Carbon Storage in Trees of Urban and Peri-urban Forests of
Agartala, Tripura
Tamal Majumdar1 and Thiru Selvan2* Department of Forestry and Biodiversity, Tripura University, Suryamaninagar, Agartala, Tripura
*Corresponding Author: [email protected]
Abstract-Quantification of total carbon sequestration by urban trees in Agartala, India was done based on generalized
allometric model by estimating above and below ground tree biomass and carbon content. All trees with Girth at Breast
Height (GBH) ⩾10cm were measured in 444 surveyed plots of equal size (20×20m). A total 3470 trees of 111 species, 92
genera and in 45 families were recorded. Total stand basal area 240.76 m2 (13.56m2 ha1), biomass carbon 806.52 Mg (45.42
Mg ha1) and carbon dioxide sequestration 2959.92 Mg (166.66 Mg ha1) were recorded from study area. Out of total
recorded 1613.04 Mg biomass, Above Ground biomass was 1153.05 Mg, Below Ground Biomass was 287.03 Mg and
Litter Biomass 172.95 Mg. In the study area, biomass ranged from 0.0012 Mg/ha to 27.41 Mg/ha and carbon stock from
0.0006 Mg/ha to 13.70 Mg/ha.
Fabaceae accounted for 9.9 % of species and Moraceae 37.58% of the total estimated biomass and 303.1 Mg carbon.
Collectively, top four species (Artocarpus heterophyllus, Mangifera indica, Ficus benghalensis and Gmelina arborea) with 33.17%
individuals contributed 60.13% of total biomass. Tree diameter class 21-30 cm contributed 24.90 Mg/ha biomass
(27.42%). The rate of CO2 fixation per tree was found highest in Alstonia scholaris followed by Albizia saman. Native
(94.33%) and evergreen (85.44%) species showed better performance in biomass and carbon sequestration over
introduced and deciduous. It is evident that biomass and carbon content of a tree related with its diameter and not on
number of trees alone. Diameter of trees has shown strong positive correlation with its total biomass (0.965) and carbon
content (0.963). Urban trees selected with in AMC area for biomass and carbon content estimation will help for future
research purposes as well as town and country planners.
Key Words: Carbon sequestration, Urban Forest, Standing Biomass, Urban Trees, Agartala City.
I. INTRODUCTION
India is the second populous country in the world after China and third biggest greenhouse gas emitter contributing about
5.3% of the total global emissions. During recent decade unprecedented population growth and urbanization has been
observed in India. In between 2001 and 2011, the total population in India increased by 17.64%. From 5161 classified
towns and 384 urban agglomerations in 2001, India’s urban centers grew to 7935 classified towns and 475 urban
agglomerations in 2011, making India the second largest urban system in the world [1]. Cities occupy less than 3% of the
global terrestrial surface, but account for 78% of carbon emissions, 60% of residential water use, and 76% of wood used
for industrial purposes. In 1800, Beijing was only city in the entire world that had more than a million people; 326 such
cities existed 200 years later [2]. Indeed, such rapid has been the pace of growth that in 1900 just 10% of the global
population was living in urban areas which now exceeds 50% and is expected to further rise to 67% in the next 50 years
[3](Grimm et al.2008). With increasing population, vehicles population in India is also increasing at an unprecedented rate
and contributing CO2 content in atmosphere in competitive mode. Recently, growing anxiety about climate change has led
to researchers to quantify the effects of forests on atmospheric carbon dioxide [4], [5], [6], [7], [8], [9].The cause and effect
of global warming is more alarming now than ever. It is observed that increase in global average temperatures is due to
steady increase of CO2 in our atmosphere, i.e. from 280 parts per million (ppm) in 1850 up to 394 ppm in 2012 [10].
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At the 16th Conference of the Parties held in 2010, parties to the UNFCCC agreed that future global warming should be
limited below 2°C relative to the pre-industrial temperature level [11]. Forest cover more than one third of the world’s land
area and constitute the major terrestrial carbon pool [12]. The amount of carbon sequestered and stored in forest varies
greatly based on many factors, including the type of forest, its Net Primary Production (NPP), the age of the forest, and its
overall composition [13]. Carbon storage in forest involves many components including biomass carbon and soil carbon.
As more photosynthesis occurs, more CO2 is converted into biomass, reducing carbon in the atmosphere and sequestering
it in plant tissue above and below ground [14], [15] resulting in growth of different parts [16]. Biomass production in
different forms plays an important role in carbon sequestration in trees. Above Ground Biomass, Below Ground Biomass,
Dead Wood, Litter, and Soil Organic Matter are 5 major carbon pools in any ecosystem [17], [18], [19]. Assessment of
carbon stocks and stock changes in tree biomass are relevant to deal with the United Nation Framework Convention on
Climate Change (UNFCCC) and Kyoto Protocol report [20]. Research estimates shows that India’s forest and tree cover
of 78.29 million ha (23.81 %) is capable of neutralizing 11.25% of India’s total GHG emissions [21].
