The Effect of Air Pollution

8/8/2019 The Effect of Air Pollution

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THE EFFECT OF AIR POLLUTION ON YIELD AND QUALITY OF

MUNG BEAN GROWN IN PERI-URBAN AREAS OF VARANASI

M. AGRAWAL1, B. SINGH1, S. B. AGRAWAL1, J.N.B. BELL2 and F. MARSHALL3,1Department of Botany, Banaras Hindu University, Varanasi-221 005, India; 2Department of

Environmental Policy, Imperial College London, Silwood Park, Ascot, Berks, SL5 7PY; 3Science and

Technology Policy Research, Freeman Centre, University of Sussex, Brighton, BN1 9QE, U.K.

(author for correspondence, email: [email protected])

Received 27 October 2003; accepted 16 August 2005

Abstract. There is growing concern that air pollution may have adverse impacts on crops in develop-

ing countries, yet this has been little studied. This paper addresses this issue, for a major leguminous

crop of the Indian sub continent, examining the effect of air pollution in and around an Indian city.

A field study was conducted using a gradient approach to elucidate the impact of air pollutants on

selected production characteristics of Vigna radiata L. cv. Malviya Jyoti (mung bean) plants grown

from germination to maturity at locations with differing concentrations of air pollutants around peri-

urban and rural areas of Varanasi. The 6 -h daily mean SO 2, NO2 and O3 concentrations varied from

8.05 to 32.2 ppb, 11.7 to 80.1 ppb and 9.7 to 58.5 ppb, respectively, between the sites. Microclimatic

conditions did not vary significantly between the sites. Changes in plant performance at different sites

were evaluated with reference to ambient air quality status. Reductions in biomass accumulation and

seed yields were highest at the site experiencing highest concentrations of all three gaseous pollutants.

The magnitude of response indicated that at peri-urban sites SO2, NO2 and O3 were all contributing

to these effects, whereas at rural sites NO2 and O3 combinations appeared to have more influence.The quality of seed was also found to be negatively influenced by the ambient levels of pollutants. It

is concluded that the air pollution regime of Varanasi City causes a major threat to mung bean plants,

both in terms of yield and crop quality, with serious implications for the nutrition of the urban poor.

Keywords: India, mung bean, nitrogen dioxide, ozone, plant response, seed quality, sulphur dioxide,

yield

1. Introduction

Crop production is highly dependent upon environmental conditions among which

air quality can play a major role. Studies conducted in North America and Europehave clearly shown significant yield losses in a range of major crop species due to

ambient air pollutant levels in rural areas (Heck et al., 1988; Jageret al., 1994). The

crop loss is mainly attributed to the widespread occurrence of ozone (O3) in agricul-

tural regions (Heck et al., 1988). Studies conducted on the adverse effect of O3 on

crops also confirmed reductions in rice yield in Japan (Kobayashi et al., 1995), bean

yield in UK and France (Sanders et al., 1992), and Netherlands (Tonneijck and Van

Dijk, 1998). Whilst the number of experimental studies from developing countries

is very limited, there are indications of major yield reductions due to ambient air

Water, Air, and Soil Pollution (2006) 169: 239254 C Springer 2006


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240 M. AGRAWAL ET AL.

pollution. For example, Wahid et al. (1995) demonstrated a grain yield reduction of

46 and 38% for two cultivars of winter wheat in an open top chamber study in the

vicinity of Lahore, Pakistan using ambient and charcoal filtered air. Maggs et al.

(1995) have further shown significant reductions in various yield parameters of both

wheat and rice near Lahore at annual mean nitrogen dioxide (NO2) concentrations

of 2025ppb and 6 h mean O3 concentrations reaching 60 ppb in certain months. In

both cases the effect was attributed primarily to O3. A study conducted in the United

Kingdom simulating Chinese agriculture and an O3 concentration regime similar

to Chongquing (1575 ppb, 7 h daily mean > 59 ppb, over 28 day period) showed

typical foliar injury to rice, egg plant, tomato and pepper and growth reductions in

wheat, maize, radish and zucchini along with those showing foliar injury (Zheng

et al., 1998).In India, high levels of SO2 can result in localised impacts on crops as demon-

strated in the vicinity of industrial complexes. For example, Singh et al. (1990) have

shown yield reductions in several field grown crop species downwind of industrial

sources of SO2 in the Obra- Renukoot- Singrauli area of the Sonbhadra district

in India. Agrawal et al. (2003) have shown significant reductions in physiological

characteristics, pigments and above ground biomass ofBeta vulgaris, Triticum aes-

tivum, Brassica compestris and Vigna radiata at sites experiencing higher ambient

concentrations of SO2, NO2 and O3 as compared to sites with very low levels of

pollutants.

Air pollution is one of a number of specific environmental threats to crop yield

in urban and peri-urban areas. The definition of peri-urban is subject to debate,

but in the present study is taken to be the urban fringe, where pockets of agriculture

occur within and close to built up areas. Urban and peri-urban agriculture will

characteristically be subject to a mixture of both primary and secondary pollutants,

but there are very limited field based data to demonstrate the impacts on crop

production in these areas.

