Roadside plants as bio indicators of air pollution in an ... · PDF fileTitle-Roadside plants...

International Journal of Advancements in Research & Technology, Volume 4, Issue 1, January -2015 14 ISSN 2278-7763

Copyright © 2015 SciResPub. IJOART

Roadside plants as bio indicators of air pollution in an industrial region, Rourkela,

India.

Prabhat Kumar Rai*, Lalita L.S. Panda

*Corresponding Author (Prabhat Kumar Rai), Department of Environmental Science,

Mizoram University

Tanhril, Aizawl-796004, Mizoram

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Title-Roadside plants as bio indicators of air pollution in an industrial region, Rourkela,

India.

Abstract

Foliar surface undergoes several structural and functional changes when particulate-laden air

strikes it. An attempt was made to evaluate the quality of air in terms of respirable suspended

particulate matter (RSPM), suspended particulate matter (SPM), sulphur dioxide (SO2) and

nitrogen dioxide (NO2) along with biochemical parameters of twelve selected roadside plant

species at industrial, traffic, residential and rural areas of Rourkela city in India. Increase

concentration of heavy metals (Fe, Cu and Zn) was recorded at site B (industrial area).

Considerable reduction in chlorophyll, sugar and protein contents were observed at sites

receiving higher pollution load. The variation in heavy metal concentration and enzyme

activity (Catalase, Peroxidase) were found to be pollution load dependent, suggesting the

activation of protective mechanism in these plants under air pollution stress. A significant

negative correlation was found between ambient air quality and biochemical parameters

except for ascorbic acid which exhibited significant positive correlation with pollution load.

Keywords: Air quality, heavy metals, sugar, protein, enzyme activity

Introduction

Increasing industrialization and anthropogenic activities is the main agent of pollutant

discharge into the environment and introduce various harmful substances into the

atmosphere. Many industrial plants and heavy traffic may produce heavy metals and other

toxic compounds into the atmosphere that may cause adverse health effects in human or

animals; affect plant life and impact the global environment by changing the atmosphere of

the earth (Ghorbanli et al. 2007; Raabe 1999; Bakand et al. 2005; Hayes et al. 2007). There is

no mechanical or chemical device, which can completely check the emission of pollutants at

the source. Once the pollutants are released to the atmosphere, only the plants are the hope,

which can mop up the pollutants by adsorbing and metabolizing them from the atmosphere.

Therefore, the plants, role in the air pollution abatement have been increasingly recognized in

recent years. Plants act as a sink or even as living filters to minimize air pollutant by

developing characteristic response and symptoms. Moreover, roadside plant leaves are in

direct contact with air pollutant, and may act as stressors for these pollutants, hence to be

examined for their Biomonitoring potential (Pandey et al. 2005; Sharma et al. 2007). The use

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of higher plants especially different parts of trees, for air monitoring purpose is becoming

more and more widespread. A number of air pollution Biomonitoring studies have been

performed using leaves of different plant species. Deposited materials on the leaves have

some effect on the overall biochemical and physiological aspects of plants such as

chlorophyll, stomata, ascorbic acid, relative water content, pH, enzymes etc and reduce the

plants development. Several investigation have been performed on the physiological and

biochemical response of plants growing in an industrial region (Joshi et al. 2009; Gupta et al.

2009; Sharma and Tripathi 2009; Gupta et al. 2012). By analyzing these parameters, an early

diagnosis of the extent of pollution can be done and air quality can also be assessed. The

changed ambient environment due to the air pollutants in industrial area of Rourkela has

exerted a profound influence on the morphological, biochemical and physiological status of

plants, and its responses. The objective of the present investigation is first ly to estimate and

analyze air quality of Rourkela and classify it according to the Air Pollution Index. Secondly

to study the foliar traits based on biochemical and enzymatic responses of some common

roadside plant species growing in the selected study sites.

Material and methods

Study area and site characteristics

sea level. The climate of Rourkela is characterized as tropical monsoon climate, with

minimum temperature in December and maximum in May. Rourkela city is famous for its

steel industries under Steel Authority of India Ltd. (SAIL) and is known as steel city. A

number of other industries are also present such as cement factory, fertilizer, sponge iron

industries and thermal power plants therefore Rourkela became a significant and long term

point source of pollutants causing air pollution. The entire area under the study has been

divided into four sites in order to assess the status of air pollution on the biochemical and

physiological parameters of plant growth along with morphological changes. A detailed

description of the selected sites is described below (Figure1)

Site-A: Station road is an old and densely populated area of the city with high traffic. It is

also a commercial area.

