Growing popularity of small scale biogas plants in Bangladesh
Uploaded by
Humayun Kabir,
Volunteer Researcher,
FAO, Rome, Italy
Contents
1. Introduction ............................................................................................................. 1
1.1 Objectives ............................................................................................................................ 1
1.2 History of biogas in Bangladesh ......................................................................................... 2
1.3 Infrastructure Development Company Limited (IDCOL)................................................... 2
1.3.1 Grameen Shakti (GS) ................................................................................................... 4
1.4 Raw Material and plant size requirement for a biogas plant ............................................... 5
1.5 Benefits of biogas uses ........................................................................................................ 7
1.5.1 Direct benefits .............................................................................................................. 7
1.5.1.1 Biogas production................................................................................................................7
1.5.1.2 Organic fertilizer or bio-slurry ............................................................................................7
1.5.2 Indirect benefits ............................................................................................................ 7
1.5.2.1 Health benefits.....................................................................................................................8
1.5.2.2 Improved education .............................................................................................................8
1.5.2.3 Employment generation ......................................................................................................8
1.5.2.4 Sex benefit ...........................................................................................................................8
1.5.2.5 Reduce biomass consumption .............................................................................................8
1.5.2.6 Reduce use of dried dung ....................................................................................................9
1.5.2.7 Reduction of chemical fertilizer use and improved soil fertility .........................................9
1.5.2.8 Time savings........................................................................................................................9
1.5.2.9 Protection from environmental degradation ........................................................................9
2 METHODOLOGY AND STUDY DESIGN .............................................................. 11
2.1 Study area .......................................................................................................................... 11
2.2 Sampling design and survey tools ..................................................................................... 12
2.2.1 Sampling design ......................................................................................................... 12
2.3 Data processing: Descriptive analysis ............................................................................... 13
3 ADOPTABILITY OF BIOGAS TECHNOLOGY ........................................................ 14
3.1 Empirical analysis of the models ...................................................................................... 14
3.1.1 Logistic model ............................................................................................................ 14
3.2 Variables explaining adoption of biogas energy ............................................................... 15
3.3 Profile of biogas users in study areas ................................................................................ 15
3.4 Results and discussion ....................................................................................................... 16
3.4.1 Factors influencing biogas energy adoption ............................................................... 16
4 SLURRY BASED EFFICIENCY AND PROFITABILITY OF RICE ............. 18
4.1 Introduction ....................................................................................................................... 18
4.2 Model specification ........................................................................................................... 18
4.3 Results and discussion ....................................................................................................... 19
4.3.1 Descriptive statistics of the variables of translog production function and technical
efficiency effect models of Boro production ....................................................................... 19
4.3.2 Parameter estimates of the stochastic production frontier .......................................... 21
4.3.2.1 Interaction impacts of biogas users .................................................................................. 22
4.3.2.2 Interaction impacts of biogas non-users ........................................................................... 25
4.3.2.3 Interaction impacts of pooled users .................................................................................. 25
4.4 Determinants of technical inefficiency ............................................................................. 26
4.5 Technical efficiency in Boro rice production .................................................................... 26
4.6 Profitability of Boro rice production ................................................................................. 27
5 COST-BENEFIT ANALYSIS ........................................................................... 28
5.1 Introduction ....................................................................................................................... 29
5.2 Analytical Approach of cost-benefit estimation model..................................................... 29
5.2.1 Financial evaluation ................................................................................................... 29
5.2.2 Economic evaluation .................................................................................................. 30
5.3 Economic viability of energy production from a biogas plant .......................................... 30
5.3.1 Net Present value (NPV) ............................................................................................ 31
5.3.2 Internal rate of return (IRR) ....................................................................................... 31
5.3.3 Payback period (PBP) ................................................................................................ 32
5.4 Systematic profile of costs and benefits of biogas plants .................................................. 32
5.4.1 Costs of a biogas plant................................................................................................ 32
5.4.1.1 Investment cost ..................................................................................................... 33
5.4.1.2 Operating and maintenance costs ......................................................................... 33
5.4.2 Benefits of a biogas plant ........................................................................................... 34
5.4.2.1 Valuation of a biogas plant ................................................................................... 35
5.4.2.2 Valuation of slurry as organic fertilizer ............................................................... 36
