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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 01 | Jan -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 598
Sequestration and storage of carbon by trees in and around University
campus of Aurangabad city in Maharashtra, India.
Potadar Vishnu R1, and Satish S Patil2
Research student, Department of Environmental Sciences, Dr. Babasaheb Ambedkar Marathwada University Aurangabad
vishnupotadar@gmail.com
Professor, Department of Environmental Sciences, Dr. Babasaheb Ambedkar Marathwada University Aurangabad
sushshrey@rediffmail.com
Abstract:Trees from the urban regions currently store
carbon, which can be released into the atmosphere after the
death of tree, and capture carbon as they grow. A major
challenge is the lack of correct and spatially explicit
estimates of tree carbon storage over the entire urbanized
area. The study was carried out in and around university
campus of Aurangabad city to know the CO2 sequestration
from the selected ten tree species. Assessment of the carbon
sequestration of urban trees was carried out through the
biomass estimation and quantification. For the estimation of
total CO2 sequestration DBH and height measured. Wood
densities were obtained from world agroforestry centre. It
is found that highest CO2 3916. 81 kg/tree captured by
Swietenia mahagoni followed by Pithocellobium dulce which
is captured 1401.18 kg of CO2 per tree. Total above ground
biomass 3463.10, total below ground biomass 900, total
biomass 4363.50, total carbon 2181.75 kg/tree. Total tree
count is 835 out of which Roystonea regia found 206 tree
count which is maximum. It is found that total CO2
sequestered by the selected area is 565.32 tonnes. Carbon
sequestration is a way to mitigate the accumulation of
greenhouse gases in the atmosphere released by the burning
of fossil fuels and other anthropogenic activities.
KEYWORDS: - biomass, tree, CO2 sequestration, gas, fuels
1. INTRODUCTION
More than half of the population at the global level now lives
in urban regions, and this figure will continue to increase at
a rate of 4% a decade by 2050 [1]. Carbon sequestration is
one of the important processes of storage of CO2 or other
forms of carbon to mitigate environmental issues like global
warming, green house effect and its one of the important
clause of Kyoto Protocol, through biological, chemical or
physical processes; CO2 is sequestered from the atmosphere.
The Kyoto Protocol to the UN Framework Convention on the
Climate Change has provided a vehicle for considering the
various effects of carbon sinks and sources, as well as
addressing issues concerned to fossil fuels emission.
Growing concern about the climate change and concerned
problems led to the research quantifying the overall effects
of trees from the urban area on atmospheric carbon dioxide
(CO2 ) [4,5,6,7,8,9]. Trees from Urban area also affect
temperatures of air and building energy use, and
consequently alter carbon release from numerous urban
sources [2]. Thus, urban trees potentially influence the
climate at the local level, carbon cycles, energy use and the
climate change [10, 11, 12, 13, 14]. Urban trees affect
climate change, but these trees are often disregarded
because their environmental services are not so well
understood or quantified. Trees act as a sink for carbon
dioxide (CO2) by fixing carbon during the photosynthesis
and storing carbon as the biomass. The clear long-term CO2
origin dynamics of the forests change through time as trees
grow, die, and decay. Human influences on forests can
further affect CO2 source dynamics of urban forests through
such components as fossil fuel emissions and harvesting of
biomass [3].
2. MATERIALS AND METHODS
2.1 Location
The study area comprises of 2126 hectares of area which is
mainly from B.A.M. University campus and Jaisingpura,
Pahadsingpura etc. The district is from 19 to 20 degrees
north longitude and 74 to 76 degrees east latitude.
Aurangabad city is situated on the river bank Kham a
tributary of the Godavari river. The entire city is situated at
the latitude of 19o53’50” N and longitude of 75o22’46” E.
Aurangabad District is located mainly in the Godavari river
basin and partly in the Tapi river basin. The city is
surrounded by the hills of the Vindhya ranges and the river
Kham passes through it.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 01 | Jan -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 599
2.2 Measurement of diameter at breast height (DBH)
and tree height:
To estimate the biomass of different trees, non-destructive
method was used. The biomass of the tree was estimated on
the basis of diameter at breast height (DBH) and tree height.
DBH can be determined by measuring tree Girth at Breast
Height (GBH), approximately 1.3 meter above the ground.
The GBH of trees having the diameter greater than 10 cm
were measured directly by the measuring tape [21]. The tree
height measured by the Theodolite instrument.
2.3 Above ground biomass (AGB) of trees:
The above ground biomass of the tree includes whole shoot,
branches, flowers, leaves and fruits. It is calculated using the
following formula.[22].