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Site-B: Plant side road, an industrial area. This area comprises of the Steel Authority of India

Limited (SAIL) and experience heavy load of traffic.

Site-C: Sector area is a planned residential area with medium traffic. It is a semi urban area

with religious places, recreational areas etc.

Site-D: Hamirpur area is a rural area, mainly agricultural fields, few educational institutes

and few colonies. It experiences less traffic load.

Ambient air quality monitoring

Ambient air quality for SPM, RSPM, SO2 and NO2 were done twice in a month of winter

season, 2011 and 2012. The representative months considered were November, December,

January and February. High Volume Air Sampler (Envirotech model, APM-460NL) with

gaseous attachment (Envirotech model, APM-411TE) was used to monitor the air quality.

RSPM were trapped by glass fibre filter papers and SPM were collected in the separate

containers at average air flow rate of 1.5 m3/min. The sampler was run for 24 hour on eight

hourly basis and triplicate samples were collected at each time. West and Gaeke method

(1956) and Sodium Arsenite method (Margeson, 1977) were used for the analysis of SO2 and

NOx respectively. Using air pollutants data the air pollution index (API) was calculated by

modifying the following equation (Rao and Rao, 1989).

API = 1/3(SO2/Sso2 + NOX/SNOX + SPM/SSPM) × 100

Where SSPM, SSO2 and SNOx represent the ambient air quality standards for SPM, SO2 and

NOx.

Plant sampling and biochemical parameters assessed

Twelve plant species namely Ficus bengalensis, Ficus religiosa, Mangifera indica,

Bougainvillea spectabilis, Psidium guajava, Hibiscus rosasinensis, Lantana camara, Delonix

regia, Artocarpus heterophyllus, Cassia auriculata, Bauhinia variegate and Lagerstroemia

speciosa were selected for this study, as they were common along roadside. Three samples

from healthy and mature leaves of each plant were plucked through random selection in early

hours of morning and brought in polythene bags, kept in ice box to the laboratory and

enzyme activity w y. T − 0 C

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freeze till analysed for various morphological and biochemical parameters within twenty four

hour of their harvesting.

The leaf samples were analyzed for total chlorophyll (Arnon, 1949) , ascorbic acid (Keller

and Schwager, 1977), protein content (Lowery et al, 1951), Total soluble sugar content ,

using the anthrone method described by Irigoyen et al (1992). Heavy metals in the plant

foliage were analyzed by using an Atomic absorption spectrophotometer (model 370A,

PERKIN ELMER).

For determination of antioxidant enzyme activities, enzyme extraction procedure was

prepared according to Nayyar and Gupta (2006) with some modification. Catalase activity

was determined according to Aebi (1984) by monitoring the decomposition of H2O2. In 1ml

of reaction mixture contain potassium phosphate buffer (pH 7.0), 50µl of enzyme extract and

10 mM H2O2 to initiate the reaction. The reaction was measured at 240 nm for 5min and

H2O2 consumption was calculated using extinction coefficient, 43.6 M-1

cm-1

.

Peroxidase activity was determined using the guaicol oxidation method by Chance and

Machly (1955). The 3 ml reaction mixture contains 10 mM potassium phosphate buffer (pH

7.0), 8 mM guaicol and 50 µl enzyme extract. The reaction was initiated by adding 10 mM

H2O2. The increase in absorbance was recorded within 5 min at 470 nm due to the formation

of tetraguaicol. A unit of peroxidase activity was expressed as the change in absorbance per

min and specific activity as enzymes units per mg soluble protein (extinction coefficient 6.39

mM-1

cm-1

).

All statistical calculation was performed using Statistical Programme for Social Science

(SPSS Version 11.2). The observations were replicated thrice for each parameter, mean

values were pooled and standard error (S.E) was calculated. The correlation coefficients were

also determined between air pollutant concentrations and selected plant parameters.