Urban populations have increased dramatically in India over the past few

decades, with consequent increases in the number of vehicles and industries. Open

burning of solid wastes and domestic combustion of coal are additional sources

of urban pollution. The Indian national ambient air quality data demonstrate the

increasing emissions of a range of phytotoxic air pollutants. Annual average SO 2concentrations range from 4 to 15 ppb in the majority of the regions where mea-

surements have been made. Industrial belts and metropolitan cities show annualaverage SO2 concentrations ranging from 23 to 32 ppb. (Agrawal et al., 1999). The

annual average NO2 concentrations ranged from 5 to 47 ppb, with high levels in

metropolitan cities. (Agarwal et al., 1999). High concentrations of the secondary

photo-oxidant, O3, have also been reported from some urban, periurban and forested

parts of the country (Pandey et al., 1992; Khemani et al., 1995; Singh et al. 1997),

but it is difficult to make generalisations due to an extremely limited amount of

monitoring for this pollutant.


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MUNG BEAN YIELD AND AIR POLLUTION IN VARANASI 241

If there is a direct impact of air pollutants in cities on crop yield this has impli-

cations in terms of the livelihoods of producers and food security for inhabitants of

urban and peri-urban areas. In contrast to many industrialised countries, increased

food production is a major goal in the developing world, and urban and peri-urban

agriculture plays a vital role in the nutrition of city dwellers, particularly the poor,

in many developing countries (UNDP, 1996).

Mung bean is widely grown by local producers in and around Varanasi, but little

is known about the response of this plant to increasing ambient air pollution levels

under field conditions (Varshney et al., 1997; Agrawal et al., 2003). This paper

reports the results of an experiment conducted to assess the impacts of ambient air

pollution in Varanasi city on yield and quality of a local cultivar of mung bean plants

(Vigna radiata) at peri-urban and rural locations with differing concentrations ofair pollutants.

2. Materials and Methods

2.1. STUDY AREA

Thestudywas conductedin theperi-urban andruralenvironment of Varanasi located

in the eastern Gangetic Plain of the Indian subcontinent at 2518N 8301E and

76.19 m above sea level. The city has a population of about 1.8 million.

The climate of the area is tropical monsoonic with three distinct seasons: summer

(March to June), rainy (July to October) and winter (November to February). The

present experiment was conducted during summer 1998 (March to June), when

the mean monthly maximum temperature ranged from 34 to 41 C, mean monthly

minimum temperature from 23 to 29C and the daylight duration from 11 to 14 h.

Themean monthly maximum relative humidity varied from 60 to 90%and minimum

from 35 to 80%. The first half of the summer season experienced strong hot winds

and high temperatures, while the second half was generally hot and humid. The

wind direction was predominantly easterly or north westerly and wind speed varied

from a minimum of 3.04km h1 in April toa maximum of 5.8 km h1 in June. Total

rainfall during the experimental period was 41.5 mm.

2.2. STUDY SITES

Nine study sites were selected along a NW-SE transect in peri-urban and rural

locations of Varanasi city based on an earlier report of a gradient of declining

air pollutant levels towards the SE in 1989 (Pandey et al., 1992) (Figure 1). The

characterisation of sites in terms of location from the city centre, land use and

pollutant sources around are detailed in Table I. Plants were kept in an unshaded

open area, and received uniform light at all sites. Micrometeorological variations

in temperature were 0.1 to 0.5 C and relative humidity 12% between the sites.


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Figure 1. Map of Varanasi city indicating the experimental study sites and major land use categories.

2.3. AIR POLLUTION MONITORING

Air quality monitoring was performed for 6 h daily between 0.900 and 15.00 twice

a week for SO2, NO2 and O3 using wet chemical methods at sites 1, 3, 4, and

9. Monitoring commenced directly after transfer of germinated plants (March 1,

1998) to the field and continued up to crop maturity (June 30, 1998). No continuous

monitors are available in Varanasi and this wet chemical-sampling regime, which

produced data in the form of six hourly means, was the best available option. At

the other sites, gaseous monitoring was conducted occasionally (twice a month


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TABLE I

Characteristics of the study sites

Direction

from the city

Sites Name of the area centre Land use/pollution sources

1. Tikari South Rural area with agricultural land; a bypass

linking Varanasi and Allahabad within 1km N.

2. Seer Goverdhan Southeast Peri-urban area with agricultural land; a

bypass linking Varanasi and Allahabad within 1km S.

3. Banaras Hindu South Residential locality with official buildings,

University South dense plantations and cultivated land

4. Sunderpur Southwest Residential locality, vegetable growing

fields and gardens, road transections

5. Hedgawar nagar West Cultivated land, orchards and plant

nurseries; close to diesel locomotive works

6. Lahartara West Medium density population, motor

workshops, small scale industries, cold

stores, transport companies

7. Chandpur West Small scale industries, nurseries, residential

localities; 1 km S from a highway.

8. Government Northwest Cultivated land, road intersections, small scale

Agricultural. scale industries and petrol stations; along a

Farm major highway

9. Bhullanpur Northwest Cultivated land, road intersections, small

scale industries and petrol stations; along a

major highway

at fortnightly interval for 6 h) to improve understanding of the overall pattern of

pollutants. SO2 NO2 and O3 were scrubbed separately in tetrachloromercurate,

NaOH (0.1 N) and buffered KI (0.1 N), respectively, from 08.00 to 14.00. These

absorbing solutions were later analysed colorimetrically for SO2 (West and Gaeke,

1956), NO2 (Merryman et al.,1973)andO3 (Byers and Saltzman, 1958; ISC, 1972).

For SO2, the values were calibrated with an automatic SO2 analyzer (Model 319,

Kimoto Japan). Ozone concentration was calibrated with ozone generator (Standard

Appliances Model SA 112- LP- 230c India). Six-hour average concentrations were

calculated for each site for the whole experimental period. The O3 burden was also

estimated by means of assessing leaf injury on a bioindicator species of tobacco(Nicotiana tabacum L. cv. Bel W3) over a 30 day period. Since the wet chemistry

methods were used for pollutant monitoring, interferences due to other pollutants

may not be completely ruled out.