AGB kg = volume of tree (m3) x wood density Kg/m3
V = π r2H
Where H = Height of the tree in meter, V= volume of the
cylindrical shaped tree in m3, r = radius of the tree in meter,
Radius of the tree is calculated from GBH of tree. Height was
measured with the help of the instrument Theodolite. The
wood densities were obtained from the website
www.worldagroforestycentre.org. The standard average
density of 0.6 gm/cm was applied wherever the density
value is not available for tree species [20].
2.4 Estimation of the Below Ground Biomass (BGB)
The Below Ground Biomass (BGB) includes all biomass of
live roots excluding fine roots having < 2 mm diameter. The
below ground biomass was calculated by multiplying AGB
by 0.26 factors as the root: shoot ratio. BGB is calculated by
following formula [21,20, 23].
BGB (Kg/tree) = AGB (Kg/tree) or (ton/tree) x 0.26
Table 1: Wood densities of tree species
Sr.
No.
Tree Species
(Scientific Name)
Local name Wood
density in
g/cm3
1
Pithecellobium
dulce
Vilayati chinch
0.6657
2
Polyalthia
longifolia
Ashok
0.5635
3 Pongamia pinnata Karanj 0.6198
4 Psidium guajava Peru 0.6713
5 Punica granatum Dalimb 0.771
6 Roystonea regia palm tree 0.66
7 Santalum album Chandan 0.9367
8 Sesbania sesban Shevari 0.43
9
Spathodea
campanulata
Pichkari
0.3303
10
Swietenia
mahagoni
Mohogony
0.66
3. RESULTS AND DISCUSSION
Humans constantly interact with the natural environment to
create some differences in the tree cover. Costs of
maintaining the cover of vegetation and attitudes toward the
trees in urban landscape, both related to ambient
environmental factors, alter the desire and ability of
individuals to incorporate trees in the urban landscape. Tree
cover can be increased by allowing space for the vegetation
cover, planting, and inspiring natural regeneration.
Measurements of the tree cover provide important basic
structural data used to model urban tree cover functions
such as air pollution control and carbon dioxide capture
[19]. Understanding the relationship among the urban trees,
people, and environment can facilitate probable urban
designs that might increase the environmental and social
benefits from trees. Large trees also preserve approximately
1000 times maximum carbon than smaller trees [19,20]. It
may be one of the crucial green region in the urban and
industrial sectors. Carbon capture rates vary by species, soil,
climate, topography and most important is management
practice [13]. Environmentalists have highlighted the role of
urban forests as a place of social integration as they provide
recreation and relief to the urban population from their
hectic life.
More research work is required on the overall effects of
trees, soils and its proper management in the urban areas.
Carbon storage by tree species in woodlands at national
level was 20.2 billion tonnes in 2008 [20].
Table 2: Shows Biophysical measurements with AGB
and BGB
Sr
.
N
o.
Scientific
name
DBH
(Mete
rs)
Heigh
t
(Mete
rs)
Volu
me
(m3)
AGB
(kg/tr
ee)
BGB
(kg/tr
ee)
1
Pithecello
bium
dulce 0.363 8.79 0.91
606.6
4
157.7
3
2
Polyalthia
longifolia 0.194 7.88 0.23
131.2
2 34.12
3
Pongamia
pinnata 0.189 5.88 0.16
101.7
0 26.44
4
Psidium
guajava 0.192 5.99 0.17
116.0
5 30.17
5
Punica
granatum 0.142 4.19 0.07 50.97 13.25
6
Roystonea
regia 0.317 8.46 0.67
400.4
7
104.1
2
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 01 | Jan -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 600
7
Santalum
album 0.17 4.49 0.10 91.79 23.86
8
Sesbania
sesban 0.148 4.25 0.07 31.50 8.19
9
Spathodea
campanul
ata 0.295 10.50 0.72
237.0
0 61.62
1
0
Swietenia
mahagoni 0.464 15.22 2.57
1695.
76
440.9
0
Average
0.247 7.56 0.56
346.3
0 90.04
Total
2.474 75.64 5.67
3463.
10
900.4
0
Table 3: Shows TB, C, CO2, Tree count, Total CO2
Sr
.
N
o.
Scientific
name
TB
(kg/tr
ee)
C
(kg/tr
ee)
CO2
(kg/tr
ee)
Tre
e
cou
nt
Total
CO2
(Tonn
es)
1
Pithecello
bium dulce
764.3
6
382.1
8
1401.