Result and discussion

Air pollutant concentration

Ambient air quality monitoring at different sites of Rourkela city indicated that Site B

(industrial area) was highly charged with pollutants emission from steel plant (SAIL) and

automobile exhaust (SPM, 540.09 µg m-3

, RSPM, 220.12 µg m-3

, NO2, 23.62 µg m-3

, SO2,

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21.65µg m-3

), followed by Site A (traffic area) (SPM, 538.32 µg m-3

, RSPM, 190.08 µg m-3

,

NO2, 20.41 µg m-3

, SO2, 17.65µg m-3

) in the ascending order, while Site C (residential area)

(SPM, 410.28 µg m-3

, RSPM, 165.92 µg m-3

, NO2, 18.88 µg m-3

, SO2, 11.77µg m-3

) and Site

D (rural area) (SPM, 370.43 µg m-3

, RSPM, 128.74 µg m-3

, NO2, 11.98 µg m-3

, SO2, 9.89µg

m-3

) showed minimum level of air pollutants when compared to other two sites. Air quality

index for the selected sites in Rourkela city is shown in Table 1. On the basis of air pollution

index, site B was categorized as heavy air pollution site with air pollution index 79.50 , site

A and site C as moderately air pollution site with air pollution index 59.00 and 72.75

respectively and site D as light air pollution site with air pollution index 48.50 (Table1and 2)

. The values of all the four air pollutants were lowest at site D because it is a rural area with

less number of vehicles and highest at site B as it is an industrial area with some commercial

complexes and ample no of heavy vehicle passes throughout the day due to the presence of

Steel Authority of India Limited (SAIL).

Biochemical characteristics

The vegetation of Rourkela city is exposed to dust pollution, chronic concentration of

gaseous pollutants and heavy metals. Plants on exposure to dust, gaseous pollutant and heavy

metal may undergo several biochemical and physiological changes. Heavy metal

concentrations in the leaves of studied sites are shown in figure 2 (A, B and C).Heavy metal

concentration were ranked in the order of Zinc >Iron > Copper in the studied species. The

average value of Fe and Zn at different sites has been found to be in large amount. A

maximum value of Fe (37.34±2.40mg kg) was observed at Site B, followed by Site A

(33.07±1.98mg kg), Site C (29.04±1.20mg kg) and minimum (24.38±3.10mg kg) at site D.

The concentration of Zn and Cu were observed as 51.07±3.77mg kg, 23.14±2.11mg kg at the

site A and 53.27±3.72mg kg, 26.32±2.62 mg kg at site B and 50.97±3.48mg kg,

21.93±2.51mg kg at site C and 47.73±3.43mg kg, 20.31±2.43mg kg at site D respectively,

while at the low polluted site, Fe, Cu and Zn showed their concentration as low as

15.85±1.24mg kg, 4.39±0.14mg kg and 12.54±0.62mg kg respectively. Among the examined

plant species, Ficus bengalensis and Psidium guajava showed the highest heavy metal

concentration while the lowest were observed in Cassia auriculata and Bauhinia variegate.

The elevated emission of heavy metals concentration in our study sites can be attributed to

industrial emission and a greater density of heavy vehicles. However, heavy metal

accumulation in plants did not follow any particular pattern, which might be due to their

inherent metal accumulation capacity, Variation in growth rate and stage of maturity (Gupta

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et al. 2012; Pandey et al. 2009; Sharma et al. 2008). In site B, metal content were higher than

other sites. Average metal concentrations in site D were always the lowest among the four.

The maximum concentration of Fe, Zn and Cu in the airborne dust particulates of site B

might be due to the presence of Steel Authority of India Limited (SAIL) and heavy traffic

density. However, an excess of these heavy metal may cause oxidative stress either by

inducing the generation of reactive oxygen species (ROS) within sub cellular compartments

or by decreasing enzymatic and non-enzymatic antioxidants due to an affinity with sulphur

containing groups (-SH) (Benavides et al. 2005) and disturbances in their supply can cause

significant modifications of biochemical processes in plants, leading to lower productivity.

Overall the occurrence of metal concentration was found in the order Site B > Site A > Site C

> Site D. Table 3 reflects the values of total chlorophyll content in the foliar tissues of the

selected roadside plants at selected sites. It was noticed that chlorophyll content decreased

with increasing pollution load with maximum reduction at site B and site A that harbours

industrial set up and highest vehicular density. The highest total chlorophyll content

(2.10±0.04) was recorded in Hibiscus rosasinensis at Site D and the lowest (0.30±0.03) in

Ficus religiosa at Site B. Chlorophyll is said to be an index of productivity and it plays an

important role in plant metabolism, hence any alteration in chlorophyll concentration may

change the morphological, physiological and biochemical behaviour of the plant. It is well

evident that chlorophyll content of plant varies from species to species; age of leaf and also

with the pollution level as well as with other biotic and abiotic conditions (Katiyar and Dubey

2001). The chlorophyll content in all the plants varies with the pollution status of the area i.e.

higher the levels of SPM and RSPM lower the chlorophyll content. The reduction in

chlorophyll concentration in the polluted leaves could be due to chloroplast damage (Pandey

et al. 1991), inhibition of chlorophyll biosynthesis (Esmat 1993) or enhanced chlorophyll

degradation due to the interference of foliar heavy metal deposition.

