Solid waste management has become a global problem. Littering of wastes on streets not only causes inconvenience and aesthetic problems, but also has a lot of impact on human health Municipal Solid Waste Management (MSWM) is highly neglected aspect of Delhi. At present approximately 6000 tons of waste is generated per day which is disposed in the three existing landfills. The three landfills are almost saturated therefore some alternate method of disposal should be designed. The present paper discusses the energy content of MSW of Delhi so that some suitable technology can be adopted for the disposal of wastes. Generally evaluation of the heating value of Municipal Solid Waste (MSW) is done experimentally by using bomb calorimeter and theoretically by using Dulong’s equation. In this paper, regression analysis is used to develop a predictive model of the energy content for MSW of Delhi.

1. Study of municipal solid waste of Delhi for energy content
JEWM
Study of municipal solid waste of Delhi for energy
content
Sushmita Mahapatra
Associate Professor in Bharati Vidyapeeth College of Engineering, A 4, Paschim Vihar, New Delhi – 11006, India
Email: monty_s3@yahoo.com, Tel.:011 2578443, Fax: 01125275436
Solid waste management has become a global problem. Littering of wastes on streets not
only causes inconvenience and aesthetic problems, but also has a lot of impact on human
health Municipal Solid Waste Management (MSWM) is highly neglected aspect of Delhi. At
present approximately 6000 tons of waste is generated per day which is disposed in the
three existing landfills. The three landfills are almost saturated therefore some alternate
method of disposal should be designed. The present paper discusses the energy content of
MSW of Delhi so that some suitable technology can be adopted for the disposal of wastes.
Generally evaluation of the heating value of Municipal Solid Waste (MSW) is done
experimentally by using bomb calorimeter and theoretically by using Dulong’s equation. In
this paper, regression analysis is used to develop a predictive model of the energy content
for MSW of Delhi.
Keywords: Solid wastes, landfill, Incineration, dulong’s equation
INTRODUCTION
Growth of population and Industrialization has led to
human activities as a result of which huge amount of
solid wastes is generated. This generated waste thus
needs to be collected, transported and finally disposed
off. Dumping of these wastes (which was practiced
earlier) has caused lots of damage to the environment.
Therefore, disposal methods must be adequately
selected so that the waste could be disposed off
without any further environmental problems.
In Delhi about 6000 tons of MSW are generated per
day and the average per capita generation of MSW in
Indian cities varies between 0.4 – 0.6 Kg/day (Khan
and Naved 2003). The per capita generation of MSW in
Delhi is the highest which is approximately 0.65 Kg/day.
Delhi has the largest municipal body in the world
providing services to an estimated population of 17
million people (in 2014) covering an area of ~ 1400 Km2
(Manual on Municipal Solid Waste Management 2000)
There are three agencies that are mainly responsible
for solid waste management in Delhi i.e. Municipal
Corporation of Delhi (MCD), the New Delhi Municipal
Corporation (NDMC) and the Delhi Cantonment Board
(DCB). Of these, the Conservancy and Sanitation
Engineering (CSE) Department of MCD bears the
maximum burden, as it is responsible for 1399 km2
of
the total territory of 1484.5 km2
. There is also a wide
variation in the generation of wastes observed while
moving from low to high income groups as reported in
the MSW management, 2000 (Notification by Ministry
of Environment and Forests Issued on 25th September,
2000) As part of the data collected and compiled,
(Bhoyar Titus Bhide and Khanna 1996) showed that
most places in Delhi lack proper collection facilities.
Hence, transportation, collection and disposal have
become labor intensive activities. The only method of
disposal of waste is landfills. In Delhi, at present there
are three landfills which are in use (MCD Delhi 2012).