19 156
218.5
86
2
Polyalthia
longifolia
165.3
4 82.67
303.1
0 40
12.12
4
3
Pongamia
pinnata
128.1
4 64.07
234.9
1 205
48.15
6
4
Psidium
guajava
146.2
2 73.11
268.0
5 156
41.81
5
5
Punica
granatum 64.22 32.11
117.7
2 40 4.709
6
Roystonea
regia
504.6
0
252.3
0
925.0
0 206
190.5
50
7
Santalum
album
115.6
5 57.83
212.0
1 7 1.484
8
Sesbania
sesban 39.69 19.85 72.76 6 0.437
9
Spathodea
campanul
ata
298.6
2
149.3
1
547.4
2 8 4.379
1
0
Swietenia
mahagoni
2136.
66
1068.
33
3916.
82 11
43.08
5
Average 436.3
5
218.1
7
799.8
9 83.5
56.53
0
Total 4363.
50
2181.
75
7998.
96 835
565.3
20
Carbon capture and sequestration is a theoretical approach
to control and mitigate the contribution of emissions of
fossil fuels to global warming, based on capturing carbon
dioxide from large point sources such as the fossil fuel
power plants. The carbon dioxide might then be stored away
from the atmosphere permanently. As urban areas discharge
maximum amount of emissions of carbon, tree creates an
impact on carbon emissions through changing in climates at
micro level, albedo, use of energy, and maintenance of
emissions which require to be added with tree storage and
capture estimates to improve a more complete evaluation of
the role of trees of the urban area on climate change [20].
Graph showing CO2 sequestration
The study was conducted in the Aurangabad city to estimate
the above ground biomass, below ground biomass, total
biomass, carbon dioxide, carbon from selective ten tree
species. Swietenia mahagoni has sequestered 3916.81
kg/tree of CO2 which is highest compared to other tree
species from the study area. It is due to high DBH and height
of the tree. At the same time AGB 1695.76, BGB 440.89, total
biomass 2136.65, carbon 1068.32 which is highest in the
Swietenia mahagoni which has only 11 tree count. Sesbania
sesban sequestered lowest CO2 72.75 kg/tree compared to
other trees which is may be due to lowest DBH i.e. 0.148
meters, total biomass sequestered 39.69 kg/tree. Total tree
count of the study area is 835. Maximum 206 trees found of
Roystonea regia and only 6 trees found of Sesbania sesban
from the study area. Total AGB 3463.10, total BGB 900, Total
biomass 4363.50, Total carbon 2181.75, total CO2
sequestered is 7998.96kg/tree and total CO2 from all tree
species from the study area is 565.32 tonnes. Large healthy
trees having the diameter more than 77 cm sequester
approximately 90 times more carbon as compared to the
small healthy trees species which have the diameter less
than 8 cm [19]. Large trees also store nearly 1000 times
maximum carbon than smaller trees [20, 19].
0.0
1000.0
2000.0
3000.0
4000.0
1401.2
303.1234.9268.0117.7
925.0
212.072.8
547.4
3916.8
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 01 | Jan -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 601
REGRESSION ANALYSIS
To estimate the closeness and relationships various
parameters a regression analysis was performed with the
help of SPSS 16.0 software.
Model Summary
Mode
l R
R
Square
Adjuste
d R
Square
Std. Error of
the
Estimate
1 .949a .900 .871 .27519
a. Predictors: (Constant), Height,
DBH
Coefficientsa
Model
Unstandardized
Coefficients
Standardize
d
Coefficients
t Sig.B
Std.
Error Beta
1 (Constant
) -1.097 .229
-
4.79
1
.00
2
DBH
3.169 2.321 .443
1.36
6
.21
4
Height
.116 .072 .522
1.61
0
.15
2
a. Dependent Variable: Volume
Where,
t = Statistics R= Multiple correlation coefficient; R2 and
adjusted R2 = Coefficient determination of variablesB=
Regression coefficient
Above table shows that strong correlation coefficient
between DBH with volume and the height whereas adjusted
R2 shows 87 % variability between the Volume with DBH
and Height. Above statistical table shows that volume is
significant with DBH. As increase in DBH its metabolic and
the growth necessities would also increase.
4. CONCLUSION
Trees from urban area play crucial roles in reduction of the
atmospheric carbon dioxide levels. In the present research
work calculation of AGB, BGB, TB, carbon and carbon
dioxide sequestration potential rate often tree species was
done by nondestructive method. Theodolite instrument was
used for height measurement. Wood densities were
obtained from the World Agroforestry Centre for the
measurement of carbon sequestered by trees. Carbon stock
was determined for Pithecellobium dulce, Polyalthia
longifolia, Pongamia pinnata, Psidium guajava, Punica
granatum, Roystonea regia, Santalum album, Sesbania
sesban, Spathodea campanulata, Swietenia mahagoni tree
species in and around university campus of Aurangabad city.