The role of forested areas in carbon sequestration is conventional and well documented [22] but the potential of trees in
carbon sequestration from urban, peri-urban and trees outside of forest areas is either ignored or not documented
properly. Studies showed that urban forests can be an important source of carbon sinks, although there is a general lack of
information on urban tree and its role in carbon storage and sequestration. Likewise, very little is known about release of
CO2 into the atmosphere from combustion of fuels used to power equipment and vehicles. Once dead, trees release most
of the CO2 they accumulated into their body through decomposition. The rate of release of CO2 into atmosphere depends
on how the wood is utilized.
Trees in urban area, Trees Outside of Forest (TOF) or trees in peri-urban area also store and sequester carbon as biomass
from the atmospheric carbon dioxide during the process of photosynthesis and 50% of trees standing biomass is
considered as carbon [23]. Moreover, as carbon has been introduced as a commodity in the world of climate change,
measurement of carbon stock and carbon sequestration has already occupied its position and market and biomass
estimation has gained massive momentum. In India, very limited successful studies have shown exclusively carbon
estimation, sequestration and its potential for urban forest and trees available in various Universities Campuses. Attempts
have been made to study the potential of trees in carbon sequestration from urban areas in Pune, India [24] and
Aurangabad, Maharashtra, India [16]. These studies highlighted the need on non-forested but tree dominated areas such as
University campus including avenues role in carbon sequestration as these areas comes under cities. None of the studies
have been carried out to assess the urban forest inventory and to estimate the quantity of tree biomass, carbon stored and
sequestered in urban trees. The present study assesses the distribution pattern of carbon in different tree size classes and
will bridge the gaps of carbon storage. This will disseminate the idea of carbon trading in world market by sequestering
carbon if documentation is done perfectly.
II. MATERIALS AND METHODS
A. Study Area Tripura is the third smallest state of India having an area of 10,491.60 km2 bordered by Bangladesh to the north, south and
west and two Indian states namely Assam and Mizoram to the east. Agartala is the capital, hub of administrative and all
economic activities of Tripura. Agartala Municipal Corporation (AMC), the study area (Fig1 &2) is 76.504 km2 in size
which is 0.72 % of the state’s geographical area and lies in between Latitudes 23°45' and 23°55' N and 91°15' and 91°20'
E Longitudes and 12.8 m above mean sea level. As per 2011 census, Tripura state population was 36,73,917 (350
density/km2) which is 0.30 % of the country’s population. The population of Agartala city was 4,00,004 [1] which is 10.88
% of total state population and 41.60 % of total urban population of the state. Out of 20 urban local bodies in Tripura,
AMC is the only largest and biggest urban local body. The administrative area of Agartala city has increased about 30.01 %
from 58 .84 sq km in 2001 to 76.504 sq Km in 2014 [25].
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Though Tripura is a hilly state but AMC area has a plain landscape and enjoy tropical monsoon climate. Climatically one
calendar year could be divided into three distinct season namely winter from November to February, summer from March
to May and rainy season from June to September. In Tripura rainfall is mostly received in June to September from south –
west monsoon. Average rainfall of Agartala city is 220 cm, average temperature varies from 4° to 37.6° C and average
humidity varies from 78% to 90%. Howrah is longest perennial river of Tripura and passes through Agartala city. The soil
is mostly red loamy and sandy soil. The AMC area is vulnerable to flood during rainy season. It is also vulnerable to
earthquake as it is located in seismic zone five (V).
Fig.1.Map of AMC with coordinates. Fig.2.Map of AMC showing wards &
zones
B. Field Survey
The area of AMC (76.504 km2) was divided into 500 X 500 m2 grid by superimposing map of AMC on Google map with
the help of Tripura Space Application Research Centre (TSARC). A total of 365 full grids and 26 part grids fall within
AMC area. 10 % of full grids (37) were randomly selected using excel generation random number. Partial grids were
discarded. Within one grid 12 plot of 20 m x 20 m (0.04 ha) were identified from south corner of sample plot to north at
50 m interval of each plot for detailed survey. A guide map of AMC (1: 20,000 scale) prepared by Survey of India (SI) was
used to identify the sample plot location in the field. Cadastral map of AMC was also used to facilitate in field survey. For
study, individual trees ≥10 cm in girth at breast height (1.37m) were enumerated. Shrubs and herbs were not recorded.
