Research Article Open Access Oxygen Generation by Dominant Urban Trees: a case Study from Konnagar Municipality, West Bengal, India Abhijit Mitra



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Abhijit Mitra.

 Biomed J Sci & Tech Res 



             

Research Article                                                                                                                          Open Access

Oxygen Generation by Dominant Urban Trees: A Case Study 

from Konnagar Municipality, West Bengal, India

Abhijit Mitra*

1

, Tanmay Ray Chaudhuri

2

, Nabonita Pal

2

, Sufia Zaman

2

 and Ankita Mitra

3

1

Department of Marine Science, University of Calcutta, India

2

Department of Oceanography, Techno India University, India

3

Center for Oceans, Rivers, Atmosphere and Land Sciences (CORAL), Indian Institute of Technology, India

Received:

 May 20, 2017; Published: May 31, 2017



*Corresponding author:

 

Abhijit Mitra, Department of marine science, University of Calcutta, 35 B.C. Road, Kolkata 700091, India



Introduction

Net oxygen production by trees is a function of the amount 

of oxygen produced during photosynthesis minus the amount 

of oxygen utilized during respiration [1]. If the carbon dioxide 

uptake during photosynthesis exceeds carbon dioxide release by 

respiration during the year, the tree will accumulate carbon (carbon 

sequestration). Thus, a tree that has a net accumulation of carbon 

during a year (tree growth) also has a net production of oxygen. 

This net production of oxygen is estimated as per the following 

expression

Net O

2

 release (Kg/yr) = Net C sequestration (Kg/yr) ×32/12



The entire methodology of estimating oxygen production 

conducted during 2016 involved four phases.



Methodology

Phase 1: Site selection

  

Konnagar is located on the west bank of the River Hooghly 



between 22.7°N and 88.35°E and has an average elevation of ~ 

13.56metres. It is positioned between Rishra and Hindmotor 

on the Howrah-Bardhaman Main Line and Grand Trunk Road. 

Approximate area of Konnagar is 4.32km

2

. A wide spectrum 



of tree species is a noted feature in the landscape of Konnagar. 

The dominant tree species includes Mangifera indica (Mango), 



Azadirachta indica

 (Neem), Aegle marmelos (Bel), Terminalia arjuna 

(Arjun), Eucalyptus globus (Eucalyptus), Psidium guajava (Guava), 

Acacia auriculacformis

 (Akashmoni), Peltophorum pterocarpum 

(Radhachura), Delonix regia (Krishnachura) etc.

Phase 2: Biomass estimation of dominant trees

The entire network of the present study initiated with the 

selection of six sampling zones in the Konnagar Municipality area. 

In each zone 10m×10m quadrat was selected (at random) for 

the study and the average readings were documented from each 

such quadrate by involving the school students and teachers after 

imparting a training to the team members on biomass estimation of 

trees. A form was supplied to all the participating schools where the 

students measured and estimated the Diameter at Breast Height 

(DBH) and Relative Abundance (RA) of the tree species under the 

supervision of their teachers. The mean relative abundance of each 

tree species was evaluated for assessing the order of dominance of 

tree species in the study area. Only those species occupying equal 

to and above 70% in the study area were considered for carbon 

estimation. This exercise (by involving the teachers, students and 

staffs of Konnagar Municipality) was carried out to aware the 

people of all ranks of the society regarding the values of trees in 

upgrading the environmental health.

The Above Ground Biomass (comprising of stem, branch and 

leaf) of individual trees of dominant species in each quadrate 

was estimated as per the standard procedure stated here and the 

average biomass values (of all quadrates of each zone) were finally 

expressed as tonnes per hectare. The methodologies adopted for 

assessing the above ground biomass (sum total of leaf, stem and 

root) in the present study are explained in details through three 

sections.



Cite this article:

 Abhijit M, Tanmay R C, Nabonita P, Sufia Z, Ankita M. Oxygen Generation by Dominant Urban Trees: A Case Study 

   from Konnagar Municipality, West Bengal, India. Biomed J Sci & Tech Res. 1(1)-2017.

Abstract

Urban vegetation, particularly trees provides a wide spectrum of ecosystem services which include upgradation of air quality, stabilizing 

temperature, reduction in ultraviolet radiation, oxygen generation, carbon sequestration, habitat of several flora and fauna (enhancement of 

biodiversity) aesthetic beauty etc. Oxygen production is one of the most commonly cited benefits of urban trees. The purpose of this article is 

to estimate the oxygen production by the dominant trees in the urban area of Konnagar, compare it with the estimated oxygen consumption by 

the population of the area and illustrate why oxygen production by urban trees is an important ecosystem service.