Results show that Swietenia mahagoni has the better carbon
sequestration potential rate which sequestered 3916.81
kg/tree of CO2 whereas Sesbania sesban has the least
sequestration rate which sequestered 72.75 kg/tree of CO2
as compared to other species. Total tree count is 835. Total
carbon sequestered 2181.75. Total carbon dioxide from all
the tree species sequestered 7998.96 kg/tree. Carbon
dioxide sequestered by the trees 565.32 tonnes. More field
measurements are needed in urban regions to help improve
carbon accounting and other functions of urban forest
ecosystems. Before applying the approach of urban tree
management, quantification of organic carbon in the urban
region by nondestructive method will be helpful.
REFERENCES
[1] United Nations (2015). World Urbanization
Prospects: The 2014 Revision. NewYork, NY: United
Nations Department of Economic and Social Affairs,
Population Division.
[2] Nowak, D.J. (1993). Atmospheric carbon reduction
by urban trees. Journal of Environmental
Management 37 (3), 207-217.
[3] Nowak, D.J. (2010). Urban biodiversity and climate
change. In: Muller, N., Werner, P., Kelcey, J.G. (Eds.),
Urban Biodiversity and Design. Wiley-Blackwell
Publishing, Hoboken, NJ, pp. 101-117.
[4] McPherson EG (1998). Atmospheric carbon dioxide
reduction by Sacramento’s urban forest. J Arboric
24(4):215–223
[5] Jo HK (2002). Impacts of urban greenspace on
offsetting carbon emissions for middle Korea. J
Environ Manage 64(2):115–126
[6] Nowak DJ, Crane DE (2002). Carbon storage and
sequestration by urban trees in the USA. Environ
Pollut 116(3):381–389
[7] Escobedo F, Varela S, Zhao M, Wagner JE, Zipperer
W (2010) Analyzing the effi cacy of subtropical
urban forests in offsetting carbon emissions from
cities. Environ Sci Policy 13(5):362–372
[8] Stoffberg GH, van Rooyen MW, van der Linde MJ,
Groeneveld HT (2010) Carbon sequestration
estimates of indigenous street trees in the City of
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 01 | Jan -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 602
Tshwane, South Africa. Urban For Urban Green
9(1):9–14
[9] Zhao M, Escobedo F, Staudhammer C (2010) Spatial
patterns of a subtropical, coastal urban forest:
implications for land tenure, hurricanes and
invasives. Urban For Urban Green. doi: 10.1016/j.
ufug.2010.01.008
[10] Abdollahi, K.K., Ning, Z.H., Appeaning, A. (2000).
Global Climate Change and the Urban Forest. GCRCC
and Franklin Press, Baton Rouge, pp. 31-44.
[11] Wilby, R.L., Perry, G.L.W. (2006). Climate change,
biodiversity and the urban environment: a critical
review based on London UK. Progress in Physical
Geography 30 (1), 73-98.
[12] Gill, S.E., Handley, J.F., Ennos, A.R., Pauleit, S.
(2007). Adapting cities for climate change: the role
of the green infrastructure. Built Environment 33
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[13] EPA (2010). Environmental co-benefits of
sequestration practices. Internet file http;//www.
epa.gov/sequestration/fag.html.
[14] Lal, R., Augustine, B. (2012). Carbon Sequestration
in Urban Ecosystems. Springer, New York, p. 385.
[15] Nowak, D.J., 1994. Atmospheric carbon dioxide
reduction by Chicago’s urban forest. In: McPherson,
E.G., Nowak, D.J., Rowntree, R.A. (Eds.), Chicago’s
Urban Forest Ecosystem: Results of the Chicago
Urban Forest Climate Project. USDA Forest Service
General Technical Report NE-186, Radnor, PA, pp.
83–94.
[16] Potadar Vishnu R, and Satish S Patil. (2016).
Carbon Storage and Sequestration by Trees in and
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Maharashtra. International Journal of Innovative
Research in Science, Engineering and Technology
Vol. 5, Issue 4, April 2016 ISSN (Online) : 2319-8753
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M.Mahajan and NishaChaudhari (2012). Carbon
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Sequestration and storage of carbon by trees in and around University campus of Aurangabad city in Maharashtra, India.