Height and girth of trees were recorded using altimeter and measuring tape, respectively while crown, crown light exposure
and species level identification of trees were done in the field on visual observation. Longitude and Latitude of each grid
and plot were recorded using Global Positioning System (GPS-Gramin) in pre designed field survey format. Enumerations
of all trees with in 444 sample plots were done from May, 2015 to December, 2016 at various intervals. Local names of
trees were collected in consultation with local people, help from forest department officials and using Flora of Tripura
[26]. Doubtful sample were collected and stored in herbarium for identification by taxonomists. Girth at Breast Height
(GBH) of sampled trees was converted into Diameter (D) by dividing the value of pi (π).
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Average Diameter at Breast Height (DBH) of all trees were calculated and arranged in 10 cm interval of 6 (six) diameter
classes. Similarly, height of all measured tree species were arranged in 3 m interval of 6 (six) height classes. Height and
width of crown (N-S & E-W) of each tree were also measured in field to measure tree canopy cover. Crown light exposure
of all trees was also measured by visual observation.
As tree biomass is an important parameter for carbon cycle [27], attempts were made to measure the tree biomass, carbon
storage and carbon sequestration of all trees (≥ 10 cm GBH) with in study area. Indirect or nondestructive method for
biomass estimation was used as it is based on equations using measurable parameters viz girth, height and density. The use
of girth at breast height alone for above ground biomass estimation is common to many studies that showed that diameter
at breast height (DBH) is one of the universally accepted predictor because it shows a high correlation with all tree
biomass components and easy to obtain accurately from field though it is time consuming and costly method in
comparison to satellite image or GIS based survey [5], [7]. Most of the research work revealed that AGB is strongly
correlated with tree diameter [28], [29]. Also, it is accepted that simple model with only diameter as input is a good
indicator of AGB [30]. Hence, in the present study allometric equation using tree diameter to estimate AGB was
considered. Average DBH of all species were worked out for mean biomass calculation. Mean biomass was multiplied by
number of individuals of that particular species to get the total biomass of said species (Table 2). For all statistical
calculation and computation of primary data Past3 software and excel sheet were used, respectively. Though height of all
surveyed trees were measured but its use was not reflected directly in this study. The purpose of measuring tree height was
to establish if there was a relationship between diameter at breast height and tree height.
Above Ground Biomass (AGB) - model developed by [31], Below Ground Biomass (BGB) - model developed by [32],
Litter Biomass-15% of aboveground biomass [33] and Total Biomass (TB) of all trees species were calculated using
following equation and methods.
i) Y= Exp [- 0.37+0.333 lnD +0.933 [ln(D)]2- 0.122 [ln(D)]3
where Y = Above Ground Biomass(AGB) (Kg)
D = DBH (cm) and -0.37, 0.333, 0.933 & -0.122 are constants.
ln = Natural logarithm
ii) Y= Exp [-1.0587 + 0.8836 × ln (AGB)]
Where Y = Below Ground Biomass (BGB) (Kg)
AGB = above ground biomass and -1.0587, 0.8836 is constants.
ln = Natural logarithm.
iii) Litter Biomass (LB) = 15 % of AGB
iv) Total Biomass (TB) = Sum of above ground + Below ground + Litter Biomass
v) Carbon estimation = 50% of plant biomass [34]
vi) CO2 sequestration= Carbon value x 3.67.The total carbon stock is then converted to tons of CO2 equivalent by
multiplying 44/12 or 3.67 [35].
III. RESULTS
A total 111 species belonging to 92 genera and 45 families with 3470 individuals were recorded from surveyed area of
17.76 ha [Table 1]. Stem density, average diameter and height of tree were recorded as 195.38 stem ha1, 22.9 cm and 7.9 m,
respectively. Stand basal area was recorded as 240.76 m2 (13.56m2ha1). Mangifera indica; Artocarpus heterophyllus; Gmelina
arborea; Tectona grandis; Areca catechu; Azadirachta indica and Psidium gujava are 7 species dominated more than 50% of the
study area with 442 (12.73%); 434(12.50%); 242(6.97%); 201(5.79%); 186(5.36%); 141(4.06%) and 126(3.63%) individuals,
respectively. 18 species with single tree (0.02%)were found in the study area.
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In total 240.76 m2 (13.56 m2 ha-1) basal area was recorded from the study area. Artocarpus heterophyllus shows highest basal
area 78.07 m2 (32.42%) followed by Mangifera indica (43.21m2; 17.94%) and Ficus benghalensis (18.83 m2; 7.82%). Lowest
basal area was observed in Jatropha curcas (0.002 m2) followed by Lawsonia inermis (0.0023 m2) and Araucaria heretophylla
(0.0035m2).