2.4. TEST SPECIES

The plant species chosen for this study was mung bean (Vigna radiata L. (Wilczek)

cv. Malviya Jyoti, bred by the Institute of Agricultural Sciences, Banaras Hindu


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University, and Varanasi. This cultivar is widely used as a protein supplement in the

eastern part of India. Mung bean plants are known for their high sensitivity to SO2and NO2 in the laboratory (Varshney et al., 1997) and in field studies conducted

around point sources of pollution (Singh et al., 1990).

2.5. RAISING OF PLANTS

Five uniform seeds of moong bean were sown in 30 cm diameter earthen pots of

30 cm height filled with well manured garden soil (pH 7.2, organic carbon 1.2%,

total N 0.09%, available P 0.05%, exchangeable K 0.1%, cation exchange capacity

15.4 m equiv. 100 g1) and allowed to germinate. The soil was prepared by mixing

garden soil and farmyard manure in a 3:1 ratio, according to normal local agri-

cultural practice; diamine phosphate was added at a rate of 100 kg ha1 to the soil

before sowing. After germination, seeds were thinned to three per pot. Twelve days

after sowing, twenty pots were transferred to each site. The pots were uniformly

watered every day throughout the experiment in order to maintain constant soil

moisture. For biomass and yield determinations, two different sets of plants were

kept for harvesting on two occasions.

2.6. PLANT SAMPLING AND ANALYSIS

For biomass determination, plants were sampled destructively at 85 days after

sowing (DAS) and separated into root, shoot, leaf and pod components, before

being dried at 80 C to constant weight. Plants were finally harvested at maturity at

120 DAS and numbers of seeds pod1, weight of seeds pod1, no. of pods plant1,

weight of pods plants1, no. of seeds plant1 and weight of seeds plant1 were

measured.

Reproductive biomass carbon allocation was calculated as the ratio of total

vegetative biomass to total reproductive biomass on a dry weight basis (Fekete

et al., 1988), root:shoot ratio, leaf weight ratio and harvest index (Hunt, 1982).

Seed quality was analysed for selected metabolites (starch, total soluble sugars,

reducing sugars and protein). In order to extract sugars and starch, powdered seed

samples were boiled with 5 ml 80% ethanol and then centrifuged. The pellets were

then washed with distilled water and centrifuged again. The supernatant collectedafter each washing was used for estimating soluble sugars using the colorimetric

method of Dubois et al. (1956) and reducing sugar by the colorimetric copper

method of Somogyi-Nelson(Herbart etal., 1971).For starch extraction,pellets were

washed twice with 52% perchloric acid and centrifuged successively (McCready

et al.,1950). Finally the pellets were washed with distilled water and the supernatant

was used for starch determination by the phenol/H2SO4 colorimetric method of

Dubois et al. (1956). For protein estimation, the method of Lowry et al. (1951) was

followed.


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2.7. STATISTICAL ANALYSIS

Assumptions of normal distribution and homogenous variance were tested by the

Kolmogrov-Smirnov test and Cochrans C test, respectively prior to subjecting the

pot means to a one way analysis of variance test (ANOVA) using site as the factor

for biomass accumulation, yield measurements and seed quality parameters. Data

exhibiting non-Gaussian distribution were log transformed prior to ANOVA. For

determining significant differences between treatments, Duncans multiple range

test was used. The correlation coefficient and regression equations were determined

for individual pollutant concentrations and different growth and yield parameters

for sites where regular air monitoring was done. All statistical analyses were done

using SPSS/PC+ programme for microcomputers.

3. Results and Discussion

3.1. AIR POLLUTION MONITORING

The6 hr means concentrations of gaseous pollutants andtheir variations from March

to June during crop growth measured regularly at the four locations are shown in

Table II. The air quality data clearly indicate that spatial variations in SO 2 and NO2concentrations showed a similar pattern of distribution, the concentrations from

maximum to minimum being sites 8 > 4 > 1 > 3. Ozone, however, showed a

pattern of 8 > 1 > 4 > 3. On the basis of occasional monitoring at other sites, fourgroups of sites can be identified. Site 1 and 2 showing similar ranges of pollutants

formed group I, site 3 showing lowest pollutant levels formed group II, sites 4, 5,

6 and 7 at similar variations in pollutant concentrations formed group III and sites

8 and 9 showing highest pollution load formed group IV. Group IV comprising

sites 8 and 9 showing the highest pollutant load is situated downwind of a national

highway, small scale industries and intersections and hence is in the proximity

of numerous emission sources. The city plume from east to west may also have

TABLE II

Six hr mean pollutant concentrations (ppb) at selectedsites around Varanasi city

Sites SO2 NO2 O3

1. 13.3 (1116) 31.9 (2439) 55.7 (4666)

3. 8.04 (610) 11.7 (815) 9.73 (813)

4. 17.18 (1424) 31.9 (2737) 25.1 (1827)

8 32.2 (2440) 80.1 (6099) 58.5 (4973)

Minimum and maximum concentrations in parentheses.