  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 01 | Jan -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 598 Sequestration and storage of carbon by trees in and around University campus of Aurangabad city in Maharashtra, India. Potadar Vishnu R1, and Satish S Patil2 Research student, Department of Environmental Sciences, Dr. Babasaheb Ambedkar Marathwada University Aurangabad vishnupotadar@gmail.com Professor, Department of Environmental Sciences, Dr. Babasaheb Ambedkar Marathwada University Aurangabad sushshrey@rediffmail.com Abstract:Trees from the urban regions currently store carbon, which can be released into the atmosphere after the death of tree, and capture carbon as they grow. A major challenge is the lack of correct and spatially explicit estimates of tree carbon storage over the entire urbanized area. The study was carried out in and around university campus of Aurangabad city to know the CO2 sequestration from the selected ten tree species. Assessment of the carbon sequestration of urban trees was carried out through the biomass estimation and quantification. For the estimation of total CO2 sequestration DBH and height measured. Wood densities were obtained from world agroforestry centre. It is found that highest CO2 3916. 81 kg/tree captured by Swietenia mahagoni followed by Pithocellobium dulce which is captured 1401.18 kg of CO2 per tree. Total above ground biomass 3463.10, total below ground biomass 900, total biomass 4363.50, total carbon 2181.75 kg/tree. Total tree count is 835 out of which Roystonea regia found 206 tree count which is maximum. It is found that total CO2 sequestered by the selected area is 565.32 tonnes. Carbon sequestration is a way to mitigate the accumulation of greenhouse gases in the atmosphere released by the burning of fossil fuels and other anthropogenic activities. KEYWORDS: - biomass, tree, CO2 sequestration, gas, fuels 1. INTRODUCTION More than half of the population at the global level now lives in urban regions, and this figure will continue to increase at a rate of 4% a decade by 2050 [1]. Carbon sequestration is one of the important processes of storage of CO2 or other forms of carbon to mitigate environmental issues like global warming, green house effect and its one of the important clause of Kyoto Protocol, through biological, chemical or physical processes; CO2 is sequestered from the atmosphere. The Kyoto Protocol to the UN Framework Convention on the Climate Change has provided a vehicle for considering the various effects of carbon sinks and sources, as well as addressing issues concerned to fossil fuels emission. Growing concern about the climate change and concerned problems led to the research quantifying the overall effects of trees from the urban area on atmospheric carbon dioxide (CO2 ) [4,5,6,7,8,9]. Trees from Urban area also affect temperatures of air and building energy use, and consequently alter carbon release from numerous urban sources [2]. Thus, urban trees potentially influence the climate at the local level, carbon cycles, energy use and the climate change [10, 11, 12, 13, 14]. Urban trees affect climate change, but these trees are often disregarded because their environmental services are not so well understood or quantified. Trees act as a sink for carbon dioxide (CO2) by fixing carbon during the photosynthesis and storing carbon as the biomass. The clear long-term CO2 origin dynamics of the forests change through time as trees grow, die, and decay. Human influences on forests can further affect CO2 source dynamics of urban forests through such components as fossil fuel emissions and harvesting of biomass [3]. 2. MATERIALS AND METHODS 2.1 Location The study area comprises of 2126 hectares of area which is mainly from B.A.M. University campus and Jaisingpura, Pahadsingpura etc. The district is from 19 to 20 degrees north longitude and 74 to 76 degrees east latitude. Aurangabad city is situated on the river bank Kham a tributary of the Godavari river. The entire city is situated at the latitude of 19o53’50” N and longitude of 75o22’46” E. Aurangabad District is located mainly in the Godavari river basin and partly in the Tapi river basin. The city is surrounded by the hills of the Vindhya ranges and the river Kham passes through it.