Amongst 45 recorded families, Fabaceae represented highest species (11 nos, 9.90 %) followed by Moraceae (7nos,
6.30%), Apocynaceae, Rutaceae and Myrtaceae with 6 species each (5.41%), Arecaceae, Euphorbiaceae, Malvaceae, with 5
species each (4.50%), Mimosaceae and Rubiaceae with 4 species each (3.60%) and Anacardiaceae, Lauraceae, Lythraceae,
Combretaceae and Meliaceae with 3 species each (2.70%); and 7 least dominated families with 2 species each and another
23 families with one species each. Top 5 families contributing 57.76% of total trees was Anacardiaceae which contributed
442 (12.73%) of total 3470 trees followed by Verbenaceae 434 (12.51%), Moraceae 424 (12.22%), Arecaceae 421 (12.13%)
and Meliaceae 277 (7.98%). Araucariaceae, Asteraceae, Bignoniaceae, Calophyllaceae, Nyctaginaceae, and Solanaceae are
least contributing families in terms of number of trees in the survey area (Table 1; Fig- 3 & 4).
The total biomass recorded was 1613.04 Mg (90.82 Mg ha-1 contributed by AGB- 1153.06 Mg; BGB- 287.03 and LB-
172.95Mg with mean biomass of 0.46 Mg per tree. Family Moraceae got the highest biomass 606.21 Mg (37.58%) followed
by Anacardiaceae and Verbenaceae with 288.12 Mg (17.86%) and 153.17 Mg (9.45%) biomass, respectively. Nyctaginaceae
and Araucariaceae family showed very less biomass 0.05 and 0.04 Mg respectively in the study area.
Fig.3.Top 15 families with no of species
Fig.4. Top 15 families with no of Trees
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Total standing biomass 1326 Mg (74.66 Mg ha1) (AGB- 1153.05 Mg and LB-172.95 Mg) was recorded in study area. Most
of the biomass accumulated in the aboveground compartment of the plant i.e. 82.2%. Artocarpus heterophyllus the second
highest (434 out of 3470 trees) in numbers in study area showed highest biomass (486.95 Mg; 30.18 %) and Mangifera indica
the dominating trees species (442) showed second highest (285.13 Mg; 17.68%) biomass. Collectively, top four species
namely Artocarpus heterophyllus, Mangifera indica, Ficus benghalensis and Gmelina arborea with 1151 (33.17%) individuals
contributed 969.96 Mg biomass (54.61 Mg/ha) which is 60.13% of total biomass. Least biomass was recorded by Jatropha
curcas (0.0219 Mg) followed by Lawsonia inermis (0.0244Mg) and Araucaria heterophylla (0.0358Mg) (Table 2).
Out of six diameter classes, maximum biomass 525.05 Mg (32.55%) was measured from 468 individuals of 41-50 cm class
followed by 442.28 Mg (27.42%) and 332.10 Mg (20.59%) from 1279 and 520 individuals of 21-30 cm and 31-40 cm,
respectively. Least biomass 17.46 Mg (1.08%) was measured from 268 individuals of < 10 cm diameter class (Fig. 5).
Larger trees altogether (> 41 cm) stored 672.6 Mg (41.69%) biomass. Big size trees (>41 cm DBH) store 38 times more
biomass than small size trees (<10 cm DBH)
Among four zones, central zone showed least numbers of trees (654 out of 3470, 18.84%) as well as biomass and carbon
content. Southern zone (1074, 30.95%) is much better followed by eastern zone (897, 25.85%) in terms of tree individuals,
biomass and carbon content.
0.00100.00200.00300.00400.00500.00600.00
< 10cm
11-20cm
21-30cm
31-40cm
41-50cm
>51 cmBio
mas
s(M
g)
Diameter classes
Fig. 5. Diameter Class wise total biomass.
From 85 evergreen species (2775 trees) and 26 deciduous species (695 trees) 1378.23 Mg (85.44%) and 234.81 Mg
(14.56%) biomass was measured (Fig.6).
Fig.6. Phenology wise total biomass.
Moreover, highest biomass 1521.58 Mg (94.33%) was recorded from 3063 native trees followed by 91.46 Mg (5.67%) from
407 individuals of introduced origin (Fig.7).
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Fig.7. Origin wise total biomass.