The three landfills that are functional are at Ghazipur,
Okhla and Bhalswa and have nearly reached their full
capacity. The two composting plants include a MCD
owned and operated plant in Okhla and a privately
owned and operated plant in Bhalswa. Large scale
composting plants are not economically beneficial and
are highly dependent on the ready market for the
product. As the energy content of the waste disposed in
the landfill is high incinerating the MSW
Journal of Environment and Waste Management
Vol. 2(1), pp. 056-058, February, 2015. © www.premierpublishers.org,ISSN: 1936-8798x
Short Communication

2. Mahapatra 056
Table 1. Details of zonewise survey (Figures in %)
Physical
Composition
Mongolpuri
AtaThakurdas
Greenpark
Subhasnagar
Trilokpuri
NaveenSahadra
Shakurpur
Chandnimahal
Outremline
Kutubroad
Aryasamaj
Sundarnagri
Foodwastes 9.7 5.6 40.7 5.5 10.6 9.6 3.7 42.1 57.7 5.6 6 8
Paper 2.7 8.6 5.9 8.7 9.7 2.7 4.1 3.8 7.7 8.6 10.5 6.1
Plastic 1.9 11.1 4.7 6.2 5.8 2 3.3 1.3 5.8 11.2 9.9 48
Textile 12.4 11.4 4 6.5 5.6 12.6 0.7 10.1 7.7 13 13.3 3.7
Glass 2.3 8.6 4.8 6.1 8.1 2.3 3.3 4.4 5.8 9.1 16.9 5
Metals 0.9 6.7 1.7 4.4 3.2 0.9 3.4 1.2 3.8 6.8 14.8 1.2
Dirt Ash
etc. 70.1 23 34.2 56.9 39.4 69.9 72 19.1 11.5 22.9 16.5 24.9
# Source: white paper on pollution in Delhi with an action plan government of India ministry of environment &
forests chapter 5 (1997)
appears to be one of the options for management of
municipal solid waste of any area (Qudais and Qdais
2000)
Energy Content of MSW of Delhi
The determination of heating value of MSW is done
either experimentally using a bomb calorimeter or
theoretically using mathematical models. The models
are based on the physical composition, proximate or
elemental analysis. The disadvantage of using
Dulong”s equation (elemental analysis) is that the
sample size used for this equation is very small (1-10
mg) and skilled workers are required to carry out the
analysis (Jimenez andGonalez. 1991, Dermirbas 1996,
5 (76) and9/10 , Raveendran and Ganesh 1996
Fernadez, Diaz and Xiberta 1997). On the other hand,
the models which are based on proximate analysis or
physical composition (Liu ,Paode and Holsen 1996 and
Reddy, Basha, Joshi, Sravan, Jha and Ghosh 2005) fit
well within the locality but do not give good results for
other places. Thus considering the above factors, this
paper aims to develop a new model for the calculation
of HCV (high calorific value) for Delhi. The equations
proposed in this model are based on data either from
the physical, proximate or elemental analysis of MSW
of Delhi (as collected from various sources). The
physical composition analysis is based on the heat
generated from various sources like paper, plastic,
garbage etc. The elemental analysis is based on the
percentage of carbon, oxygen, nitrogen and sulfur in
the waste while the proximate analysis includes an
assessment of moisture, volatile combustible matter
fixed carbon and ash. Since the MSW of any area is
highly heterogeneous in nature the HCV calculated by
proximate or elemental analysis is not very accurate.
Thus an attempt is made to find the heating value using
physical composition. The following equations are
used for the development of the model.
H = 88.2 R + 40.5 (G+P) – 6 W ,where {1}
H = net calorific value (Kcal/kg)
R = plastic, percent weight on dry basis
G = garbage, percent weight on dry basis
P= paper, percent weight on dry basis
W = water, percent on dry basis
Equation used for ultimate analysis is Dulong Model {2}
H = 81 C + 342.5 (H-O/8) + 22.5 S –6 (9H+W), where
H = net calorific value (Kcal/kg)
C = Carbon (% wt)
H = Hydrogen (% wt)
O = Oxygen (%wt)
S = Sulphur (% wt)
Equation used for proximate analysis Traditional Model
H= 45 B – 6 W where {3}
H = net calorific value (Kcal/kg)
B = combustible volatile matter
W = water (% dry basis)
MATERİAL AND METHOD
A systematic approach in managing solid waste is
necessary because there is a variation in the
composition of MSW from area to area. A detailed
physical composition of MSW has been carried out
zone wise in Delhi by NEERI in 2000 The analysis
covered all areas such as high income group (HIG),
middle income group (MIG), vegetable market,
industrial areas, construction sites etc. The components
of waste identified in the analysis are food waste,
paper, plastic, textile, glass and metal (as shown in
Table 1).
For sample calculation, Modified Dulong’s Equation is
used, which is :
E= 81C + 342.5 (H-O/8) + 22.5 S – 6(9H-W) {4}
Where, E is the energy content (HHV) of waste in
Kcal/Kg and C, H, O, S & W are percentage weight of
Carbon, Hydrogen, Oxygen, Sulfur and water

3. Study of municipal solid waste of Delhi for energy content
J Environ. Waste Manag. 057
Table 2. Data from the Ultimate Analysis of the components in residential MSW
Component
Percent by weight (dry basis)
Carbon Hydrogen Oxygen Nitrogen Sulfur Ash
Organic
Food waste 48.0 6.4 37.6 2.6 0.4 5.0
Paper 43.5 6.0 44.0 0.3 0.2 6.0
Cardboard 44.0 5.9 44.6 0.3 0.2 5.0
Plastics 60.0 7.2 22.8 - - 10.0
Textiles 55.0 6.6 31.2 4.6 0.15 2.5
*Organic content is from coatings, labels and other attached materials.