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contributed to high ambient pollutant concentrations at these sites. Site 3, which

showed the minimum pollutant load, is characterised by residential and official

buildings, and hence low emission levels, and dense plantations of perennial tree

species, which may have provided a sink for pollutants. Pandey et al. (1992) have

also reported maximum concentrations of pollutants around the zone having 8 and

9 as sub sampling sites and minimum at site 3 in 1989. The average concentration

of SO2 recorded at site 8 in the present study (32.2 ppb) was slightly higher than

the average summer concentration of 27 ppb reported by Pandey et al. (1992) for

the same zone. In contrast, the NO2 average recorded during the present study

(80.1 ppb) was triple the concentration of 25 ppb reported by Pandey et al. (1992)

around sites 8 and 9. This trend might have occurred due to a switch to natural gas

from coal burning for home cooking and also due to an increase in vehicle numbersleading to more emissions of NOx . Concentrations of pollutants were intermediate

at group III, which includes sites 4, 5, 6 and 7.

The results indicated a different pattern of spatial variation for O 3 than SO2 and

NO2. Ozone showed comparable concentrations at group IV and I sites. Group I

sites 1 and 2 represent rural and periurban areas, respectively with no specific source

of pollution. The concentrations of O3 and NO2 showed different relationships in

rural and periurban areas. At group I sites (rural area) O3 concentration was higher

that NO2 due to no other specific source of NO2 in this area other than transport

of precursors leading to high O3 formation. In contrast at group III and IV sites

NO2 concentration was higher than O3 due to proximity of sources close to these

sites. Agrawal et al. (2003) also showed a similar pattern of O3 in different areas

of Varanasi city. Pandey et al. (1992) did not monitor any site close to 1, but

higher O3 levels were recorded from urban sites than suburban areas. Hassan et al.

(1995) have however, observed higher levels of ambient oxidant in a rural area

of Egypt compared with a nearby urban site in Alexandria. Aneja et al. (1992)

have observed a similar pattern in southeastern area of United States and Schenone

and Lorenzini (1992) in urban and rural areas of Italy. Pandey et al. (1992) and

Pandey and Agrawal (1994) have shown positive significant correlations between

temperature and O3 concentration which may be ascribed to higher oxidant levels

in summer. A similar result was reported by Nasralla and Shakour (1981) in Egypt.

Ozone levels recorded during the present study were higher than those reported

by Pandey et al. (1992) in 1989. For example O3 concentration at site 8 in the

present study was 58.5 ppb, whereas the earlier study reported a concentrationof 34 ppb in the zone including site 8. This may be ascribed to the increase in

traffic emissions of O3 precursors at present compared to the earlier study. Tobacco

biomonitoring also indicated highest O3 levels at sites 1, 2, 8 and 9, as white

flecks on the upper leaf surfaces were observed at these sites only. Other sites

did not show O3 symptoms on tobacco. Since all the pollutant concentrations are

lowest at site 3, the data for this site were used as the reference for comparing

the changes in plant parameters obtained at other sites in relation to pollutant

concentration.


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TABLE III

Biomass accumulation in different parts of mung bean plants kept at different sites around Varanasi

city at 85 days age (Mean of 10 replicates SE)

Site Root Shoot Leaf Pod Total

1 0.56 0.06ab 2.42 0.26abc 2.19 0.23b 6.40 0.39b 11.58 0.66bc

2 0.61 0.07ab 2.82 0.19ab 2.43 0.30b 7.42 0.47b 13.27 0.43b

3 0.71 0.10a 3.07 0.23a 3.17 0.40a 10.45 1.03a 17.40 1.35a

4 0.50 0.08ab 2.69 0.33ab 2.30 0.14b 4.68 0.47c 10.18 0.41cd

5 0.47 0.10b 2.21 0.21bc 2.08 0.22b 4.68 0.18c 9.44 0.52de

6 0.40 0.06bc 2.28 0.10bc 2.02 0.19bc 3.05 0.32de 7.76 0.25e

7 0.40 0.07bc 1.98 0.28cd 1.94 0.31bcd 3.70 0.46cd 8.01 1.01e

8 0.20 0.02c 1.37 0.18d 1.22 0.15d 2.53 0.16de 5.33 0.41f

9 0.21 0.02c 1.37 0.19d 1.30 0.12cd 1.95 0.15e 4.83 0.31f

Within each parameter, values not followed by the same letter are significantly different at p 0.05.

3.2. GROWTH AND YIELD

The foliage of the mung bean plants did not show any specific lesions at any of the

study sites. However, the biomass accumulation pattern (F = 33.44; p < 0.001)

varied significantly between sites (Table III). Maximum site-wise variations were

observed for pod biomass (F = 23.21; P < 0.001) followed by leaf (F = 5.70;

P < 0.001), then shoot (F = 6.93; P < 0.001) and root (F = 6.11; P < 0.001)

(Table III). Biomass accumulation in all plant parts showed a trend of maximum

to minimum as 3 > 2 > 1 > 4 > 5 > 6 > 7 > 8 > 9. The relationship between

the individual pollutants levels at sites 1,3,4 and 9 and total biomass accumulation

was found to be significantly negative, suggesting a negative impact of air quality

across the sites. The trend of total biomass accumulation at all sites clearly showed

that plants at pollutant group II had highest values and at group IV had lowest

biomass accumulation values (Table VIII). The impact of SO2 and NO2 appears

more important than O3, the latter having a lower correlation coefficient. Ashmore

et al. (1988) have also reported a decline in biomass accumulation in different

plant parts along a gradient of air pollution out of London. In this case a multiple

regression analysis also provided evidence that SO2 and NO2 levels of 20 and25 ppb, respectively were inversely related to the yield of Trifolium pratense and

Hordeum vulgare,respectively; however effects of O3 appeared to be less important.

Thus the present work is very much in accord with the results of Ashmore et al.,

(1988), which were obtained at somewhat lower concentrations of SO2 and NO2but under temperate conditions.