Artocarpus heterophyllus stored highest 243.47 Mg (30.18%) carbon followed by Mangifera indica (142.56 Mg, 17.67%) and
Ficus benghalensis (54.27 Mg, 6.72%), respectively. Jatropha curcas stored least carbon 0.011Mg (0.001%) followed by Lawsonia
inermis (0.012 Mg, 0.0014%) and Araucaria heterophylla (0.018 Mg, 0.0022%). Artocarpus heterophyllus sequestered highest CO2
893.55 Mg (30.18%) followed by Mangifera indica (523.21 Mg, 17.67%) and Ficus benghalensis (199.20Mg, 6.72%). Jatropha
curcas sequestered least CO2 0.040 Mg (0.001%) followed by Lawsonia inermis 0.045Mg and Araucaria heterophylla 0.066 Mg.
Family Moraceae stored highest carbon (303.10 Mg) followed by Anacardiaceae (144.06Mg) and Verbenaceae (76.58Mg).
Araucariaceae (0.065Mg) and Nyctaginaceae (0.089Mg) are two families to sequester least CO2. Native species store
highest 760.79 Mg carbon (94.32%) and sequestered 2792.11 Mg CO2 than introduced species 45.72 Mg carbon (5.66%)
and 167.82 Mg CO2, respectively.
IV. DISCUSSION
In the study area tree density (195.38 trees ha-1) is greater than those of urban forests (111.9 trees ha-1 of Oakland,
California, [36] Modesto, California (61 trees ha-1, [37]); ten USA cities [7]; Sacramento, USA (73 trees ha-1, [28]) and
Beijing, China (79 trees ha-1, [29]). However, tree density recorded in this study is lesser than in urban forests of three USA
cities (563 ± 77 ha-1, range 332-674 ha-1 [30].
High density of trees in study area may be due to more number of small diameter fruit and flower trees (< 20 cm DBH;
1148 trees, 33%) within small size of land holding of urban area. In urban area due to small quantum of land holding with
the city dwellers, they prefer to plant fruit and flowering species to the species of trees with timber value. It is found that
67% of trees are ≥ 21 cm DBH and found more when compared to other urban forests of the world, such as Oakland,
California (39%; Nowak, 1991); Shorewood, Wisconsin (33%, [39]; Los Angeles of USA (60%; [40] and Chennai, Tamil
Nadu, India (27%, [41]).
The mean biomass (AGB, BGB and LB) stored in a tree in the surveyed area was 464.84 kg. It is more than that of Yang
et al., 2005. They reported 162.6 kg mean biomass from urban areas of China and slightly less than 477.76 Kg of urban
tree biomass in Pachaiyappa’s College, Chennai, India. Mean carbon stored in an individual tree in the study area was
232.42 kg which is slightly lower than urban tree biomass 238.88 Kg recorded in Pachaiyappa’s College, Chennai, India.
The carbon storage 45.41Mg ha-1 in present study area is more than Pachaiyappa’s College, Chennai (43.09Mg ha1, [41]),
Germany (11 Mg ha-1, [42]); but less than that of Pune, India (54.87Mg ha1, [43]), Beijing, China (45.39 Mg ha-1, [29]). Less
C storage in study area could be due to the presence of large number of small trees (≤ 20 cm DBH; 1148 trees, 33%) and
absence of large trees (>51 cm DBH, 55 trees, 1.5%). Moreover, quantity of biomass /carbon storage by a tree also
depends upon the density, tree cover, stand basal area and diameter of tree [44]. The present study as compared to some
institutional areas of US cities stored more carbon (41.0 Mg C ha-1, [30]; 12.9 Mg ha-1, [36]) However, institutional urban
forests in Pune city stored more carbon (87.33 Mg ha-1, [43]) than the present study.
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It is observed that most of the biomass accumulated in the aboveground compartment of the tree, i.e. 82.20% biomass
than the below ground. The findings are almost similar to many studies giving percentages of aboveground biomass
81.9% as reported by [45], and 81%, [46].
The average DBH of 111 tree species was measured as 21.92 cm which indicated that trees are young and have the
capacity to sequester more carbon in near future from the atmosphere. The observed DBH classes showed strong
correlation with Biomass as total biomass is a function of DBH of trees (r2 = 0.954). Above data indicates that with
increase in diameter of trees, biomass and carbon storage capacity increases and trees also sequester more carbon by
removing more CO2 from the atmosphere (Table 2). Jatropha curcas and Bougainvillea glabra are two species that has least
biomass 0.014Mg and 0.031Mg, respectively due to their single tree with less diameter.
Large ( ≥ 41 cm) size trees stored approximately 38 times more C (336.10Mg) when compared to low (< 10cm) diameter
class (8.73Mg). In low diameter size class ( < 30 cm) though number of trees (2427, 69.94%) is much more than big
diameter class (> 31 cm; 1043 trees, 30.06%) but total biomass 608.34 Mg (37.71%) in small sizes trees is much less than
biomass of big sizes trees (1004.7Mg, 62.29%). The said result is also supported by [47]. It is evident that total biomass or
carbon content of study area does not depend on numbers of trees alone but on diameter and basal area of trees also.