5.6 Summary of all assumptions of costs and benefits of a biogas plant ................................ 36
5.7 Results and discussion ....................................................................................................... 38
5.7.1 Assumption Analyses ................................................................................................. 38
5.7.1.1 Current costs of a biogas plant ......................................................................................... 38
5.7.1.2 Current benefits of a biogas plants ................................................................................... 38
5.8 Estimation of financial evaluation ..................................................................................... 40
5.8.1 With subsidy ............................................................................................................... 40
5.8.2 Without subsidy......................................................................................................... 41
5.8.3 Health benefits ............................................................................................................ 41
5.8.4 Surplus time used for income generation ................................................................... 42
5.9 Estimation of economic evaluation ................................................................................... 43
5.9.1 Carbon trading ............................................................................................................ 43
6 Policy recommendations..................................................................................... 46
i. Message to the literate households ....................................................................................... 46
ii. Sex appreciation .................................................................................................................. 46
iii. Subsidy and loan repayment: ............................................................................................. 46
iv. Role of electronic and print media ..................................................................................... 46
v. Awareness and capacity building ........................................................................................ 47
REFERENCES ...................................................................................................... 48
LIST OF TABLES
Table 1: Organizations involved in the extension of biogas technology in Bangladesh .............. 2
Table 2: POs wise biogas plant installation under NDBMP ......................................................... 3
Table 3: Design parameter of biogas plant .................................................................................... 5
Table 4: plant size range under warm climate ............................................................................... 6
Table 5: Definition of explanatory variables for biogas technology adoption model ................. 15
Table 6: Descriptive statistics of selected variables of biogas technology adoption .................. 16
Table 7: Logistic regression estimates of biogas energy adoption .............................................. 16
Table 8: Summary statistics of the variables used in the production function ............................ 20
Table 9: Descriptive statistics of the variables used in the technical efficiency model .............. 21
Table 10: Maximum likelihood estimates for parameters of translog stochastic production
function and technical inefficiency effect model .................................................................... 23
Table 11: Technical efficiency in Boro rice production.............................................................. 27
Table 12: Summary of input values, gross margin and BCR of rice production (per acre) ........ 28
Table 13: Cost and capacity of biogas plants .............................................................................. 33
Table 14: Estimation of annual current costs for small scale biogas plants ................................ 38
Table 15: Estimation of annual current benefits of biogas plants (BDT/year)............................ 39
Table 16: NPV, IRR, PBP and NBI of different biogas plants with subsidy ......................... 40
Table 16: NPV, IRR, PBP and NBI of different biogas plants without subsidy .................... 40
Table 18: NPV, IRR, PBP and NBI of different biogas plant with health benefits ................ 4242
Table 19: NPV, IRR, PBP and NBI of different biogas plants under time surplus for income
generation............................................................................................................... 43
Table 20: NPV, IRR, PBP and NBI of different biogas plants under carbon trading ........... 44
LIST OF FIGURES
Figure 1: Year wise biogas plant constructions under Grameen Shakti ................................. 4
Figure 2: Domestic biogas plant practiced in Bangladesh ................................................... 6
Figure 3: Study areas (spotted) of Bangladesh ................................................................ 11
Figure 4: Schematic presentation of sampling technique................................................... 12
Figure 5: Mean value of NPV, IRR, PBP and NBI of biogas plants in Bangladesh ............... 45
ACRONYMS AND ABBREVIATIONS
BBS= Bangladesh Bureau of Statistics
BCAS= Bangladesh Centre for Advanced Studies
BCSIR= Bangladesh Council of Scientific and Industrial Research
BDT= Bangladesh Taka
BER= Bangladesh Economic Review
BONDHAN = Bangladesh Organization Network for Development and
Humanitarian Aid for Nation
BSP= Biogas Sector Partnership
CAEEDAC = Canadian Agricultural Energy End Use Data and Analysis Centre
DLS= Department of Livestock Services
GOB= Government of Bangladesh
GS= Grameen Shakti
IDCOL = Infrastructure Development Company Limited
IEA = International Energy Agency
IFAD= International Fund for Agricultural Development
IRR= Internal Rate of Return
ISAT= Information and Advisory Service on Appropriate Technology
KVIC= Khadi and Village Industries Commission
kWh= Kilo Watt per Hour
LGED= Local Government Engineering Department
NDBMP = National Domestic Biogas and Manure Program
NPV= Net Present Value
PBP= Pay Back Period
PKR= Pakistan Rupee
POs = Partner Organizations
REEIN= Renewable Energy and Environmental Information Network
SHSs = Solar Home Systems
SNV= Netherlands Development Organization
UNCTAD= United Nations Conference on Trade and Development
UNFCC= United Nations Framework on Climate Change
1
1. Introduction
According to Biogas Digest (2009), Biogas is composed of methane (40-70%)
and carbon dioxide (30-60%) as a combustible gas produced by the action of
methanogenic bacteria. Bacteria create biogas through the organic procedures
under anaerobic (without oxygen) conditions. The usual production of biogas is
a core part of the biogeochemical carbon rotation. Methane producing bacteria
are the last link in a chain of micro-organism which degrade organic material
and return the decomposed products to the environment (REHLING, 2001).
Methane is a neutral gas that produces clear blue flame without smoke for
cooking. Biogas is used in a suitably-designed burner for use.
Biogas production technology has been available since the early 1900s when it
was used for the stabilization of the organic sludge produced during treatment of
domestic sewage (STUCKEY, 1983).
Biogas has seen rising popularity in the world especially the developing
countries due to its importance in the context of technical, socio-economic and
resource endowments of these countries. It has been used in India since 1923
(Prasad et al., 1974) and in China for a period of nearly 65 years (APH, 1989).