Growth indices further reflect the mechanism of biomass allocation under dif-

ferent levels of air pollutants. Root/shoot ratio (RSR) did not show significant vari-

ations due to sites. Leaf weight ratio (LWR) (F = 5.32; P < 0.001), vegetative


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TABLE IV

Final harvest leaf weight ratio (g g1), root:shoot ratio (g g1), reproductive to vegetative ratio (g g1)

and harvest index (g g1) of moong bean plants kept at different sites around Varanasi city (Mean of

10 replicates SE)

Site LWR RSR RVR HI

1 0.188 0.01b 0.053 0.007a 0.82 0.08de 0.97 0.09ab

2 0.183 0.02b 0.048 0.005a 0.83 0.1de 0.96 0.08abc

3 0.180 0.02b 0.045 0.007a 0.70 0.09e 1.12 0.017a

4 0.227 0.01ab 0.053 0.009a 1.30 0.20abc 0.68 0.08bcd

5 0.218 0.01ab 0.053 0.01a 1.02 0.08cde 0.74 0.08bcd

6 0.263 0.03a 0.056 0.01a 1.73 0.27a 0.51 0.06d

7 0.242 0.02ab 0.054 0.008a 1.23 0.14bcd 0.71 0.11bcd

8 0.228 0.02ab 0.041 0.004a 1.09 0.06cde 0.66 0.04cd

9 0.271 0.03a 0.046 0.004a 1.55 0.18ab 0.56 0.10d


reproductive ratio (F = 12.23; P < 0.001) and harvest index (F = 9.23;

P < 0.001), however, varied significantly among sites with differing concen-

trations of air pollutants (Table IV). Leaf weight ratio increased significantly at

sites of group III and IV receiving a higher pollution load as compared to refer-

ence site (Table IV). Higher LWR suggests partitioning of a large amount of fixed

carbon into leaf growth to enable the plants to overcome the adverse impact at the

place of impingement. Cooley and Manning (1987) have indicated that reduction

in total biomass due to air pollutants is often accompanied by a change in parti-

tioning of photosynthate in different plant components. No significant change in

RSR of plants suggests that pollutants do not alter the partitioning pattern between

below and above ground parts. This, however, is contradictory to some reports in

the literature (Cooley and Manning, 1987; Kasana and Mansfield, 1986). Since the

experiment was conducted on pot grown plants, such a response may be attributed

to limited space for root growth. The vegetative/reproductive biomass ratio was

increased significantly at all sites compared to the reference site which further sug-

gests that the photosynthate produced is utilized more for maintaining vegetative

parts than for allocation to yield components (Cooley and Manning, 1987).

At the time of final harvest, numbers of seeds pod1, pods plant1 and seedsplant1 and weight of seeds pods1, pods plant1 and seeds plant1 showed a trend

of maximum to minimum 3 > 2 > 1 > 4 > 5 > 7 > 6 > 8 = 9 (Table V).

Analysis of variance test further showed that numbers of seed pod 1 (F = 17.10;

P < 0.001), pod plant1 (F = 27.04; P < 0.001) and seed plant1 (F = 33.44;

P < 0.001) and weight of seeds pod1 (F = 12.80; P < 0.001), pods plants1

(F = 32.21; P < 0.001) and seeds plants1 (F = 31.02; P < 0.001) varied

significantly between the sites. As compared to plants at reference site 3, weight

of seeds plant1 (yield) was lowered by 18, 22, 34, 50, 53, 59, 66, 74 and 79% at


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TABLEV

Differentyieldpara

metersofmoongbeanplantskeptatdifferentsitesaroundVaranasicityatthetimeoffinalharvest(Meanof10

replicates

SE)

Wt.ofone

No.ofseeds

Wt.ofseeds

No.ofpods

Wt.ofpods

No.

ofseeds

Wt.ofseeds

Sites

pod(g)

perpod

perpod(g)

perplant

perplant(g)

per

plant

perplant(g)

1.

0.2

8

0.004c

5.6

0

0.1

6c

0.1

83

0.0

06b

23.1

3

1.4

1a

6.4

0

0.3

9b

130.3

7

10.7

7b

4.2

0

0.1

9b

2.

0.3

7

0.02a

6.2

5

0.3

6abc

0.2

5

0.0

1a

19.7

5

0.7

3b

7.4

2

0.4

7b

123.4

0

7.7

2bc

4.9

6

0.3

2b

3.

0.4

0

0.02a

7.0

8

0.3

0a

0.2

5

0.0

1a

25.7

5

1.7

8a

10.4

5

1.0

3a

181.3

3

13.8

6a

6.4

0

0.5

9a

4.

0.2

4

0.02cd

4.7

3

0.2

8d

0.1

7

0.0

1bc

19.1

3

0.8

8b

4.6

8

0.4

7c

90.1

8

6.4

9de

3.2

0

0.2

7c

5.

0.2

8

0.01c

5.9

3

0.2

2bc

0.1

8

0.0

1bc

17.2

5

1.0

8b

4.6

8

0.1

8c

101.6

5

6.2

3cd

3.0

0

0.1

7cd

6.

0.2

4

0.01cd

4.2

3

0.3

4d

0.1

7

0.0

1bc

12.5

0

0.8

5cd

3.0

5

0.3

2de

53.1

0

5.7

5f

2.1

5

0.2

2de

7.

0.3

3

0.01b

6.7

0

0.1

5ab

0.2

3

0.0

1a

11.3

8

1.3

8cd

3.7

0

0.4

6cd

76.0

2

9.0

8e

2.6

0

0.3

3cd

8.