Number of evergreen tree species and its contribution towards total carbon storage is more (689.11 Mg; 85.44%) than
deciduous species (117.40 Mg; 14.56%). The rate of carbon storage per evergreen tree (0.24Mg) is higher than per
deciduous (0.16Mg) tree. Evergreen trees were found in higher proportions in Ludhiana (61.20%) and Pathankot
(50.82%) city of Punjab, India [48]. Native trees accumulated much more carbon (760.79 Mg; 94.33%) compared to
introduced trees (45.71Mg; 5.67%).
It is also found that native tree species also dominated in Bathinda (81.06%) and Ludhiana (71.94%) cities as well. Carbon
stored in a tree ranged from as low of 0.009 Mg C / tree to as high as 1.64 Mg C / tree. Moreover, evergreen trees
sequester 2529.03 Mg CO2 (85.44%) than the deciduous 430.85 Mg (14.55%). As far as carbon storage and CO2
sequestration is concerned in urban and peri urban area one should select native and evergreen species due to its more
foliage duration for photosynthesis and CO2 fixation and more litter biomass production than introduced and deciduous
species. More rain fall followed by moderate high temperature also helps in growth of trees with in study. City dwellers
preferred evergreen trees due to constant foliage throughout the year and less litter falls compared to deciduous trees. For
beautification also dwellers prefer vigorous trees not bare looking trees during winter months. Evergreen trees also are
considered best for air pollution removal due to all round the year foliage [9]. The carbon sequestration per year in the
study area was 16134 kg. Therefore, trees of surveyed area are sequestering 16.134 ton of carbon per year which is very
low than Pune city [49].
V. CONCLUSION
This paper shows the process of biomass, carbon and carbon sequestration measurement through the use of allometric
equations using tree measurements. Urban trees are most susceptible for urbanization as they are the first victims for
widening of roads, construction of buildings, maintenance of utility services like electric and telephone lines. Biomass and
carbon allocation in all the species are in the order of above ground, below ground and litter. All the tree species have
good potential to accumulate huge biomass and contribute for environment amelioration. We should not ignore the non-
tangible services of urban trees in carbon storage and carbon sequestration though the quantity of urban trees is limited as
compared to natural forest. To enhance more diversity in urban area varieties of native and evergreen trees should be
planted. The above ground portion of tree biomass shares the highest amount biomass as well as carbon followed by
below portion and least by litter. Urban trees are under threat of succession rule. These species, genera and families
including carbon data will provides the base line data of the Agartala city for future research works. In this study
nondestructive method was used for biomass quantification but result from destructive method and satellite image data
should be used to validate the result. More studies on urban forest will accelerate the concept of carbon trading.
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ACKNOWLEDGEMENTS
We are thankful to the Director and scientists of Tripura Space Application Centre, Agartala for their time to time
cooperation. We are also thankful to the officials of Agartala Municipal Corporation for their help in this study.
REFERENCES
[1] Census, 2011 [Online]. Available: www.censusindia.gov.in/2011
[2] Brown, L. R. 2001. Eco-Economy: Building an Economy for the Earth. Norton, New York. 332pp.
[3] Grimm, N. B., S. H. Faeth, N. E. Golubiewski, C. L. Redman, J. Wu, X. Bai and J. M. Briggs. 2008. Global change and the ecology
of cities. Science 319(5864): 756-760.
[4] Nowak DJ 1994a. Urban Forest structure: The state of Chicago’s urban forest. In: McPherson EG, Nowak DJ and Rowntree RA,
(eds.) Chicago's urban forest ecosystem: Results of the Chicago Urban Forest Climate Project. General Technical Report, NE– 186. U.S.
Department of Agriculture, Forest Service, Radnor, PA. p. 3–18.
[5] McPherson EG and Simpson JR 1999 Carbon dioxide reduction through urban forestry: guidelines for professional and volunteer tree
planters. General Technical Report PSW–171. USDA Forest Service, Pacific Southwest Research Station, Albany, USA. 237 pp.
[6] Jo, H., 2002. Impacts of urban greenspace on offsetting carbon emissions for middle Korea. Journal of Environmental Management 64:
115-126.
[7] Nowak, D. J. and Crane, D. E. 2002. Carbon storage and sequestration by urban trees in the USA. Environmental Pollution 116:
381-389.
[8] Pataki, D., Alig, R., Fung, A., Golubiewski, N., Kennedy, C., McPherson, G., Nowak, D., Pouyat, R. and Lankao, P., 2006.
