0.4 1.0± 0.2 0.9 ± 0.2

Cl� 2.1± 1.0 2.5± 0.9 1.7 ± 1.1

NO�3 1.9± 1.8 0.7± 1.0 1.1 ± 0.9

SO2�4 3.2± 2.3 2.6± 1.1 2.3 ± 1.2


3.4. Deposition velocity

Deposition velocity is used as a measure of mass

transfer into the canopy (Hosker and Lindberg, 1982)

and is calculated by dividing the deposition flux of major

ions by their respective atmospheric concentrations. The

deposition fluxes of SO2�4 , NO�

3 and NHþ4 from guava

and peepal leaves were divided by their respective at-

mospheric concentrations which were measured at the

same site and during the same study period. Particulate

concentration of SO2�4 , NO�

3 and NHþ4 were 2.6 ± 1.6,

1.1 ± 1.3 and 1.0 ± 0.4 lgm�3 respectively while that of

SO2, HNO3 and NH3 were 3.7 ± 2.2, 0.7 ± 0.6 and

6.7± 4.2 lgm�3 respectively.

The deposition velocities (Vd) of SO2�4 , NO�

3 and

NHþ4 were greater on guava leaves than peepal leaves

(Table 10). The higher Vd on guava leaves may be due to

leaf characterstics, guava leaves being rougher than

Table 10

A summary of deposition velocities (cm s�1) derived from field experi

Variables Technique Mean

SO2�4 Micrometeorological 0.6 ± 0.6

Foliar extraction 0.2 ± 0.2

Surrogate surfaces 0.3 ± 0.3

Throughfall 1.0 ± 0.4

Cassia leaf 0.5 ± 0.6

Guava leaf 0.7 ± 0.4

Peepal leaf 0.2 ± 0.1

NO�3 Foliar extraction 0.2 ± 0.1






NHþ4 Foliar extraction 0.44






peepal leaves. Dry deposition velocities were highest for

NHþ4 on both leaves, 0.8 and 0.5 cm s�1 for guava and

peepal leaves, respectively. The Vd of NO�3 and SO2�

4 on

guava leaves was 0.6 and 0.7 cm s�1 respectively while on

peepal leaves it was 0.2 cm s�1 for both species.

A comparison of deposition velocities from different

published studies is shown in Table 10. These data were

separated into three categories based on collection

techniques, throughfall, surrogate and foliar extraction.

Deposition velocities observed by the present study were

lower than those measured by the throughfall method.

Average Vd for SO2�4 , NO�

3 and NHþ4 derived on natural

surface (guava and peepal leaves) were lower than for

throughfall experiment. This might be due to fluxes from

the present study being confined to the dry period while

in throughfall experiments there may be contamination

from wet deposition. In addition collection of samples

through many layers may also result in higher fluxes

in throughfall method (Bytnerowicz, 1987). Deposition

velocities to leaves are typically higher than to surrogate

surfaces (Dasch, 1985; Bytnerowicz, 1987), possibly due

to surface roughness and the tendency for surrogate

surfaces to collect mainly coarse particulates (Davidson

et al., 1982) while leaf surfaces are prone to deposition of

gases as well as particles. The deposition velocities of

NHþ4 , SO

2�4 and NO�

3 by foliar extraction method are

lower than present study.

The observed higher Vd of NHþ4 may be due to

deposition of gaseous NH3 as its level is quite high in

comparison to particulate NHþ4 at the present site. At

sites where aerosol is basic in nature due to calcareous

nature of soil and road dust, most of the sulphuric acid

ments using different techniques along with present study

N Range Source

20 0.01–2.9 Ruijgrok et al. (1995)

5 0.05–1.2 -do-

26 0.01–0.9 -do-

9 0.4–2.0 -do-

50 0.03–3.4 Kumar et al. (2003)

85 0.1–1.7 Present study


7 0.1–0.4 Ruijgrok et al. (1995)

3 0.1–0.7 -do-

9 0.3–2.3 -do-

50 0.04–3.3 Kumar et al. (2003)



1 – Ruijgrok et al. (1995)

7 0.1–0.6 -do-

7 0.5–1.4 -do-

50 0.4–3.2 Kumar et al. (2003)




and nitric acid preferentially react with these aerosol

particles or SO2�4 and NO�

3 are formed after adsorption

of SO2 and NO2 on these calcareous particles. Hence

transformation of gaseous NH3 into particulate NHþ4 is

less (Gupta et al., 2003). Size segregated study from this

region shows unimodal distribution for NHþ4 and bi-

modal for SO2�4 (Kulshrestha et al., 1998). This indicates

that in addition to anthropogenic sources SO2�4 is also

contributed by terrigenous sources which may also be

the reason for different Vd of SO2�4 and NO�

3 .

4. Conclusion

Dry deposition was collected on natural surfaces

[guava (P. guyava) and peepal (F. religiosa) leaves] at

Rampur, a rural site of semi-arid region. Dry deposition

flux was the highest for Ca2þ and it decreased in the

order of Kþ > NHþ4 > Mg2þ > SO2�

4 > Naþ > Cl� >NO�

3 > F� on guava leaves. In the case of peepal leaves

the deposition flux was highest for NHþ4 and it decreased

in the order of Kþ > Ca2þ > Naþ > Mg2þ > SO2�4 >

Cl� > F� > NO�3 . Overall dry deposition flux was

higher on guava leaves than of peepal leaves, which may

be due to surface characteristics (surface roughness) and

arrangement of leaves. Peepal leaves are arranged along

the axis of the stem, whereas guava leaves are at right

angles to the stem. The deposition flux of cations con-

tribute 66% and 76% of dry deposition on guava and

peepal leaves, respectively as soil is major contributor

towards dry deposition flux at tropical region. The high

correlation between SO2�4 and NO�

3 indicates their likely

origin from similar sources. Ca2þ and Mg2þ are signifi-

cantly correlated on both guava and peepal leaves,

which implies their association and probable origin from

soil. Factor analysis revealed three likely sources, I in-

cludes Naþ, Kþ, Ca2þ, Mg2þ and NHþ4 , which may be

contributed by soil. II includes F�, Cl� and SO2�4 , which

may be attributed to biomass combustion, III includes

NO�3 , which indicates the contribution of atmospheric

HNO3 deposition. ANOVA revealed no significant

seasonal difference in deposition. The deposition veloc-

ities of NHþ4 , NO�

3 and SO2�4 were greater on guava than

peepal leaves, which were attributed to leaf character-

istics, in particular the rougher surface of guava com-

pared to peepal leaves.

Acknowledgements

We wish to thank Prof. Satya Prakash, Head, and

Department of Chemistry of this Institute for providing

necessary facilities. Sampling assistance by Mr. Dayal

Saran is greatly appreciated. Financial assistance from

DST (ESS/63/166/98) is gratefully acknowledged. One of

the authors (RK) acknowledges CSIR, New Delhi for

SRF.

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