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 Biomed J Sci & Tech Res 



Section 1: Stem biomass estimation

The stem biomass for each tree species in every plot was 

estimated using non-destructive method in which the Diameter 

at the Breast Height (DBH) was measured after assessing the 

circumference with a measuring tape and height with laser beam 

(BOSCH DLE 70 Professional model). Form factor was determined 

with Spiegel relascope as per the method outlined by Koul and 

Panwar[2]. The stem volume (V) was then calculated using the 

expression FHΠr

2

, where F is the form factor, r is the radius of the 



tree derived from its DBH and H is the height of the target tree. 

Specific  gravity  (G)  of  the  wood  was  estimated  taking  the  stem 

cores, which was further converted into stem biomass (B

S

) as per 



the expression B

S

 = GV.



Section 2: Branch biomass estimation

 The total number of branches irrespective of size was counted 

on each of the sample trees. These branches were categorized on 

the basis of basal diameter into three groups, viz. <6cm, 6–10cm 

and >10cm. Dry weight of two branches from each size group was 

recorded separately using the equation of Chidumaya [3].

 Total branch biomass (dry weight) per sample tree was 

determined as per the expression:

B

db

 = n



1

bw

1



 + n

2

bw



2

 + n


3

bw

3



 = Σ n

i

bw



i

Where, Bdb is the dry branch biomass per tree, n

i

 the number of 



branches in the i

th

 branch group, b



wi

 the average weight of branches 

in the i

th

 group and i = 1, 2, 3, …..n are the branch groups. This 



procedure was followed for all the dominant tree species separately 

for every quadrate.



Section 3: Leaf biomass estimation

Leaves from nine branches (three of each size group as stated in 

section 2) of individual trees of each species were removed. One tree 

of each species per quadrate was considered for estimation. The 

leaves were weighed and oven dried separately (species wise) to a 

constant weight at 80 ± 50C. The leaf biomass was then estimated 

by multiplying the average biomass of the leaves per branch with 

the number of branches in a single tree and the average number of 

trees per plot as per the expression:

L

db



 = n

1

Lw



1

N

1



 + n

2

Lw2N



2

 + ……….n


i

Lw

i



N

i

Where, L



db

 is the dry leaf biomass of the tree species per 

quadrate, n

1

..….n



i

 are the number of branches of each tree species, 

Lw

1

 …….Lw



i

 are the average dry weight of leaves removed from the 

branches and N

1

………N



i

 are the number of trees per species in the 

quadrate. 

Phase 3: Estimation carbon and carbon sequestration

Direct estimation of percent carbon was done by a CHN 

analyzer. For this, a portion of fresh sample of stem, branch and leaf 

from selected trees (two trees/species/plot) of individual species 

(covering all the selected plots) was oven dried at 700C, separately 

ground to pass through a 0.5mm screen (1.0mm screen for leaves). 

The  carbon  content  (in  %)  was  finally  analyzed  for  each  part  of 

each species through a Vario MACRO elementar CHN analyzer. The 

total stored carbon in the above ground biomass was estimated 

by considering the mean relative abundance of each species in the 

selected quadrats and finally the stored carbon in the above ground 

biomass was estimated for each species by dividing the values with 

the respective age of the species. The information on the age of the 

tree was collected from the local inhabitants.



Result

The AGB of the study site was in the order Eucalyptus globus 

(5853.95) > Tamarindus indica (4195.60) > Aegle marmelos 

(3202.00) > Arecea catechu (3111.52) > Delonix regia (2854.98) 

Magnifera indica (2474.53) > Ficus religiosa (2143.11) > Acacia 

auriculacformis

 (1961.45) > Ficus bengalensis (1095.66) > Psidium 



guajava

 (924.92) > Cocos nucifera (914.90) Bombax ceiba (830.03) 

Peltophorum pterocarpum (604.14) > Tectona grandis (542.72) > 

Dalberegia sissoo

 (486.62) > Terminalia arjuna (481.24) > Swietenia 



mahagoni

 (455.35) > Albizia saman (448.24) > Polyalthia longifolia 

(341.39) > Azadirachta indica (307.89) > Ziziphus mauritiana 

(301.74) > Terminalia catappa (233.12) > Artocarpus heterophyllus 

(228.67) > Alstonia scholaris (116.54) > Murraya koenigii (34.10) > 

Syzygium samarangense

 (30.10) > Santalum album (5.96) (Table 1). 

