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CHAPTER-IV

MATERIALS AND METHODOLOGY

Estimates of carbon stock and sequestration in the urban areas were based

on our knowledge of the urban planted areas resource from the initial. Carbon

sequestered and stored in residential gardens was also included in the urban carbon

stock.

4.1 Study Area

Aurangabad is also known as 'city of gates', as there are as many as 52

gates scattered across the city (Gazeetter, 1977).Aurangabad city has witnessed

continuous growth in the past few years. It is an attraction as touristsdue to

embracing heritage monuments of Ajanta, Ellora, Daulatabad and Bibi-Ka-

Maqbara and other historical and religious places of National importance

(Gazeetter, 1972; MPCB,2000;ESRAM, 2010).The city’s popularity is well known

to the international tourists.It has good infrastructure, ranging from low budgeted

to high five-star hotels. The city has superb road, air and train connectivity

(MPCB, 2002). Aurangabad is an industrialized city with 5 established

Maharashtra Industrial DevelopmentCorporation (MIDC) industrial estates at

Waluj, Paithan, Chikalthana, Chittegaon and Shendre (MPCB, 2000; 2002).

4.1.1 Geography

Aurangabad district is mainly situated in vicinity of Godavari River and

some part of North West lies in Tapi river belt (Gazeetter, 2007; MPCB, 2000).

Aurangabad city is situated on the banks of the River Kham a tributary of the

Godavari River. The entire city is situated at the latitude of 19053

’50

’’ N and

longitude of 75022

’46

’’ E. It is located 512 meters above sea level. Aurangabad sits

in a strategic position on the Decaan Plateau. The city is surrounded by hills of the

Vindhya Ranges and the River Kham passes through it. The city stands in the

Dudhana valley between Lakenvara range on the north and Satara hills on the

south (ESRAM, 2009; 2010). Aurangabad has total about 10,107km2

geographic

areas. The total land portion under forest cover is 557 km2which is only 7.6% area

of total land area of Aurangabad (SFR, 2009). The total trees under garden area of

Aurangabad city was 21,434 (ESRAM 2008; 2009; 2010; Chavan and Rasal,

2010).

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4.1.2 Geology and soil

The geological formations of the city are characterized by the Deccan

traps Upper Cretaceous to Lower Eocene. The granite rocks have given rise to

red as well as black cotton soils. Major part of the city has deep black soil derived

from the trap rock. Certain variations occur due to exposure and protection (GSI,

2008; http://cultural.maharashtra.gov.in.) A mixture of laterite and black soil, for

example, is encountered in the eastern parts together with sandy soil along river

banks. Most of the hill tops are bare or covered by coarse gravel while the low

lying area accumulates clay and loam (ESRAM, 08-09; 09-10).

4.1.3 Climate

The weather, in general, can be said to be dry and moderately extreme. The

average day temperature ranges from 27.70C to 38.0

0C while it falls from 26.9

0C to

20.00C during night. Relative humidity is extremely low for major part of the year

between 30% to 50% while, it is highest 85% during monsoon. The winter season

commences from the middle of November and ends by the end of the January

followed by a dry hot summer from February to middle of June. Summers are in

general full of gusty winds (ESRAM, 2008; 2009; 2010).

4.1.4 Rainfall

The rainy season is considered from middle of June to the end of

September which is followed by a humid period from about the end of September

to the middle of November. The normal average rainfall is about 90 cm but it is

rather variables from year to year. Rainfall in city varies between 6.5 mm to 334

mm per month. Average rainfall is 725 mm. The major amount of South West

Monsoon precipitation is received on the West Coast of India due to the Sahyadris

and only a small amount escapes through high hills, which is received by the

Deccan Plateau (ESRAM, 2008; 2009; 2010).

4.1.5 Cropping pattern

The major agricultural crops are Cotton, Oil seeds, Bajra, Jowar,

Groundnut, Wheat, Safflower and irrigated crops like Sugarcane which is one of

the important irrigated crops. The other irrigated crops like Grapes, Bananas,

Sweet Limes and Oranges etc are also grown in the soil of the Aurangabad. In the

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soil of Aurangabad variety of vegetables like Brinjals, Tomatoes, Onions, Potatoes

and Leafy vegetables are grown. The Godavari is the main river in the Marathwada

region (ESRAM, 2008; 2009; 2010). Some part of Aurangabad city having good

fertile land with climate, so this particular Aurangabad city shows ample

biodiversity. Due to the lack of adequate rainfall, vegetation cover shows its

diversified nature.