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 01 | Jan -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 599 2.2 Measurement of diameter at breast height (DBH) and tree height: To estimate the biomass of different trees, non-destructive method was used. The biomass of the tree was estimated on the basis of diameter at breast height (DBH) and tree height. DBH can be determined by measuring tree Girth at Breast Height (GBH), approximately 1.3 meter above the ground. The GBH of trees having the diameter greater than 10 cm were measured directly by the measuring tape [21]. The tree height measured by the Theodolite instrument. 2.3 Above ground biomass (AGB) of trees: The above ground biomass of the tree includes whole shoot, branches, flowers, leaves and fruits. It is calculated using the following formula.[22]. AGB kg = volume of tree (m3) x wood density Kg/m3 V = π r2H Where H = Height of the tree in meter, V= volume of the cylindrical shaped tree in m3, r = radius of the tree in meter, Radius of the tree is calculated from GBH of tree. Height was measured with the help of the instrument Theodolite. The wood densities were obtained from the website www.worldagroforestycentre.org. The standard average density of 0.6 gm/cm was applied wherever the density value is not available for tree species [20]. 2.4 Estimation of the Below Ground Biomass (BGB) The Below Ground Biomass (BGB) includes all biomass of live roots excluding fine roots having < 2 mm diameter. The below ground biomass was calculated by multiplying AGB by 0.26 factors as the root: shoot ratio. BGB is calculated by following formula [21,20, 23]. BGB (Kg/tree) = AGB (Kg/tree) or (ton/tree) x 0.26 Table 1: Wood densities of tree species Sr. No. Tree Species (Scientific Name) Local name Wood density in g/cm3 1 Pithecellobium dulce Vilayati chinch 0.6657 2 Polyalthia longifolia Ashok 0.5635 3 Pongamia pinnata Karanj 0.6198 4 Psidium guajava Peru 0.6713 5 Punica granatum Dalimb 0.771 6 Roystonea regia palm tree 0.66 7 Santalum album Chandan 0.9367 8 Sesbania sesban Shevari 0.43 9 Spathodea campanulata Pichkari 0.3303 10 Swietenia mahagoni Mohogony 0.66 3. RESULTS AND DISCUSSION Humans constantly interact with the natural environment to create some differences in the tree cover. Costs of maintaining the cover of vegetation and attitudes toward the trees in urban landscape, both related to ambient environmental factors, alter the desire and ability of individuals to incorporate trees in the urban landscape. Tree cover can be increased by allowing space for the vegetation cover, planting, and inspiring natural regeneration. Measurements of the tree cover provide important basic structural data used to model urban tree cover functions such as air pollution control and carbon dioxide capture [19]. Understanding the relationship among the urban trees, people, and environment can facilitate probable urban designs that might increase the environmental and social benefits from trees. Large trees also preserve approximately 1000 times maximum carbon than smaller trees [19,20]. It may be one of the crucial green region in the urban and industrial sectors. Carbon capture rates vary by species, soil, climate, topography and most important is management practice [13]. Environmentalists have highlighted the role of urban forests as a place of social integration as they provide recreation and relief to the urban population from their hectic life. More research work is required on the overall effects of trees, soils and its proper management in the urban areas. Carbon storage by tree species in woodlands at national level was 20.2 billion tonnes in 2008 [20]. Table 2: Shows Biophysical measurements with AGB and BGB Sr . N o. Scientific name DBH (Mete rs) Heigh t (Mete rs) Volu me (m3) AGB (kg/tr ee) BGB (kg/tr ee) 1 Pithecello bium dulce 0.363 8.79 0.91 606.6 4 157.7 3 2 Polyalthia longifolia 0.194 7.88 0.23 131.2 2 34.12 3 Pongamia pinnata 0.189 5.88 0.16 101.7 0 26.44 4 Psidium guajava 0.192 5.99 0.17 116.0 5 30.17 5 Punica granatum 0.142 4.19 0.07 50.97 13.25 6 Roystonea regia 0.317 8.46 0.67 400.4 7 104.1 2