0.2

3

0.01d

4.0

3

0.1

7d

0.1

5

0.0

05c

11.3

8

0.9

4cd

2.5

3

016de

45.2

8

3.3

0f

1.6

3

0.1

3e

9.

0.2

2

0.02d

4.2

5

0.3

9d

0.1

5

0.0

2bc

9.0

0

0.4

2d

1.9

5

0.1

5e

37.9

3

3.1

9f

1.3

4

0.1

4e

Withineachparameter,valuesnotfollowedbythesameletteraresignificantlydifferentatp

0.

05.


12/16


TABLE VI

Site wise changes in selected metabolite contents (mg g1) of seeds of mung bean plants kept at

different sites around Varanasi city (Mean of 10 replicates SE)

Site Total sugar Red. Sugar Starch Protein

1 29.78 0.16bc 3.26 0.11de 332.35 3.15b 321.00 3.79b

2 27.65 0.09e 3.08 0.09ef 292.60 3.31c 322.33 3.38b

3 29.51 0.24c 3.94 0.07ab 354.71 3.40a 357.67 8.64a

4 30.40 0.15ab 3.57 0.07bcd 271.57 3.63d 311.00 6.08b

5 30.98 0.21a 3.68 0.09bc 270.23 3.40d 366.67 3.71a

6 26.79 0.30f 2.82 0.16f 253.03 3.99e 362.00 5.69a

7 28.64 0.25d 4.17 0.16a 270.233.99d 367.33 4.41a

8 28.16 0.25de

3.86 0.14ab

173.725.20g

317.67 4.67b

9 22.92 0.29g 3.31 0.17cde 223.223.64f 364.67 4.33a


TABLE VII

Correlation coefficients and linear regression between selected parameters of mung bean

plants and mean pollutant concentrations

Correlation between Correlation coefficient Regression Equation

SO2 vs. Biomass 0.847 Y= 19.123 0.452x

NO2 vs. Biomass 0.839 Y= 17.302 0.160x

O3 vs. Biomass 0.697 Y= 17.177 0.162x

SO2 vs. Yield 0.824

Y= 7.026 0.179xNO2 vs. Yield 0.805

Y= 6.271 0.062x

O3 vs. Yield 0.639 Y= 6.117 0.060x

SO2 vs. Starch 0.984 Y= 418.95 7.685x

NO2 vs. Starch 0.952 Y= 385.812 2.652x

O3 vs. Starch 0.560NS Y= 354.306 1.910x

SO2 vs. Protein 0.548NS Y= 348.443 1.222x

NO2 vs. Protein 0.522NS Y= 342.94 0.416x

O3 vs. Protein 0.579 Y= 347.86 0.564x

SO2vs. Reducing Sugar 0.187NS Y= 3.548 + 0.006x

NO2 vs. Reducing Sugar 0.144NS Y= 3.592 + 0.002x

O3 vs. Reducing Sugar 0.389NS Y= 3.873 0.006x

SO2 vs. Total Sugar 0.680 Y= 30.626 0.066x

NO2 vs. Total Sugar 0.731 Y= 30.440 0.025x

O3 vs. Total Sugar 0.483NS Y= 30.223 0020x

p < 0.01;p < 0.05 and N S not significant.

sites 2, 3, 4, 5, 7, 6, 8 and 9, respectively. The relationship between the individual

pollutants levels at sites 1, 3, 4 and 9 and yield was found to be significantly negative

(Table VII). The variation in weight of seeds directly corresponded to the pollutant

concentrations in different pollution groups (Table VIII). Pollution group II having


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TABLE VIII

Comparison of selected parameters (mean values) of mung bean plantskept at different groups

of pollutant concentrations around Varanasi

Pollution Group

Parameters I II III IV

Total Biomass (g plant1) 11.5813.27 17.40 7.7610.18 4.835.83

Weight of seeds (g plant1) 4.204.96 6.40 2.153.20 1.342.53

Weight of pods (g plant1) 6.407.42 10.45 3.054.68 1.952.53

Protein content (mg g1) 321.00322.33 357.67 311.00367.33 317.67364.67

Starch content (mg g1) 292.60332.35 354.71 253.03270.23 173.72223.22

lowest concentrations of pollutant showed maximum value for weight of seeds

(6.40 g plant1) followed by group I sites having higher pollutant concentrations

than group II site. Minimum value for weight of seeds plant1 wasobserved at group

IV sites (1.341.63 g plant1) having highest pollutant concentrations. Weight of

pods also showed a similar trend (Table VIII).

The reductions in weight of seeds plant1 were attributed to reductions in

numbers of seed pod1, no of pods plant1 and no of seeds plant1 and also in

their respective weights. Ozone, SO2 and NO2 individually and in combination are

known to reduce the yield of many crop plants (e.g. Renaud et al., 1997; Heggestad

and Lesser, 1990). Upon comparison of the coefficient values of linear correlation

matrics, it is evident that SO2 and NO2 have greater impact on yield compared toO3 (Table VII).

The harvest index (HI) showed a significantly higher value at site 3 as compared

to other sites. The reduction in HI further suggests that photosynthate allocation to

pods is minimised during pollution stress and the photoassimilate is utilised more

for repair and maintenance of assimilatory surfaces. Such a strategy makes the

plants most vulnerable during the pod filling stage. Post anthesis O3 exposure had

maximum impact on grain yield of wheat (Pleijel et al., 1998).

3.3. SEED QUALITY

Seed quality also showed significant variations between sites with respect to Starch(F = 202.67; P < 0.001), total sugar (F = 115.40; P < 0.001), reducing sugar

(F = 12.47; P < 0.001) and protein (F = 22.03; P < 0.001) contents (Table VI).