4.1.6 Flora and fauna

The climate of Aurangabad city is generally hot and dry. It receives low

rainfall, some part of Aurangabad city having good fertile land with climate, so this

particular Aurangabad city shows ample bio-diversity. Due to the lack of adequate

rainfall, vegetation cover shows its diversified nature. Aurangabad district covers

more forest area than the others. There are Teak, Sandalwood, Anjan, Moh,

Tembhurni, Ain and other kinds of trees in these forests. In Aurangabad district,

Gautala is a well known sanctuary, Jayakwadi is also famous for bird sanctuary.

Thorny scrub forests are having major trees like Bor, Babul, Aloe-voera, etc. A

variety of wild animals can be seen in the above said forests like wild boars, Foxes,

Hares etc. Leopards are seen but rarely. There are many monkeys and Baboons in

the Aurangabad city area.

4.1.7 Data on Trees and Gardens in AMC area

Environmentally rich area has been received by Aurangabad Municipal

Corporation. The process of calculation of trees in its area has been started by the

Aurangabad municipal corporation. The task of tree protection and garden

development has been successfully undertaken and completed by Aurangabad

Municipal Corporation. Garden department has developed about 88 gardens on

64.97 hectare of land. In the year 2008-09 total 15000 trees have been planted in

municipal corporation area also in that 1070 trees are planted besides the road, and

new plantation in last three year was more than 35000 (ESRAM, 2009; 2010).

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Table 4.1: Trees present in gardens of Aurangabad city

Zone No. of

gardens

Area

hectare

No. of

trees

No. of tree

per hectare

Total 95 68.37 18367 268.64

A 19 44 11071 251.90

B 17 07.60 1305 171.71

C 01 0.50 125 250

D 21 4.62 693 150

E 11 4.01 556 138.65

F 26 7.64 4617 604.32

(Source: Garden Department, Aurangabad Municipal Corporation; ESRAM, 2009;

2010)

The total 28.47 km2

area of Aurangabad city is selected for the carbon

sequestration study. The total area is divided into ninesectors as per the locations

selected from the toposheet and maps collected from various sources. The area of

these nine sectors is measured with the help of GIS map is shown in fig. 4.1 and

Table 4.1.

Table 4.2: Area of nine sectors of Aurangabad city

Sectors Area in Km2 Area in hectare

1 2.21 221

2 2.23 223

3 3.56 356

4 5.28 528

5 2.44 244

6 1.75 175

7 5.01 501

8 2.32 232

9 3.69 369

Total 28.47 2847

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Figure 4.1: Map and image indicate the location of study sites in Aurangabad city

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4.2 Description of sampling sites

Sector 1: The 1st sector is comprised of 221 hectare of area. It included the areas

like Aurangpura, Shahaganj, New mondha, Harshnagar, Aurangabad municipal

corporation, Lotakaranja, City police chowk, Sarafa road and Ginning factory and

surrounding area. The vegetation here pre-dominantly is comprised of Polyalthia

longifolia, Acacia nilotica, Terminalia catappa, Mangifera indica, Azadirachata

indica, etc.

Sector 2: The 2nd

sector is comprised of 223 hectares of area which included the

areas like Samarth nagar, nirala bazaar, krantichowk, mondhanaka and surrounding

area with heavy traffic areas. The Polyalthia longifolia, Azadirachata indica,

Mangifera indica, Eucalyptus spp. are dominant tree species in this sector.

Sector 3: The 3rd

sector is comprised of 356 hectares of area which included the

areas like Begumpura, Government College, Lake, zillaparishad quarters, collector

office, Bus stand, Bibi-kaMaqbara, Panchakki, Salim Ali lake, Delhi gate, Dr. B.A.

research center and surrounding area. The Polyalthia longifolia, Delonix regia,

Azadirachata indica, Cassia siamea, Terminalia catappa are dominant tree species

in this sector.