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 01 | Jan -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 600 7 Santalum album 0.17 4.49 0.10 91.79 23.86 8 Sesbania sesban 0.148 4.25 0.07 31.50 8.19 9 Spathodea campanul ata 0.295 10.50 0.72 237.0 0 61.62 1 0 Swietenia mahagoni 0.464 15.22 2.57 1695. 76 440.9 0 Average 0.247 7.56 0.56 346.3 0 90.04 Total 2.474 75.64 5.67 3463. 10 900.4 0 Table 3: Shows TB, C, CO2, Tree count, Total CO2 Sr . N o. Scientific name TB (kg/tr ee) C (kg/tr ee) CO2 (kg/tr ee) Tre e cou nt Total CO2 (Tonn es) 1 Pithecello bium dulce 764.3 6 382.1 8 1401. 19 156 218.5 86 2 Polyalthia longifolia 165.3 4 82.67 303.1 0 40 12.12 4 3 Pongamia pinnata 128.1 4 64.07 234.9 1 205 48.15 6 4 Psidium guajava 146.2 2 73.11 268.0 5 156 41.81 5 5 Punica granatum 64.22 32.11 117.7 2 40 4.709 6 Roystonea regia 504.6 0 252.3 0 925.0 0 206 190.5 50 7 Santalum album 115.6 5 57.83 212.0 1 7 1.484 8 Sesbania sesban 39.69 19.85 72.76 6 0.437 9 Spathodea campanul ata 298.6 2 149.3 1 547.4 2 8 4.379 1 0 Swietenia mahagoni 2136. 66 1068. 33 3916. 82 11 43.08 5 Average 436.3 5 218.1 7 799.8 9 83.5 56.53 0 Total 4363. 50 2181. 75 7998. 96 835 565.3 20 Carbon capture and sequestration is a theoretical approach to control and mitigate the contribution of emissions of fossil fuels to global warming, based on capturing carbon dioxide from large point sources such as the fossil fuel power plants. The carbon dioxide might then be stored away from the atmosphere permanently. As urban areas discharge maximum amount of emissions of carbon, tree creates an impact on carbon emissions through changing in climates at micro level, albedo, use of energy, and maintenance of emissions which require to be added with tree storage and capture estimates to improve a more complete evaluation of the role of trees of the urban area on climate change [20]. Graph showing CO2 sequestration The study was conducted in the Aurangabad city to estimate the above ground biomass, below ground biomass, total biomass, carbon dioxide, carbon from selective ten tree species. Swietenia mahagoni has sequestered 3916.81 kg/tree of CO2 which is highest compared to other tree species from the study area. It is due to high DBH and height of the tree. At the same time AGB 1695.76, BGB 440.89, total biomass 2136.65, carbon 1068.32 which is highest in the Swietenia mahagoni which has only 11 tree count. Sesbania sesban sequestered lowest CO2 72.75 kg/tree compared to other trees which is may be due to lowest DBH i.e. 0.148 meters, total biomass sequestered 39.69 kg/tree. Total tree count of the study area is 835. Maximum 206 trees found of Roystonea regia and only 6 trees found of Sesbania sesban from the study area. Total AGB 3463.10, total BGB 900, Total biomass 4363.50, Total carbon 2181.75, total CO2 sequestered is 7998.96kg/tree and total CO2 from all tree species from the study area is 565.32 tonnes. Large healthy trees having the diameter more than 77 cm sequester approximately 90 times more carbon as compared to the small healthy trees species which have the diameter less than 8 cm [19]. Large trees also store nearly 1000 times maximum carbon than smaller trees [20, 19]. 0.0 1000.0 2000.0 3000.0 4000.0 1401.2 303.1234.9268.0117.7 925.0 212.072.8 547.4 3916.8
  • 4. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 01 | Jan -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 601 REGRESSION ANALYSIS To estimate the closeness and relationships various parameters a regression analysis was performed with the help of SPSS 16.0 software. Model Summary Mode l R R Square Adjuste d R Square Std. Error of the Estimate 1 .949a .900 .871 .27519 a. Predictors: (Constant), Height, DBH Coefficientsa Model Unstandardized Coefficients Standardize d Coefficients t Sig.B Std. Error Beta 1 (Constant ) -1.097 .229 - 4.79 1 .00 2 DBH 3.169 2.321 .443 1.36 6 .21 4 Height .116 .072 .522 1.61 0 .15 2 a. Dependent Variable: Volume Where, t = Statistics R= Multiple correlation coefficient; R2 and adjusted R2 = Coefficient determination of variablesB= Regression coefficient Above table shows that strong correlation coefficient between DBH with volume and the height whereas adjusted R2 shows 87 % variability between the Volume with DBH and Height. Above statistical table shows that volume is significant with DBH. As increase in DBH its metabolic and the growth necessities would also increase. 4. CONCLUSION Trees from urban area play crucial roles in reduction of the atmospheric carbon dioxide levels. In the present research work calculation of AGB, BGB, TB, carbon and carbon dioxide sequestration potential rate often tree species was done by nondestructive method. Theodolite instrument was used for height measurement. Wood densities were obtained from the World Agroforestry Centre for the measurement of carbon sequestered by trees. Carbon stock was determined for Pithecellobium dulce, Polyalthia longifolia, Pongamia pinnata, Psidium guajava, Punica granatum, Roystonea regia, Santalum album, Sesbania sesban, Spathodea campanulata, Swietenia mahagoni tree species in and around university campus of Aurangabad city. Results show that Swietenia