Urban ecosystems and the North American carbon cycle. Global Change Biology 12: 1-11.
[9] Escobedo, F., Kroeger, T. and Wagner, J., 2011. Urban forests and pollution mitigation: analyzing ecosystem services and disservices.
Environ. Pollut. 159: 2078–2087.
[10] NOAA, 2012. National Oceanic and Atmospheric Administration www.esrl.noaa.gov/gmd/ccgg/trends/
[11] UNFCCC, 2011. Status of Ratification [Online]. Available: http://unfccc.int/k
oto_protocol/background.status_of_ratification/items/2613.php
[12] Robertz, P and Sune, I 1999. Effects of long term CO2 enrichment and nutrient availability in Norway spruce. II Foliar chemistry, Trees
14: 17-27.
[13] Millard P., Sommerkorn M. and Grelet G. 2007. Environmental Change and Carbon Limitation in Trees: A Biochemical,
Ecophysiological and Ecosystem Appraisal. New Phytologist 175(1): 11-28.
[14] Gorte, R.W. 2009. Carbon Sequestration in Forests. US of Library of Congress, Congressional Research Service. CRS Report for
Congress. Prepared for Members and Committees of Congress. 23p.
[15] IPCC 2003. Penman J., Gytarsky M., Hiraishi T., Krug, T., Kruger D., Pipatti R., Buendia L., Miwa K., Ngara T., Tanabe K.,
and Wagner F (Eds). Good Practice Guidance for Land Use, land- Use Change and Forestry IPCC/IGES, Hayama, Japan.
[16] Chavan B.L and Rasal G.B 2010 Sequestered standing carbon stock in selective tree species grown in University campus at Aurangabad,
Maharashtra, India. International Journal of Engineering Science and Technology 2(7): 3003-3007.
[17] Food and Agriculture Organization (FAO), 2005. Global Forest Resources Assessment 2005: “Progress towards sustainable forest
management”. FAO Forestry Paper 147. United Nations Food and Agricultural Organization. Rome, Italy. (www.fao.org)
[18] IPCC 2001 Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the
Intergovernmental Panel on Climate Change [Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der Linden, P.J., Dai, X., Maskell,
K. & Johnson, C.A. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 881pp.
[19] IPCC 2006. Forest lands. IPCC Guidelines for National Greenhouse Gas Inventories. Institute for Global Environmental Strategies
(IGES): Hayama, Japan. 4: 83. 2006.
[20] Alamgir, M. and Al-Amin, M. 2007. Organic carbon storage in trees within different Geopositions of Chittagong (South) forest division,
Bangladesh. Journal of Forestry Research, 18(3): 174−180
[21] Kishwan, J., Pandey, R. and Dadhwal, VK. 2009. India’s Forest and Tree Cover: Contribution as a Carbon Sink. BL – 23.
Technical Publication of ICFRE, Dehradun. 130:1-12.
IAETSD JOURNAL FOR ADVANCED RESEARCH IN APPLIED SCIENCES
VOLUME 5, ISSUE 2, FEB/2018
ISSN NO: 2394-8442
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[22] Tiwari A.K, and Singh J.S., 1987 Analysis of Forest Land Use and Vegetation in a part of [52] Central Himalaya, Using Aerial
photographs. Enviro Conserv. 14: 233-244.
[23] Ravindranath N.H., Somashekhar B.S. and Gadgil M. 1997 Carbon flows in Indian forests. Climate Change, 35(3): 297–320.
[24] Patwardhan. A. and Warran. A, 2005, Carbon sequestration potential in and around Pune city; RANWA, C-26/1; Ketan Heights,
Kothrud, Pune, 411038, India.
[25] Govt. of Tripura, 2013. Notification regarding increase of AMC area vide No.F.2(2) UDD/DUD/ 2013/6308-17 Dt. 10th Oct,
2013.
[26] Deb, D B 1981-1983 The Flora of Tripura State. Vol. I & II. Today &Tomorrow Printers & Publishers, New Delhi.
[27] Pragasan, A. and Karthick, L. 2013 Carbon stock sequestered by tree plantations in university campus at Coimbatore, India.
International Journal of Environmental Sciences 3: 1700-1710.
[28] Birdsey RA and Heath LS 1995. Carbon changes in U.S. Forests. In: Joyce LA, editor. Productivity of America’s Forests and Climate
change: USDA Forest Service, General Technical Report RM-271.
[29] Yang J, McBride J, Zhou J. and Sun Z 2005 The urban forest in Beijing and its role in air pollution reduction. Urban For Urban
Green 3(2): 65–78.