Sector 4: The 4th

sector is comprised of 528 hectares of areas which included the

areas like Jaisingpura, Dr. B.A.M. University, Aurangabad, Pahadsingpura, and its

surrounding areas. The university campus is having very reach biodiversity and

number of trees. The major plantation of Mangifera indica, Annona reticulata,

Annona squamosa, Emlica officinalis, and Peltaphorum pterocarpum,

Azadirachata indica are dominant species in this sector.

Sector 5: The 5th

sector is comprised of 244 hectares of areas which included the

area like Commissioner Office, Maulana Azad research center, IPS office, Police

public school, TV center, Jasawantpura, and surrounding area. It is comparative

silent area and dense vegetation observed near as government offices. The

Polyalthia longifolia, Azadirachata indica, Cassia siamea, Delonix regia are

dominant tree species present in this area.

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Sector 6:The 6th

sector is comprised of 175 hectares of areas which included the

areas like CIDCO, Baijipura, Cannaught garden, MGM-JNEC colleges, N-6, N-7,

Jincy, Mondha,Jalna road, etc and its surrounding area. Jalna road is heavy traffic

area while, MGM and JNEC college with dense vegetation. The Polyalthia

longifolia, Azadirachata indica, Tarminalia cattappa, Sesbania sesban are

dominant tree species present in this sector.

Sector 7: The 7th

sector is comprised of 501 hectares. It include areas like as

Shivchchatrapati college, Kamgarchowk, hedgewar hospital, shivajinagar area, and

surrounding area. The Polyalthia longifolia, Azadirachata indica, Eucalyptus

citridora, Milingtonia hortensis are dominant tree species present in this sector.

Sector 8: The 8th

sector is comprised of 232 hectares of areas which

includesGarkheda, Shahanurmiyadarga, Osmanpura, Jawahar colony area and

surrounding areas. The Polyalthia longifolia, Azadirachata indica, Eucalyptus

citridora are dominant tree species present in this sector.

Sector 9: The 9th

sector is comprised of 369 hectares of areas. It includes areas like

as Baba petrol pump, Railway station, Devgiri college, Bansilal nagar, Forest

office, Beed bypass and surrounding areas. The Polyalthia longifolia,

Azadirachata indica, Roystonea regia, Albizia lebbeck are dominant tree species

present in this sector.

4.3 Sampling design

There are four options for sampling design; complete enumeration, simple

random sampling, systematic sampling and stratified random sampling. For carbon

inventory, stratified random sampling generally yields more precise estimates than

the other options (McDicken, 1997b). Stratified random sampling requires

stratification. Dividing the populations into the non overlapping sub-populations.

Each stratum (or subpopulation) can be defined by vegetation type, soil type, or

topography. For carbon inventory, strata may be most logically defined by

estimated total carbon pool weight. Since that largely depends on above-ground

biomass, stratification criteria that reflect biomass are generally most appropriate.

Useful tools for defining strata include satellite images, aerial photographs, and

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maps of vegetation, soils or topography which may be preferred as per availability

(MacDicken, 1997a; Brown, 1997; Ravindranath and Ostwald, 2008)

4.4 Selection of sample units

The study is based on the latest available global data on land cover and land

use, land degradation, protected areas, soil resources and climate as described by

Ravindranath and Ostwald, (2008), Brown, (1997). The sample units are almost

always fixed-area permanent plots. Permanent plot locations were selected either

randomly or systematically. Mostly, the stratified random sampling was used;

sample units for each stratum were selected systematically. Where a little is known

about the population being sampled, Random selection of sample units was

generally preferred, than systematic selection. Plot values were distributed

irregularly in a random pattern, and then both approaches were equally precise.

Some parts of the strata have higher carbon content thanothers, systematic

selection was usually resulted in greater precision than random selection, hence

preferred.

Techniques and methods for sampling design and for accurately and

precisely measuring individual carbon pools in forestry projects exist and are based

on commonly accepted principles of forest inventory, soil sampling and ecological

surveys (Pinard and Putz, 1996, 1997; MacDicken, 1997a, b; Post, et al., 1999;

Winrock International, 1999; Brown, et al., 2000a; Hamburg, 2000). Methods used

in present study are well established and tested for determining the number, size

and distribution of permanent plots (i.e. Sampling design) for maximizing the

precision for a given monitoring cost (MacDicken, 1997a).