The concentration of ascorbic acid at Site B ranges between 0.27±0.04 to 1.03±0.03 and at

Site A it ranges between 0.23±0.03 to 0.77±0.03 with Bougainvillea spectabilis and

Artocarpus heterophyllus recording the lowest and highest value (Table 4). These are higher

than the ascorbic acid content found in Sites C and D. The ascorbic acid concentration for

Site C and D are in range (at Site C) 0.22±0.02 to 0.66±0.03 and (at Site D) 0.15±0.03 to

0.43±0.03. Ascorbic acid is a natural antioxidant and a strong reducing agent. It plays an

important role in pollution tolerance and protects the plant against oxidative damage by

maintaining the stability of cell membrane during pollution stress and scavenges cytotoxic

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free radicals. Present study showed elevation in the concentration of ascorbic acid at Site B in

all the selected plant species. Pollution load dependent increase in ascorbic acid content of all

the plant species may correspond with oxidative stress due to greater accumulation of

particulate heavy metals or increased rate of production of reactive oxygen species (ROS)

during photo-oxidation process.

The concentrations of total sugar content were markedly decreased with increasing pollution

load at Site B (heavy pollution site) for all the plant species when compared with other three

sites and the maximum reduction was seen in Mangifera indica (1.20±0.04 to 0.38±0.02

mg/g) and Delonix regia (1.02±0.05 to 0.28±0.06 mg/g) (Table 5).Soluble sugar is an

important constituent and source of energy for all living beings. Plants manufacture this

organic substance during photosynthesis and breakdown during respiration (Seyyednejad et

al. 2011; Tripathi and Gautam 2007). Reduction in soluble sugar content in polluted site may

correspond with a lower photosynthetic rate and higher energy requirements due to airborne

heavy metal stress. Pollutants like SO2, NO2 and H2S under hardening condition can cause

more depletion of soluble sugar in the leaves of plant grown in polluted area (Davison and

Barnes 1986).

The present investigation revealed significant reduction in case of total protein content for all

the selected plant species at Site B and Site A, with increase pollution load compared to other

two sites i.e. Site C and Site D (Table 6). Maximum reduction was observed in Ficus

religiosa from (0.92±0.04 to 0.21±0.03 mg/g) and Bougainvillea spectabilis (1.33±0.06 to

0.57±0.04 mg/g). Reduction in protein content of plants at Site A and B may be due to the

enhanced rate of protein denaturation and break down of existing protein to amino acid or

reduced denovo synthesis of protein which is also supported by the findings of

Constantinidou and Koztowski (1979), Prasad and Inamdar (1990), Iqbal (2000), Tripathi and

Gautam (2007), Saha and Padhy (2011). Presence of heavy metals would also interfere with

sulphur containing amino acid and crude protein resulting in decreased protein content

(Somasundaram et al. 1994). Decline in total protein content due to SO2 and NO2 pollution

has also been reported by several workers. Agarwal and Deepak (2003) determined that SO2

enrichment results in diminish leaf protein levels by 13% and the decrease is attributed by

breakdown of existing protein and reduction in synthesis.

Figure 3 and 4 summarised the Catalase and Peroxidase enzyme activities in the leaf samples

of all the sampling sites. The average activity of Catalase and Peroxidase enzymes were

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increased in all the plant species at Site B and A (heavy pollution site) compared to Site D

and C (Light and medium air pollution site). Cassia auriculata (34.40±0.12 U/mg protein)

showed highest Catalase concentration and Delonix regia (7.34±0.08 U/mg protein) showed

lowest Catalase concentration. Highest Peroxidase concentration was recorded in Delonix

regia (0.22±0.09U/mg protein) and lowest in Psidium guajava (0.01±0.01U/mg protein). In

plant cells, electron may be transferred via chloroplast or mitochondrial electron transfer

system. These electrons can produce reactive oxygen species (ROS), when come into contact

with oxygen molecules. ROS are extremely reactive and cytotoxic to all organisms (Pukacha

and Pukachi 2000) causing per oxidative destruction of cellular constituents (Tiwari et al.