[30] Nowak DJ 1994b. Atmospheric carbon dioxide reduction by Chicago’s urban forest. In: McPherson EG, Nowak DJ, Rowntree RA,
(eds.) Chicago’s Urban Forest Ecosystem: Results of the Chicago Urban Forest Climate Project. General Technical Report, NE–186, US
Department of Agriculture, Forest Service, Radnor, PA;, p. 83–94.
[31] Chambers JQ, dos Santos J, Ribeiro RJ and Higuchi N 2001. Tree damage, allometric relationships, and aboveground net primary
production in central Amazon forest. For. Ecol. Manage 152:73–84.
[32] Cairns MAS, Brown S, Helmer EH and Baumgardner GA. 1997 Root biomass allocation in the world’s upland forest. Oecologia
111:1–11.
[33] Achard F, Eva HD, Stibig HJ, Mayaux P, Gallego J, Richards T and Malingreau JP, 2002. Determination of deforestation rates of
the world’s human tropical forests. Science 297, 999–1002
[34] Pearson, T.R.H., S., Brown, and N.H. Ravindranath 2005 Integrating carbon benefits estimates into GEF Projects UNDP, GEF
Capacity Development and Adaptation Group Guidelines. 1-56. 2005.
[35] Pearson, T. R., Brown, S. L. and Birdsey, R. A. 2007. Measurement guidelines for the sequestration of forest carbon. Northern research
Station, Department of Agriculture, Washington, D.C, pp. 6-15.
[36] Nowak DJ 1993 Historical vegetation change in Oakland and its implications for urban forest management. J Arboric 19: 313–19.
[37] McPherson EG, Simpson JR, Peper PJ and Xiao Q 1999 Benefit–Cost Analysis of Modesto’s Municipal Urban Forest. J Arboric 25:
235–248.
[38] Nowak DJ 1991 Urban forest development and structure: analysis of Oakland, California. Ph.D. Dissertation. University of California,
Berkeley. 1991.
[39] Dorney JR, Guntenspergen GR, Keough JR and Stearns F 1984 Composition and structure of an urban woody plant community. Urban
Ecol 8: 69– 90.
[40] Nowak DJ, Hoehn RE, Crane DE, Weller R. and Davila A. 2011. Assessing Urban Forest Effects and Values: Los Angeles’
Urban Forest. Resource Bulletin NRS–47.United States Department of Agriculture. USDA Forest Service, Northern Research Station,
USA. 1-35p.
[41] Pachaiyappan, P. and D. Ushalaya R. 2013 A study on two important environmental services of urban trees to disseminate the economic
importance of trees to student community. Journal of Biosciences 1(6): 290-296.
[42] Strohbach MW and Haase D 2012 Above–ground carbon storage by urban trees of Leipig, Germany: Analysis of patterns in a
European city. Landscape and Urban Planning 104: 95–104.
[43] Waran A. 2001. Carbon sequestration potential of trees in and around Pune city. Master’s thesis, University of Pune, India. 2001.
[44] Udayakumar, M., M. Ayyanar and T. Sekar. 2011. Angiosperms, Pachaiyappa’s College, Chennai, Tamil Nadu, India. Check List
7(1): 37-48 .
[45] Nascimento EM and Laurance WF 2002 Total aboveground biomass in central Amazonian rainforests: a landscape scale study. For
Ecol Manag 168: 311–321.
[46] Henry, M., Tittonell, P., Manlay, R.J., Bernoux, M., Albrecht, A. & Vanlauwe, B. 2009. Biodiversity, carbon stocks and
sequestration potential in aboveground biomass in smallholder farming systems of western Kenya. Agriculture, Ecosystems & Environment,
129: 238–252.
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[47] Baishya, R, S. K. Barik, and K. Upadhya 2009. Distribution pattern of aboveground biomass in natural and plantation forests of
humid tropics in northeast India. Tropical Ecology 50(2): 295-304.
[48] Bhardwaj, B M. 2015. Diversity and Performance Evaluation of Landscape Trees in Punjab. PhD Thesis.
[49] Waran A and Patwardhan A, 2001. Urban carbon burden of Pune City : A case study from India. Masters thesis submitted to Univ.
of Pune (Unpubl.) 2001.
TABLE I
LIST OF TREES RECORDED IN AGARTALA URBAN AREA
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TABLE II
LIST OF SPECIES SHOWING THE ABOVE GROUND BIOMASS (AGB), BELOW GROUND BIOMASS (BGB),
LITTER BIOMASS (LB), TOTAL BIOMASS, CARBON STORAGE AND CARBON SEQUESTERED IN
AGARTALA MUNICIPAL AREA.
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