The carbohydrate pool in seeds showed the highest starch content at site 3, while

reducing sugar content was highest at site 7 and soluble sugar at site 4 (Table VI).

Starch content was highest at pollution group II site, followed by group I sites, group

III sites and minimum was observed at group IV sites (Table VIII). Protein content,

however, did not show a similar trend. Protein content at sites 3, 5, 6, 7 and 9 were

significantly higher than contents at sites 1, 2, 4 and 8 suggesting no definite trend


14/16


of protein content in seeds in response to ambient air pollutants (Table VII). One

trend is however, clear that the sites having high concentration of O3 had lower seed

protein. There was no significant relationship between atmospheric NO2 orSO2 and

foliar protein in the present study, although there was an indication of an O 3 effect.

Starch content of seeds showed a significant negative correlation with both ambient

SO2 and NO2 concentration (Table VII). Reducing sugar showed no relationship

with pollutant concentrations but total sugar was significantly negatively correlated

with both SO2 and NO2. Possibly, reduced photosynthetic efficiency of plants at the

more polluted sites has reduced accumulation and allocation of photosynthates to

their seeds. Agrawal et al. (1983) have also reported significant reduction in starch

content of grains ofPanicum miliaceum plants exposed to O3 and SO2 individually

and in combination. Total soluble and reducing sugars did not show a specific trendin relation to ambient air pollutant concentrations. Starch content in seeds, however,

was found to be directly correlated with total sugar.

4. Conclusion

Reductions in biomass accumulation and yield at sites having high levels of SO2,

NO2 and O3 clearly depict a marked negative influence of air quality on mung bean

plantsgrown at different sites in periurbanfringes of Varanasi city. It shouldbe borne

in mind that this study wasundertaken over the summergrowingseason when slower

rates of metabolism, as a result of the extremely hostile environmental conditions,

may have predisposed plants to susceptibility to pollutants. The experimental designdid not permit clear elucidation of the relative contribution by the individual gases,

although it is clear that O3 forms an important component of the airshed in the more

rural sites with no specific source of the primary pollutants NO2 and SO2.

The present study clearly demonstrated that air pollution could be a major con-

straint on peri-urban crop yield and its nutritional quality in India. Research to

establish exposure response relationships for a range of important crops, using

long term chamber filtration experiments under local field conditions, is urgently

required. These studies could lead to recommendations for changes in agricultural

practices to ameliorate the impacts of air pollution. Concern over air pollution

today is largely based on direct impacts to human health. However, in view of

need to maintain yields and address malnutrition in the developing world, there

is a strong case for raising the policy profile of the indirect health impacts of air

pollution through reduced crop yield and nutritional quality. These factors should

be considered when assessing the true benefit of pollution abatement strategies.

Acknowledgements

This publication is an output from a research project (R6992 Environment Re-

search Programme) funded by the United Kingdom Department for International


15/16


Development (DFID) for the benefit of developing countries led by Dr F Marshall.

The views expressed are not necessarily those of DFID. The authors gratefully

acknowledge the financial support of DFID. The authors would like also to thank

Mr. Raj Kumar Singh and Ms Madhu Rajput for their help in experimental work.

We would also like to thank the Head, Department of Botany, Banaras Hindu Uni-

versity for providing permission for this research programme and colleagues in the

Environmental Modelling, Monitoring and Assessment group of the Department

of Environmental Sciences and Engineering at Imperial College for their helpful

inputs.

References

Agrawal, M., Nandi, P. K. and Rao, D. N.: 1983, Ozone and Sulphur Dioxide effects on Panicum

miliaceum Plant, Bull. Torrey Bot. Club. 110, 435441.

Agarwal, A., Narain, S. and Srabani, S.: 1999, State of Indias Environment. The Citizens Fifth

Report Part I National Overviews, Centre for Science and Environment, New Delhi.

Agrawal, M., Singh, B., Rajput, M., Marshall, F., Bell, J. N. B.: 2003, Effects of air pollution on

periurban agriculture: a case study, Environ Pollut 126, 323329.

Aneja, V. P., Yoder, G. T. and Pal Arya, S.: 1992, O 3 in the urban Southeastern United States,

Environ. Pollut. 75, 3944.

Ashmore, M. R., Bell, J. N. B. and Mimmack, A: 1988, Crop growth along a gradient of ambient air

pollution, Environ. Pollut. 53, 99121.

Byers, H. D. and Saltzman, B. E: 1958. Determination of Ozone in Air by Neutral and Alkaline

Iodine Procedure, J. Am. Ind. Hyg. Ass. 19, 251257.Cooley, D. R. and Manning, W. J.: 1987, The Impact of Ozone on Assimilate Partitioning in Plants:

a Review, Environ. Pollut. 47, 95113.

Dubois, M., Gilles, K. A., Hamilton, J. K., Roberts P. A. and Smith F.: 1956. Colorimetric Method

for Determination of Sugars and Related Substances, Analyt. Chem. 28, 350356.

Fekete, G., Tuba, Z. and Melko, E.: 1988, Background processes at the population level during

succession in grasslands on sand, Vegetatio 77, 3341.

Hassan, I. A., Ashmore, M. R. and Bell J. N. B.: 1995, Effect of Ozone on Radish and Turnip under

Egyptian Field Conditions, Environ. Pollut. 89, 107114.

Heck, W. W., Taylor, O. C. and Tingey, D. T.: (Eds) 1988. Assessment of Crop Loss from Air

Pollutants, Elsevier, London.