4.5 Trees sample inventory

Based on the principal of stratified random sampling outlined a sample tree

inventory method requiring no level of pre-existing information, by knowing the

total number of existing street trees in the city as described by Jaenson et al.,

(1992). The data sets consisted of individual tree measurements for DBH, total

height and total aboveground biomass of tropical tree species was used, majority of

which were fast-growing plantation species (Banaticla, 2009; Maco and

McPherson, 2003). The street tree information including species composition,

DBH, height, total number of trees and vacant planting spaces, were affordably and

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reliably collected and analyzed, providing a database that capitulated accurate

baseline information pertaining to the function and sector wise structure of the

vegetation resource.

The areas were stratified into sectors based on locations on land and land

useplanning map, street layout and naturally demarcate characteristics such as

political boundaries. Each sector was then divided into sampling units or

equivalent street sectors, which was randomly sampled throughout the city. To

determine the distribution of the all trees species to sample among sectors, a pre-

sample survey was conducted to estimate sectors street tree density or average

number of trees per sampling unit, in each of these 9 sectors. Finally survey of

each tree, within each randomly chosen sampling unit was completed. Number of

structural attributes like as tree species, DBH, tree height, tree maintenance

priorities, plantable spaces, etc. were recorded on paper for analysis. The trees

were inventoried on the basis of height class from 0-5, 5-10, and above, assuming

no preexisting knowledge regarding the street tree resource in Aurangabad city.

The method described by Jaenson, and others (1992), was followed precisely.

Inventory Protocols after determining the number of sampling units to be

inventoried per sector, all trees in the city main concern within each unit were

surveyed, with basic size and condition measurements collected as necessary to

understand desired structural attributes of the population. In addition to the public

street trees, garden trees targeted for inventory, private street trees those found

within the main concern but not maintained by the city were also sampled. Only

those private trees located in sectors randomly selected for inventory of public

trees were inventoried. Two person teams (a measurer and a recorder) were used to

record data onto a tally sheet, later entered into a computer spreadsheet for data

analysis (Maco and McPherson, 2003).

4.6 Method for estimating Above-ground Biomass

Carbon stock was estimated in terms of biomass of above-ground biomass

of different commercial plantation as well as forest types in the city area using

field methods such as plot and plotless methods after conducting the field survey.

The carbon stocks are measured and estimated using literature methods (Banaticla,

2009; Paustian, et al., 2000; Chave, et al., 2005; Jana, et al., 2009). The plotless

method is applied for carbon inventory at urban areas in Aurangabad.

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Plotless method

Plotless method involves measuring tree density and diameter (DBH) along

a series of parallel sample lines (MacDicken, 1997; Ravindranath and Ostwald,

2008) was used for present study. It was comprised of the follows:

The land-use categories from urban area for the carbon sequestration study

were selected and sampling sectors located were fixed. Series of parallel sample

lines in each sector were established. The height and diameter at breast height

(DBH) are two main biophysical measurements which measured for each tree

sample. The species name, DBH and height of the tree along with distance between

the sample point and for each tree recorded. According to trees count, maximum

100 measurements were taken for dominant species per stratum and other tree

species.

A model was used to project changes in carbon stocks in biomass in forests

and plantations (Chave, et al., 2005; Green, et al., 2007; Jana, et al., 2009). The

tree species details differing in shape, size, rate of growth and wood density were

studied. The volume of tree was measured and converted to biomass using the

density of each tree species. Biomass of tree species was estimated and

extrapolated to per hectare based on the density and distribution of each species to

estimate biomass Kilograms/tree or tones/hectare as the function of tree parameters

such as DBH in meters and height in meters. The biomass is expressed in terms of

volume (cubic meter) or weight (Kilograms/tree) whenever necessary. Above-

ground biomass of trees was calculated using DBH and height of trees and biomass

equation. It has traditionally been assumed that the carbon content of dry biomass

of a tree was 50% (Brown and Lugo, 1982; Chave, et al., 2005; Roy, et al., 2001;

Malhi, et al., 2004).The works of different Scientists and Researchers was used as

reference in which the carbon content in the plant is assumed approximately 50%

of the dry matter (Losi, et al., 2003; Negi, et al., 2003; Jana, et al., 2009).