mahagoni has the better carbon sequestration potential rate which sequestered 3916.81 kg/tree of CO2 whereas Sesbania sesban has the least sequestration rate which sequestered 72.75 kg/tree of CO2 as compared to other species. Total tree count is 835. Total carbon sequestered 2181.75. Total carbon dioxide from all the tree species sequestered 7998.96 kg/tree. Carbon dioxide sequestered by the trees 565.32 tonnes. More field measurements are needed in urban regions to help improve carbon accounting and other functions of urban forest ecosystems. Before applying the approach of urban tree management, quantification of organic carbon in the urban region by nondestructive method will be helpful. REFERENCES [1] United Nations (2015). World Urbanization Prospects: The 2014 Revision. NewYork, NY: United Nations Department of Economic and Social Affairs, Population Division. [2] Nowak, D.J. (1993). Atmospheric carbon reduction by urban trees. Journal of Environmental Management 37 (3), 207-217. [3] Nowak, D.J. (2010). Urban biodiversity and climate change. In: Muller, N., Werner, P., Kelcey, J.G. (Eds.), Urban Biodiversity and Design. Wiley-Blackwell Publishing, Hoboken, NJ, pp. 101-117. [4] McPherson EG (1998). Atmospheric carbon dioxide reduction by Sacramento’s urban forest. J Arboric 24(4):215–223 [5] Jo HK (2002). Impacts of urban greenspace on offsetting carbon emissions for middle Korea. J Environ Manage 64(2):115–126 [6] Nowak DJ, Crane DE (2002). Carbon storage and sequestration by urban trees in the USA. Environ Pollut 116(3):381–389 [7] Escobedo F, Varela S, Zhao M, Wagner JE, Zipperer W (2010) Analyzing the effi cacy of subtropical urban forests in offsetting carbon emissions from cities. Environ Sci Policy 13(5):362–372 [8] Stoffberg GH, van Rooyen MW, van der Linde MJ, Groeneveld HT (2010) Carbon sequestration estimates of indigenous street trees in the City of
  • 5. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 01 | Jan -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 602 Tshwane, South Africa. Urban For Urban Green 9(1):9–14 [9] Zhao M, Escobedo F, Staudhammer C (2010) Spatial patterns of a subtropical, coastal urban forest: implications for land tenure, hurricanes and invasives. Urban For Urban Green. doi: 10.1016/j. ufug.2010.01.008 [10] Abdollahi, K.K., Ning, Z.H., Appeaning, A. (2000). Global Climate Change and the Urban Forest. GCRCC and Franklin Press, Baton Rouge, pp. 31-44. [11] Wilby, R.L., Perry, G.L.W. (2006). Climate change, biodiversity and the urban environment: a critical review based on London UK. Progress in Physical Geography 30 (1), 73-98. [12] Gill, S.E., Handley, J.F., Ennos, A.R., Pauleit, S. (2007). Adapting cities for climate change: the role of the green infrastructure. Built Environment 33 (1), 115-133. [13] EPA (2010). Environmental co-benefits of sequestration practices. Internet file http;//www. epa.gov/sequestration/fag.html. [14] Lal, R., Augustine, B. (2012). Carbon Sequestration in Urban Ecosystems. Springer, New York, p. 385. [15] Nowak, D.J., 1994. Atmospheric carbon dioxide reduction by Chicago’s urban forest. In: McPherson, E.G., Nowak, D.J., Rowntree, R.A. (Eds.), Chicago’s Urban Forest Ecosystem: Results of the Chicago Urban Forest Climate Project. USDA Forest Service General Technical Report NE-186, Radnor, PA, pp. 83–94. [16] Potadar Vishnu R, and Satish S Patil. (2016). Carbon Storage and Sequestration by Trees in and Around University Campus of Aurangabad City, Maharashtra. International Journal of Innovative Research in Science, Engineering and Technology Vol. 5, Issue 4, April 2016 ISSN (Online) : 2319-8753 [17] Hangarge L. M., D. K. Kulkarni, V. B. Gaikwad, D. M.Mahajan and NishaChaudhari (2012). Carbon Sequestration potential of tree species in SomjaichiRai (Sacred grove) at Nandghur village, in Bhor region of Pune District, Maharashtra State, India. Annals of Biological Research, (7): 3426- 3429. [18] Bandana Gupta and Sanjay Sharma (2014). Estimation of Biomass and Carbon Sequestration of Trees in Informally Protected Areas of Rajouri, J&K, India International Research Journal of Environment Sciences ISSN 2319–1414 Vol. 3(6), 56-61, June (2014) Int. Res. J. Environment Sci. [19] K.G. MacDicken, (1997). A Guide to Monitoring Carbon Storage in Forestry and Agro forestry Projects, Winrock International Institute for Agriculture Development, USA, pp. 13-14. [20] A.N. Djomoa, , A., Ibrahimab, J. Saborowskic, , and J. Gravenhorsta, (2010). Allometric equations for biomass estimations in Cameroon and pan moist tropical equations including biomass data from Africa, Forest Ecology and Management, 260, pp 1873-1885.