Heggestad, H. E. and Lesser, V. M.: 1990, Effects of Ozone, Sulphur Dioxide, soil water deficit and

cultivar on yields of soybean, J. Environ. Qual. 19, 488495.

Herbart, D., Phillipps, P. J. and Strange, R. E.: 1971, in J.R. Norries, and D. W. Robbins (eds.),

Methods in Microbiology Vol XB, Academic Press, London, pp. 209344.

Hunt, R.: 1982, Growth Curves, Edward Arnold, London.

ISC.:1972, Methods of Air Sampling and Analysis. American PublicHealth Association, Washington

DC.

Jager, H. J., Unsworth, M., Temmerman, L. and Mathy, P.: 1994, Effects of Air Pollution on Agri-

cultural Crops in Europe, Air Pollution Report 46. CEC, Brussels.

Kasana, M. S. and Mansfield, T. A.: 1986. Effects of Air Pollutants on the Growth and Functioning

of Root. Proc. Indian Acad. Sci. (Plant Sci.) 96, 429441.

Khemani, L. T., Momin, G. A., Rao, P. S. P., Vijay Kumar, R. andSafai, P. D.: 1995, Study of Surface

Ozone Behaviour at Urban and Forested Sites in India, Atmos. Environ. 29 (16), 20212024.


16/16


Kobayashi, K., Okada, M., Nouchi, I.: 1995, Effects of ozone on dry matter partitioning and yield

of Japanese cultivars of rice (oryza sativa L.), Agri. Ecosys. Environ. 53: 109122.

Lowry, O. H., Rosenbrough Farr, A. L. and Randall, R. J.: 1951. Protein measurement with Folin-

phenol Reagent, J. Biol. Chem. 193, 265275.

Maggs, R., Wahid, A., Shasmi, S. R. A. and Ashmore, M. R.: 1995, Effects of Ambient Air Pollution

on Wheat and Rice Yield in Pakistan, Water Air Soil and Pollut. 85, 13111316.

McCready, R. M., Goggolz, J., Silviera, V. and Owens, H. S.: 1950, Determination of Starch and

Amylase in Vegetables, Analyt. Chem. 22, 11561158.

Merryman, E. L., Spicer, C. W. and Levy, A.: 1973, Evaluation of Arsenite Modified Jacobs

Hochheiser Procedure, Envir. Sci. Technol. 7, 10561059.

Nasralla, M. M. and Shakour, A. A.: 1981, NOx and Photochemical Oxidants in Cairo City Atmo-

sphere, Environ. Int. 5, 5566.

Pandey, J.,Agrawal,M., Khanam,N., Narayan, D. and Rao, D. N.:1992. AirPollutant Concentrations

in Varanasi, India, Atmos. Environ. 26B, 9198.Pandey, J. and Agrawal, M.:1994. Evaluation of air pollution phytotoxicity in a seasonally drytropical

urban environment using three woody perennials, New Phytol. 126, 5361.

Renaud, J. P., Allard, G. and Mauffette, Y.: 1997, Effects of ozone on yield growth and root starch

concentrations of two alfalfa (Medicago sativa L.) cultivars, Environ. Pollut. 95, 273281.

Sanders, G. E., Colls, J. J., Clark, A. G., Galaup, S., Bente, J. and Cantuel, J.: 1992, Phaseolus

vulgaris, and ozone: results from open top chamber experiments in France and England, Agri.

Ecosys Environ. 38: 3140.

Schenone, G. and Lorenzini, G.: 1992, Effects of Regional Air Pollution on Crops in Italy, 38, 519.

Singh, J. S., Singh, K. P. and Agrawal, M. (eds.): 1990. Environmental Degradation of the Obra-

Renukoot-Singrauli Area in India and its Impact on Natural and Derived Ecosystems. Final Tech-

nical Report submitted to Ministry of Environment and Forest Government of India (14/167/84

MAB EN-21 RE).

Singh, A., Sarin, S. M., Shanmugan, D., Sharma, N., Attri, A. K. and Jain, W. K.: 1997, Ozone

Distribution in the Urban Environment of Delhi during Winter Months. Atmos. Environ. 31,

34213427.

Tonneijck, A. E. G. and Van Dijk, C. J.: 1998, Responses of bean (Phaseolus vulgaris L CV Pros) to

chronic ozone exposure at two levels of atmospheric ammonia Environ. Pollut. 99: 4551

UNDP.: 1996, Urban Agriculture: Food, Jobs and Sustainable Cities. United Nations Development

Programme, New York.

Varshney, C. K.,Agrawal,M., Ahmad,K. J.,Dubey, P. S. andRaza,S. H.:1997,Effectof AirPollution

on Indian Crop Plants, Project report submitted to UK Overseas Development Administration,

pp. 200.

Wahid, A., Maggs, R., Shasmi, S. R. A., Bell, J. N. B. and Ashmore, M. R.: 1995, Air Pollution and

its Impacts on Wheat Yield in the Pakistan Punjab, Environ. Pollut. 88, 147154.

West, P. W. and Gaeke, G. C.: 1956, Fixation of SO 2 as Sulfitomercurate (II) and Subsequent Col-

orimetric Estimation. Analyt. Chem. 28, 18161819.

Zheng, Y., Steveuson, K. J., Barroweliffe, R., Chen, S., Wang, H., and Barnes, J. J.: 1998, Ozonelevels in Chongqing: a potential threat to crop plants commonly grown in the region? Environ

Pollut. 99: 299308.

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The Effect of Air Pollution