Therefore, the study conducted by Chavan and Rasal (2011) in University campus

of Aurangabad was exceptional in which it is found that carbon content of dry

biomass was 54% for Mangifera indica (Chavan and Rasal, 2011a).To estimate

carbon content in dry biomass, the ash method was used for Emblica officinalis,

Mangifera indica, Tamarindus indica, Achras sapota, Annona retiaculata and

Annona squamosa (Chavan and Rasal, 2011b; Chavan and Rasal, 2011c).

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Estimation of the Aboveground Biomass pool

The goal of measurement and monitoring was to estimate the stocks of

above-ground biomass or its rate of growth on per hectare basis as well as for the

total area based on identification and selection of a key set of indicators parameters

(Green, et al., 2007; Chave, et al., 2005). The parameters selected were depends on

method adopted to study biomass estimation for the “plot method”.

A Name of the species

Tree identification in urban areas is complicated. There are usually a large

number of species in urban areas, including native and exotic trees and various

conditionsassociated with the urban environment when alter specific characteristics

of a tree, such aschanging the appearance of the leaves or bark that help in tree

identification. Identifying and understanding of trees in the urban environment was

important to estimate carbon sequestration. Tree is a woody plant with several

distinguishing characteristics like often reaches 15 feet or more in height at

maturity, it has a single trunk or dominant multiple trunks, at least a partially

defined crown, usually larger than other plants and tend to be long lived.

Thegrowth form or shape, rather than size, is the feature that distinguishes a tree

from other plants such as shrubs (Harris, 1992).Trees are identified by using

different methods based on tree parts. Parts of a tree were compared to illustrations

in manuals or identification books (Fernandez,1999; Santapau, 1999) and

confirmed using photography. The most important features to look for in

identifying a tree are leaves, twigs and stems, bark, flowers, fruit and seeds. These

were compared with the literature sources (Nowak, 1994; Cairns, et al., 1997;

MacDicken, 1997; Losi, et al., 2003; Jana, et al., 2009).

B Diameter or girth at breast height (DBH)

Usually measurement of diameter or girth at breast height (DBH or GBH),

is one of the most important parameters and represents the volume or weight per

tree, which can be important to convert to biomass per unit area (Unit/hectare or

tones/hectare/year). DBH is the stem diameter at 1.3 meter above the ground

(FAO, 2004). The diameter and height can be used for estimating the volume by

simple equations; DBH values can also be used in allometric functions to estimate

volume or biomass per hectare. Usually DBH is easy measure in the field and by

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appropriate marking; the measurement can be repeated over time. Several

instruments available for measuring tree diameter such the caliper and a steel tape.

The tree diameter was measured at breast height (DBH) by using diameter measure

tape. It is a steel measuring tape (minimum length 10m). For each species and each

stand condition, calculate the average diameter (Chavan and Rasal, 2010).

Figure 4.2: Diameter Measurement

C Height measurement of trees

Tree height refers as the total tree height as the vertical distance from the

ground level to the uppermost point. Height is most important indicator of the

volume or weight of the tree and used in many allometric functions along with

DBH. Measuring the height of all trees, especially those with overlapping

canopies, require instruments and may introduce errors (Chavan and Rasal,

2010).There are a number of different methods for obtaining tree heights. To

estimate biomass from each tree species it is not advisable to cut them. For small

trees the heights can be measured directly with graduated poles. Usually this

method is too cumbersome for trees greater than 20 meters in, and this method is

mainly restricted to detailed study plots. The height of trees was measured by

Theodolite instrument follower the procedure given elsewhere (Chavan and Rasal,

2009; 2010; 2011).

The biomass can be measured by mathematical models by measuring

Diameter at Breast Height (DBH) directly and the girth at DBH. Girth considered

is the DBH measured at breast height at approximately 1.3 meter and diameter of

tree having diameter above >10 cm are treated as trees and are measured. The tree

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height was measured by Theodolite at DBH. The angle between the tree top and

eye view at breast height angle (α) is taken into consideration for tree height

measurement and height of the tree is calculated (Fig.1).