Similarly the AGC followed the sequence of Eucalyptus globus 

(2716.23) > Tamarindus indica (1929.98) > Aegle marmelos 

(1501.74) > Arecea catechu (1481.08) > Delonix regia (1350.41) 

>  Magnifera indica (1328.82) > Ficus religiosa (1073.70) > 



Acacia auriculacformis

 (927.77) > Ficus bengalensis (540.16) > 



Psidium guajava

 (454.14) > Cocos nucifera (432.74) > Bombax 



ceiba

 (392.60) > Peltophorum pterocarpum (275.69) > Tectona 



grandis

 (249.11) > Terminalia arjuna (223.30) > Dalberegia sissoo 

(222.87) > Albizia saman (220.09) > Swietenia mahagoni (219.02) 

>  Polyalthia longifolia (156.70) > Ziziphus mauritiana (145.44) 

>  Azadirachta indica (141.01) > Terminalia catappa (114.23) > 

Artocarpus heterophyllus

 (111.82) > Alstonia scholaris (55.71) 

>  Murraya koenigii (15.96) > Syzygium samarangense (14.21) > 

Santalum album

 (3.27) (Table 1).

The net oxygen release varied as per the order Tamarindus 

indica

 (429.42) > Arecea catechu (395.45) > Eucalyptus globus 

(381.70) > Aegle marmelos (364.51) > Acacia auriculacformis 

(225.19) > Delonix regia (200.30) > Magnifera indica (186.74) > 



Psidium guajava

 (134.73) > Cocos nucifera (105.04) > Ficus religiosa 

(95.56) > Swietenia mahagoni (83.54) > Bombax ceiba (58.23) > 

Borassus flabellifer

 (56.34) > Albizia saman (41.97) > Peltophorum 



pterocarpum

 (40.85) > Terminalia arjuna (39.70) > Tectona grandis 

(39.12) > Terminalia catappa (38.15) > Dalberegia sissoo (33.05) > 

Polyalthia longifolia

 (32.17) > Ziziphus mauritiana (29.88) > Ficus 



bengalensis

 (22.19) > Azadirachta indica (19.81) > Artocarpus 



heterophyllus

 (13.16) > Alstonia scholaris (12.39) > Murraya 



koenigii

 (6.09) > Syzygium samarangense (4.22) > Santalum album 

(0.72) (Table 1).

Discussion

The production of oxygen by the trees is undoubtedly an 

important ecosystem service as this gas regulates the metabolic 


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activities of living organisms. An average adult human being 

consumes 0.84 kg of oxygen per day, which is equivalent to 1.85 lb per 

day [4]. Considering this value, the average oxygen consumption in 

Konnagar Municipality is 306.6Kg/year/head. As per 2011 census, 

Konnagar had a population of approximately 80,000 and therefore 

there is a necessity of 24,528 tonnes of oxygen per year to sustain 

this population. The present study shows that the yearly generation 

of oxygen by the 28 dominant species in Konnagar Municipality is 

2959.68,  which  indicates  that  there  is  an  approximate  deficit  of 

oxygen in the Municipality area by 8 times to balance the need 

of oxygen by the population of Konnagar Municipality. In other 

words 8 times more plantations are required to meet the oxygen 

requirement of the people of the area. This calculation, however, 

has uncertainty as the seedlings and grassy vegetations have not 

been considered in the present estimation. The water bodies of 

Konnagar Municipality have also been overlooked in this estimation 

process, although phytoplankton are the major sources of oxygen in 

the ambient environment. Our first order analysis, however, reports 

that trees like Tamarindus indica, Arecea catechu, Eucalyptus globus, 

Aegle marmelos

 need to be planted to restore the oxygen depletion 

in the present municipality area. A more detailed study considering 

the seedlings, herbs and shrubs along with oxygen generated by 

phytoplankton is needed to achieve a comprehensive picture of 

floral based oxygen budget in the present geographical locale.



Table 1:

 List of dominant tree species in Konnnagar Municipality with their respective AGB, AGC, C-sequestration and O

2

 release values.



Sl. No.