2006; Lee et al. 2007). Stress such as air pollutant enhances ROS formation in plant cell

resulting in an oxidative stress (Dat et al. 2000; Mitteler 2002; Miller et al. 2010). The plant

cells have several antioxidantive defence mechanisms to protect plants against these

oxidative stressors (Kangasjarvi et al. 1994; Pell et al. 1997; Noctor and Foyer 1998;

Sanderman et al. 1998; Ghorbanli et al. 2007). Pollution load dependent increase in Catalase

and Peroxidase content of all the species may be due to the increase rate of production of

reactive oxygen species (ROS) during environmental stress such as air pollution. The ROS or

free radical production under pollution stress would increase the scavenging properties of

enzymatic and non enzymatic metabolites such as Ascorbate, Carotenoid, Superoxide

dismutase, Catalase, Peroxidase (Bowler et al. 1992; Elstner and Osswald 1994) based on

dosage and physiological status of plants. Increased level of Catalase and Peroxidase may be

due to the defence mechanism of the plant. In the present study Catalase and Peroxidase

content in all the plant species were found to be maximum at Site B and A (heavy air

pollution) compared to Site C and D (light and medium air pollution). This may be due to the

interlinked primary protection mechanism offered by Catalase and Peroxidase by scavenging

the product of oxidative stress such as H2O2 and thus help in ameliorating the adverse effect

of oxidative damage to protect them from the heavy pollution load. Varshney and Varshney

(1985) reported increase in peroxides activity in plants under a variety of stresses like

mechanical injury and attack by pathogen or an influence of environmental pollution. The

increase in Peroxidase and Catalase activity varies with the plant species and the

concentration of pollutants.

The correlation values of SO2, NO2, SPM and RSPM with total chlorophyll, ascorbic acid,

sugar and protein content at different selected sites are presented in Table 7. A significant

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negative correlation was found between air quality parameters and different foliar parameters

except ascorbic acid which showed significant positive correlation with pollution load.

Conclusion

The above study concluded that common road side plant species growing at Site B and Site A

of Rourkela city suffers maximum because of heavy pollution compared to Site D and Site C.

Reduction and increase in various parameters of the plant species studied at selected sites can

be considered as an adaption to protect plants against air pollution stress. The present study

suggests that the morphological and biochemical traits of selected roadside plant species can

serve as suitable bio indicators of particulate pollution and an excellent quantitative and

qualitative index of pollution level by capturing significant amount of health- damaging

particles from the atmosphere with the potential to perk up local air quality.

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Exp. Bot. 25: 107-114.

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subsequent colorimetric determination. Analytical Chemistry 28: 1816.

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Figure and Tables Captions:

Figure 1. Location of study sites

Figure 2(A, B, C). Heavy metal (Fe, Zn, Cu) concentration in the leaf sample of the study

sites

Figure 3. Catalase activity of selected plant species at different sites

Figure 4. Peroxidase activity of selected plant species at different sites

Table 1. Ambient Air Quality and Air Pollution Index for different sites during the study

periods.

Table 2. Rating scale for air quality indices

Table 3. Mean concentration of total chlorophyll of selected plant species at different sites.

Table 4. Mean concentration of Ascorbic acid content of selected plant species at different

sites.

Table 5.Mean concentration of total soluble sugar content of selected plant species at

different sites.

Table 6. Mean concentration of total protein content of selected plant species at different

sites.

Table 7. A Correlation between ambient air quality and foliar parameters of selected plant

species.

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Fig – 1: Study site

A)

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B)

C)

Fig-2: Heavy metal concentration in the leaf sample of the study sites during the study period.

A- Concentration of Fe; B- concentration of Zn; C- concentration of Cu.

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Fig-3: Catalase activity of selected plant species at different sites

Fig-4: Peroxidase activity of selected plant species at different sites.

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TABLE- 1: Ambient Air Quality and Air Pollution Index for different sites during the study

periods.

Sl.

No.

Site RSPM

(µg m-3

)

SPM

(µg m-3

)

NO2

(µg m-3

)

SO2

(µg m-3

)

AQI

1 Site-A 190.08 538.32 20.41 17.65 72.75

(MAP)

2 Site-B 220.12 540.09 23.62 21.65 79.50

(HAP)

3 Site-C 165.92 410.28 18.88 11.77 59.00

(MAP)

4 Site-D 128.74 370.43 11.98 9.89 48.50

(LAP)

1 Industrial 150 400 120 120 CPCB

Standard

Where SPM = Suspended particulate matter, RSPM = Respirable Suspended particulate

matter, CPCB = Central Pollution Control Board, New Delhi, India.