Figure 4.3: view of tree height measurement by Theodolite at breast height

Considering the angle ACB between tree top and the distance (b) at the

point of observer at DBH, the tree height was calculated If α is the angle between

eye view and top of the tree, a is the height of the tree in feet, c is the slope

between tree and eye view, b is the distance in feet between tree and observer and

h is height of horizontal plane of Theodolite instrument, then the height of tree (H)

is calculated by the following formulae:

D Canopy width measurement

Normally, the measurement of canopy width is taken only on species under

4 cm DBH. If the DBH of trees less than 4 cm is measured, there may be no need

to take canopy width. The responsible group must decide whether the canopy

width in this situation should be recorded (Patricia and Lynn, 1999).

The measurements of canopy were readings recorded on the data sheets but

have neglected as there can have scientific errors due to uneven spread in all

direction (Patricia and Lynn, 1999; Ravindranath and Ostwald, 2008; Hairiah, et

al., 2009). The two persons needed while canopy recording where, one person to

holds the tape at the stem of the sapling or small tree and other draws out the tape

to the drip line of the canopy and the distance were measured and recorded. For

trees, eight measurements were taken at 45 intervals, starting with the north.

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N

NW NE

W E

SW SE

S

Figure 4.5.3: Tree canopy measurement

Where,

N = North;S = South;E = East;W=West

NE = North east; NW = Northwest

SE = Southeast; SW = Southwest

E Volume Estimation

The estimation of aboveground biomass tree parameters such as DBH and

heightis play major role. The height and DBH of all trees from the sample plots

measured. The values of height and DBH by species and by plots tabulated. The

volume of each tree in the sample plot using the following formulae.

Where,

V = volume of the tree in cubic centimeter

r = radius of the tree >10 cm and 1.3m above the ground = DBH/2

H = height of the tree in meters.

F Estimation of Wood density

The wood density values for the tree species obtained from literature

mainly, www.worldagroforestry.org. Wherever the density value for dominant tree

species is not available in the literature, the species most closely related to the

species present in the site or the wood density of the tree species was unavailable,

the standard average of 0.6 gm/cm3was taken (Warren and Patwardhan, 2004).

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4.7 Method for estimating belowground biomass

Below-ground or root biomass is necessary for natural forests, areas under

natural regeneration, protected area and agroforestry systems. The Below Ground

Biomass (BGB) includes all biomass includes all biomass of live roots excluding

fine roots having <2mm diameter (Chavan and Rasal, 2011). Biomass estimation

equations for tree roots are relatively uncommon in the literature. The

belowground biomass (BGB) has been calculated by multiplying above-ground

biomass taking 0.26 as the root to shoot ratio (Cairns, et al., 1997; Ravindranath

and Ostwald, 2008).

A review by Cairns, et al., (1997) covering more than 160studies from

tropical, temperate and boreal forests estimated a mean root to shoot ratio of 0.26

with a range of 0.18-0.3. Thus, it may be practical to use a mean default value of

0.26 for estimating the root biomass in most forestry projects. A default conversion

factor of 0.26 of aboveground biomass was used to calculate the below ground

biomass (IPCC, 2003; Ravindranath and Ostwald, 2008).

4.8 Estimation of Organic carbon content in Tree samples

The leaves, stem, sub branches, bark and root of each species were

separated to estimate carbon by Ash method. The fresh weight of each part of all

species washed with distilled water and dried with tissue paper immediately was

taken then oven dried for moisture removal at 800C for 24 hrs. Oven dried sample

were taken in pre-weighed crucible. The crucibles were placed in the Muffle

furnace adjusted at 4000 C, ignition was carried out for 2.30 hrs. The crucible was

cooled slowly inside the desiccators. After cooling the crucible with ash were

weighed and percentage of organic carbon were calculated as formulae given by

Allen et al., (1986).

Where, C is the organic carbon; W1 is weight of crucibles, W2 is weight of oven-

dried grind samples with Crucibles, and W3 the weight of ash with Crucibles.

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4.9 Biomass Equation

Biomass equations are used to estimate the weights of the tree based on

DBH and height of the trees in the sample area, Chavan and Rasal, (2012a).

Biomass equations are available only for some dominant commercial tree species

(Schroeder, et al., 1997; Kenzo, et al., 2009). The equations which are available are

often only species specific and also location specific. Neither, biomass equations

developed using mature trees can be used for younger trees, nor the equations of

younger trees for mature trees. Biomass equations are not available for most local

or native tree species in many regions. It makes desirable to develop biomass

equations wherever possible to suite the local tree species and age of the stand

trees in different study regions (Kenzo, et al., 2009; Ravindranath and Ostwald,

2008; Chavan and Rasal, 2011; 2012a).