Species

AGB (tonnes ha

-1

)

AGC (tonnes ha

-1

)

C sequestration 

(tonnes ha

-1

 y

-1

)

O

2

 release (tonnes 

ha

-1

 y

-1

)

1

Cocos nucifera

 (Coconut)

914.90


432.74 

(47.3%)


39.34 (11)

105.04


2

Murraya koenigii

 (Curry tree)

34.10

15.96


(46.8%)

2.28 (7)


6.09

3

Albizia saman

 (Shirish)

448.24


220.09

(49.1%)


15.72 (14)

41.97


4

Azadirachta indica

 (Neem)


307.89

141.01


(45.8%)

7.42 (19)

19.81


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5

Mangifera indica

 (Mango)


2474.53

1328.82


(53.7%)

69.94 (19)

186.74

6

Tamarindus indica



 (Tentul)

4195.60


1929.98

(46.0%)


160.83 (12)

429.42


7

Bombax ceiba

 (Shimul)

830.03

392.60


(47.3%)

21.81 (18)

58.23

8

Aegle marmelos



 (Bel)

3202.00


1501.74

(46.9%)


136.52 (11)

364.51


9

Terminalia arjuna

 (Arjun)


481.24

223.30


(46.4%)

14.87 (15)

39.70


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10

Tectona grandis

 (Segun)


542.72

249.11


(45.9%)

14.65 (17)

39.12

11

Delonix regia



 (Krishnachura)

2854.98


1350.41

(47.3%)


75.02 (18)

200.30


12

Artocarpus heterophyllus

 (Jackfruit)

228.67

111.82


(48.9%)

12.42 (9)

13.16

13

Swietenia mahagoni



 (Mahogany)

455.35


219.02

(48.1%)


31.29 (7)

83.54


14

Terminalia catappa

 (Kath badam)

233.12

114.23


(49.0%)

14.29 (8)

38.15


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15

Psidium guajava

 (Guava)


924.92

454.14


(49.1%)

50.46 (9)

134.73

16

Acacia auriculacformis



 (Akashmoni)

1961.45


927.77

(47.3%)


84.34 (11)

225.19


17

Alstonia scholaris

 (Chatim)

116.54

55.71


(47.8%)

4.64 (12)

12.39

18

Ziziphus mauritian



a (Kul)

301.74


145.44

(48.2%)


11.19 (13)

29.88


19

Eucalyptus globus

 (Eucalyptus)

5853.95

2716.23


(46.4%)

142.96 (19)

381.70


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20

Dalbergia sissoo

 (Shishu)

486.62

222.87


(45.8%)

12.38 (18)

33.05

21

Syzygium samarangense



 (Jamrul)

30.10


14.21

(47.2%)


1.58 (9)

4.22


22

Santalum album

 (Sandal)

5.96

3.27


(54.9%)

0.27 (12)

0.72

23

Peltophorum pterocarpum



 (Radhachura)

604.14


275.49

(45.6%)


15.30 (18)

40.85


24

Polyalthia longifolia

 (Debdaru)

341.39

156.70


(45.9%)

12.05 (13)

32.17


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25

Borassus flabellifer

 (Sugar palm)

348.77

168.80


(48.4%)

21.10 (8)

56.34

26

Areca catechu



 (Betel palm or Supari)

3111.52


1481.08

(47.6%)


148.11 (10)

395.45


27

Ficus religiosa

 (Peepul)

2143.11

1073.70


(50.1%)

35.79 (30)

95.56 95.56

28

Ficus benghalensis

 (Banyan)

1095.66


540.16

(49.3%)


8.31 (65)

22.19


References

1. 


Salisbury FB, CW Ross (1978) Plant Physiology. Wadsworth Publishing 

Company, Belmont, CA, USA, pp. 422.

2. 

Koul DN, Panwar P (2008) Prioritizing Land-management options for 



carbon sequestration potential. Curr Sci 95: 5-10.

3. 


Chidumaya EN (1990). Above ground woody biomass structure and 

productivity in a Zambezian woodland. For Ecol & Manage 36: 33-46.

4. 

Perry  JL,  MD  LeVan  (2003)  Air  Purification  in  Closed  Environments. 



Overview of Spacecraft Systems. U.S.  Army Natrick Soldier Center, USA.

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Document Outline

  • Title
  • Abstract
  • Introduction
  • Methodology
    • Phase 1: Site selection
    • Phase 2: Biomass estimation of dominant trees
      • Section 1: Stem biomass estimation
      • Section 2: Branch biomass estimation
      • Section 3: Leaf biomass estimation
    • Phase 3: Estimation carbon and carbon sequestration
  • Result
  • Discussion
  • References
  • Table 1


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