Table 3. The HCV values of various localities of Delhi
Localities of Delhi HCV (kcal/kg)
Shakurpuri 0523.924
Mangolpuri 1229.65
Subhashnagar 1217.84
Naveen Sahadra 1241.55
Trilokpuri 1393.26
Ata Thakurdas 1757.39
Kutub road 1843.91
Arya samaj 1862.18
Chandnimahal 2454.54
Outermline 3378.45
Sunder nagar 3384.2
respectively. The elemental analysis of the components
in residential MSW as calculated by NEERI is given
below in Table-2 (Agarwal, Rathore and Gupta 2004)
The mass of C, H, O, N, S and Ash for food waste,
paper, plastic, rags, glass and metals is calculated on
dry basis.
RESULTS AND DİSCUSSİON
Development of the Model
For deriving the mathematical equation linear
regression analysis using SPSS 13 statistical software
is used. The model is based on physical composition of
MSW. The resulting regression equation can be
expressed as :
Y = B0 + B1X1 + B2X2 + ………+ BkXk
Where Y is dependent variable, X1, X2, …..Xk are
independent variables; B0 is intercept of straight line,
B1, B2,…..Bk are unstandarized regression
Coefficients The energy content is the dependent
variable and the physical composition of the waste
(Food waste,paper, plastic textile) is the independent
variable The equation which is developed from the
above model, using the various physical compositions
(in percentage weight) (Mohapatra and Gadgil 2008)
EC = 0.001 + 41.337 (FW) + 33.753 (P) + 59.611 (PL)
+ 50.346 (T) {5}
Where, EC = Energy content of the waste in Kcal/Kg
FW = Food waste
P = Paper
PL = Plastic
T =Textile
The average HCV of Delhi from the above table.3 is
1887.16 Kcal/kg and the actual average value of HCV
of Delhi is less than 3000 kcal/kg (from equation 4).
The difference in the theoretical and observed value is
due to the fact that the data used in the model is largely
for the low and middle income group localities.
CONCLUSİON
As seen from the calculation of Energy Content of
MSW the calorific values is less than 3000Kcal/kg
whereas in the developed countries it is 9200 Kcal/kg
Hence incineration of waste alone cannot be a solution
to the problem of disposal even in the capital state of
India i.e. Delhi. Better segregation facilities at the site of
collection of waste should be provided to give a higher
value of HCV of MSW.Gasification technologies enable
conversion of MSW into value added products, such as
liquid fuels and commodity chemicals as well as
electricity, and do so at greater efficiencies than
conventional incineration (Stevens D. 1994 ) Therefore
other technological options should be also considered
for better waste management.
REFERENCES
Agarwal GD, Rathore APS, Gupta AB (2004). A simple

4. Mahapatra 058
approach for estimating energy content of municipal
solid waste; IndIan Journal of Environment
Protection, 24: (2).
Bhoyar RV, Titus SK, Bhide AD, Khanna P (1996).
Municipal and industrial solid waste management in
India, J Indian Assoc Environ MAnag, pp 53-64.
Dermirbas A. Fuel 1996, 9/10(77) 1117-20
Fernandez P, Diaz RM, Xiberta J. Correlations of
properties of Spanish coals with their natural
radionuclides contents. Fuel 1997;76 (10): 951–5.
Jimenez L, Gonalez F, Fuel 1991,70: 947-50
Khan IH, Naved A (2003). Text book of solid waste
management. CBS Publishers, New Delhi, Manual on
Municipal Solid Waste Management, First edition,
Ministry of urban development, Govt. of India, New
Delhi, 2000.
Liu JI, Paode R, Holsen T, 1996, Modeling the energy
content of municipal solid waste using multiple
regression analysis; Journal of the Air and Waste
Management Association, 46: 650–656.
MCD Delhi (2012). Report on Solid Waste Transport
Management Systems.
Mohapatra S, Gadgil K Modeling the Energy Content
of MSW of Delhi. 23rd Conference on Solid
waste & Technology, Phildelphia, U.S.A., 31, 238-
244.
Qudais AM, Qdais A (2000). Energy content of
municipal solid waste in Jordan and its potential
utilization; Energy Conversion and Management, 41:
983-991.
Raveendran K, Ganesh A. Fuel 1996; 15 (575); 1715-
80
Reddy M S, Basha S, Joshi HV, Sravan KVG, Jha B,
Ghosh PK, (2005). Modeling the energy content of
combustible ship-scrapping waste at Alang–
Sosiya,India, using multiple regression analysis;
Waste Management, 25( 7): 747-754.
Stevens D (1994). Review and Analysis of the 1980-
1989 Biomass Thermochemical Conversion
Program.NREL/TP-421-7501. National Renewable
Energy Laboratory. Golden, Colorado.
Accepted 19 January, 2015.
Citation: Mahapatra S (2015). Study of Municipal Solid
Waste of Delhi for Energy Content. Journal of
Environment and Waste Management 2(1): 056-058.
Copyright: © 2014 Mahapatra S. This is an open-
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
cited.