Method to formulate Biomass equation:

Sample plots were selected and the tree species was identified. The

important parameters like DBH and height of selected tree species were measured

from all the trees in the sample plots. These values used to estimate the volume of

the trees, which can converted into biomass terms using wood density. The newly

biomass equation was developed by linking biomass of trees species and to DBH

and height (Banaticla, 2005; Brown, 1997; Chave, 2005). The constant (a) and

correlation coefficient (b) for the biomass equation estimated along with

coefficient of determination by using software package (Minitab/SPSS). Further

discussion on developing and using biomass equations can be found in Brown,

(1997) and Parresol, (1999).

Allometric equations describe the relation between biomass Vs diameter

and height of tree. To test the effect of height and diameter on aboveground

biomass of the tree the model is used Y = a + b (D) + c (H). Where, Y is

aboveground biomass (gm), D is diameter at breast height (cm), H is total height of

tree (m), a is the intercept and b, C = regression coefficients.

4.10 Estimating of Soil Organic Carbon

Soils are often large storage pool for carbon, both organic carbon and

inorganic carbon. Soil carbon can be determined effectively using composite

samples that represent multiple plots. The volumetric estimate of the soil carbon

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pool has to be undertaken at a scale proportionate with sampling units used for

above-ground biomass and vegetative density. This helps to reduce costs of data

collection and analysis, yet provides a reasonable estimate of soil properties.

Methods for estimating SOC are well documented and extensively used in all

projects (IPCC, 2003; 2006; Mac Dicken, 1997; Hairiah et al., 2001). Soil carbon

stock is the highest in the upper soil profile (0-15cm), which should be sampled

most intensively (Richter et al., 1999; Ravindranath and Ostwald, 2008). Soil

organic carbon is routinely estimated for all forestry, grassland and cropland

conservation and developmental projects by various methods. Among the various

methods, Wet digestion or titrimetric (Walkley and Black method) is the rapid,

most commonly adopted and cost-effective method to estimate organic carbon

content of soil. The following procedure is used to Soil organic carbon inventory

for urban area at a given depth:

For research activity the land use category were selected and according to

the defined strata boundaries was demarcated. The soil sampling points located for

the organic carbon study. The map was prepared by using a geo-referencing

systemand land use-land planning map and political boundaries. The Aurangabad

city’s area was stratified into nine sectors based on located GIS map. From each

location five soil samples were collected by soil auger from each randomly at

15cm soil depth.

A Measurement of Bulk Density

Soil bulk density is defined as the oven dry weight of soil unit of its bulk

volume. Bulk volume includes volume of soil solids and pore spaces, and bulk

density is expressed as grams/cubic centimeters. Bulk density of soil indicates the

degree of compactness and aeration, which is necessary for estimating the weight

of soil per unit area per hectare. The bulk density is calculated from bulk volume

and weight of the dried soil (Ravindranath and Ostwald, 2008).

The location for sampling sites for estimation of soil organic carbon (SOC)

was selected. The dimensions of tin like height and diameter noted. Core tin box

was weighed. The soil samples were sampled at vertically at 15cm depth. Without

disturbing the soil inside the core tin extracted and removed the extra adhered soil

with core tin and along with soil the sample tin was weighed. The soil with core tin

was dried at 1050C inside the oven and weighed the dried soil. The bulk density

108

(g/cm3) of soil was calculated by dividing the weight of the oven dry soil by the

volume of the tin.

B Organic Carbon

The soil analysis was analyzed in laboratory by Walkley and Black method

explained by Trivedy et al., 1998. The soil organic carbon (SOC) and Soil organic

matter (SOM) was estimated from nine sectors of Aurangabad city.

Estimating of soil carbon sequestration involves estimating of bulk density

of the soil and soil organic carbon content. The content of organic carbon in soil

estimated in percentage terms needs to be converted to tones per hectare (tCha-1

)

using bulk density, depth of the soil and area in hectare (Ravindranath and

Ostwald, 2008).

Soil mass (tha-1

) = [Area (10,000 m2/ha) X depth (0.3m) X bulk density (t/m

3)]

109

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