Table – 2: Rating scale for indices (ref)

Index Value Remarks

0-25

26- 50

51-75

76-100

>100

Clean Air (CA)

Light Air Pollution

(LAP)

Moderate Air pollution

(MAP)

Heavy Air Pollution

(HAP)

Severe Air Pollution

(SAP)

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Table – 3: Mean concentration of total chlorophyll of selected plant species at different sites.

Table – 4: Mean concentration of Ascorbic acid content of selected plant species at different

sites.

TOTAL CHLOROPHYLL CONTENT(mg/g)

S/N

PLANT SPECIES

SITE-A

SITE-B

SITE-C

SITE-D

1 Ficus bengalensis 0.45±0.06 0.42±0.06 1.10±0.04 1.46±0.03

2 Ficus religiosa 0.32±0.04 0.30±0.03 0.82±0.03 1.08±0.04

3 Mangifera indica 0.49±0.07 0.46±0.07 1.12±0.03 1.84±0.04

4 Bougainvillea spectabilis 1.87±0.03 1.78±0.06 2.07±0.03 2.02±0.08

5 Psidium guajava 1.12±0.04 1.05±0.07 1.54±0.04 1.89±0.11

6 Hibiscus rosasinensis 1.43±0.05 1.36±0.02 1.93±0.12 2.10±0.04

7 Lantana camara 1.59±0.04 1.11±0.02 1.82±0.04 2.00±0.12

8 Delonix regia 0.89±0.13 0.75±0.04 0.91±0.04 1.08±0.02

9 Artocarpus heterophyllus 0.88±0.09 0.83±0.03 0.99±0.02 1.19±0.02

10 Cassia auriculata 1.58±0.09 1.13±0.04 1.90±0.06 1.99±0.05

11 Bauhinia variegate 0.83±0.04 0.65±0.03 0.86±0.05 1.18±0.02

12 Lagerstroemia speciosa 1.11±0.04 1.01±0.15 1.23±0.17 1.76±0.15

ASCORBIC ACID CONTENT(mg/g)

S/N

PLANT SPECIES

SITE-A

SITE-B

SITE-C

SITE-D


2 Ficus religiosa 0.65±0.03 0.71±0.03 0.22±0.02 0.35±0.03



5 Psidium guajava 0.41±0.04 0.50±0.02 0.36±0.04 0.38±1.01


7 Lantana camara 0.33±0.01 0.36±0.04 0.31±0.03 0.25±0.02

8 Delonix regia 0.56±0.03 0.59±0.02 0.40±0.02 0.26±0.04


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Table – 5: Mean concentration of total soluble sugar content of selected plant species at different sites.




TOTAL SOLUBLE SUGAR CONTENT(mg/g)

S/N

PLANT SPECIES

SITE-A

SITE-B

SITE-C

SITE-D


2 Ficus religiosa 0.21±0.04 0.19±0.03 0.49±0.02 0.54±0.03



5 Psidium guajava 0.37±0.11 0.15±0.01 0.56±0.04 0.58±0.03


7 Lantana camara 0.13±0.03 0.11±0.02 0.16±0.02 0.21±0.04

8 Delonix regia 0.31±0.03 0.28±0.06 0.99±0.08 1.02±0.05





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Table – 6: Mean concentration of total protein content of selected plant species at different sites.

Table 7. A Correlation between ambient air quality and foliar parameters of selected plant species.

Total chlorophyll

Ascorbic acid

Protein

Sugar

SPM

-0.9706

0.9562

-0.9716

-0.9895

RSPM -0.9873 0.9948 -0.9136 -0.9168

SO2 -0.9596 0.9589 -0.9899 -0.9796

NO2 -0.9602 0.9700 -0.8208 -0.8371

TOTAL PROTEIN CONTENT(mg/g)

S/N

PLANT SPECIES

SITE-A

SITE-B

SITE-C

SITE-D


2 Ficus religiosa 0.28±0.01 0.21±0.03 0.90±0.06 0.92±0.04



5 Psidium guajava 0.77±0.03 0.63±0.04 1.40±0.06 1.31±0.05

6 Hibiscus rosasinensis 0.71±0.04 0.65±0.05 0.80±±0.01 0.73±0.01

7 Lantana camara 0.78±0.06 0.76±0.05 1.18±0.03 1.12±0.03

8 Delonix regia 0.37±0.03 0.28±0.02 0.66±0.04 0.70±0.05





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