In India, a massive increase in the number of simple biogas plants took place in
the 1970s through encouragement by strong governmental policies. In the
interim, more than one million biogas plants are functioning in India (Biogas
digest, 2009). In China since the 1970s, biogas research and technology has
been developed at a high speed and biogas technology was promoted vigorously
by the government and non-governmental organizations. Now, in rural areas,
more than 5 million small-scale biogas digesters have been constructed and over
20 million people use biogas (Biogas digest, 2009). Both China and India have
had considerable success in extending the technology for its use by common
people. Bangladesh started with biogas technology through the first
demonstration plants implemented in 1972 (Gofran, 2004). Notable numbers of
small scale biogas plants are running across the country. Biogas, a renewable
energy from organic matter seems to have tremendous potential as an alternative
source to confront foreseeable energy crises in the near future.
1.1 Objectives
The major objective of this study is to evaluate the sustainability of biogas
production as an alternative source of renewable energy.
The following specific objectives have been adopted for fulfilment of the major
objective:
2
i)
ii)
iii)
to investigate factors determinants of biogas adoption.
to assess the efficiency and profitability of slurry and chemical
fertilizer based rice production; and
to appraise costs and benefits of biogas production
1.2 History of biogas in Bangladesh
The first floating-drum biogas plant, called the Khadi and Village Industries
Commission of India (KVIC) model was built in 1972 at BAU for research
purposes. In 1976, a family size KVIC-design biogas plant was constructed
inside a station of the Bangladesh Council of Scientific Industrial Research
(BCSIR), funded by the International Fund for Agricultural Development
(IFAD), this was followed by a plant at the KBM College in Dinajpur in 1980.
Table 1 presents the existing number of biogas plants in Bangladesh.
Table 1: Organizations involved in the extension of biogas technology in
Bangladesh
Year
Implementing institutes
Number of biogas
installation
1972
Bangladesh Agricultural University (BAU)
2
1973-2005
Bangladesh Council of Scientific Industrial
22100
Research (BCSIR)
1979-1983
Department of Environment(DOE)
260
1985-2001
LGED
7000
1987-2005
Bangladesh Rural Advancement committee
300
(BRAC)
1988-1994
Department of Livestock Services (DLS)
70
1983-1988
Bangladesh Small and Cottage Industries
30
Corporation (BSCIC)
1983-84
Bangladesh Agricultural Development
20
Corporation (BADC)
1998-2003
LGED
1200
2006 to
( NDBMP) under IDCOL
22539
2012
Source: (REEIN, 2009; IDCOL, 2012)
1.3 Infrastructure Development Company Limited (IDCOL)
After the realization of the reality of renewable energy in Bangladesh,
Government established a state-owned financial support institute, IDCOL, to
expand the renewable energy sub-sector in 1997, with assistance from different
donor agencies and countries. IDCOL plays a core role in bridging the financial
3
gap in developing medium and large-scale infrastructure and renewable energy
projects in Bangladesh. This company stands as the market leader in private
sector energy and infrastructure financing in Bangladesh. The renewable energy
project of IDCOL has often been working on its solar energy program and
domestic biogas and manure in Bangladesh. The solar energy program is one of
the fastest growing renewable energy programs all over the world. IDCOL
promotes dissemination of solar home systems (SHSs) in remote rural areas
through partner organizations (POs) with financial support from international
donor agencies and countries. IDCOL has been running the biogas activities
through the National Domestic Biogas and Manure Program (NDBMP) with
active PO participation. The major goal of the NDBMP is to develop and
disseminate biogas plants in rural areas, ultimately establishing sustainable and
commercial biogas plants in Bangladesh.
Fixed-dome biogas plants are constructed under NDBMP and are often cattle
dung-based, with a few other plants poultry litter-based. Biogas plants are
constructed by POs where there is sufficient cattle and/or poultry. At present 32
POs are implementing the NDBMP and constructed 22,549 domestic biogas
plants from 2005 to April 2012, from which 100,000 rural people now have
access to cooking gas as well as high-quality organic fertilizer for improvement
of soil fertility (IDCOL, 2012).
Table 2: POs wise biogas plant installation under NDBMP
Partner organizations (POs)
Plant completed (No.)
Grameen Shakti (GS)
12795
Rahman Renewable Energy Co. Ltd. (RB)
972
Save our Urban Life -SOUL
784
Kamrul Biogas (KB)
783
Hossain Biogas Company Ltd. (HB)
634
Rural Services Foundation (RSF)
925
Srizony Bangladesh
610
DESHA
655
Shubashati
493
BONDHAN
407
Nirapad Engineering
344
Bhelabazar Shamaz Unnayan Sangstha (BSUS)
316
Development of Poor Society (DOPS)
190
Samaj Unnayan Kendra (SUK)
331
Anannyo Samaj Kallyan Sangostha (ASKS)
178
Others
2132
Total
22549
Source: IDCOL(2012)
4
1.3.1 Grameen Shakti (GS)
Grameen Shakti is a Bengali term which means rural power. It is a sister wing of
Grameen Bank (Nobel laureate organization for peace in 2006). It is one of the
biggest contributor POs under IDCOL for both SHS and NDBMP project in
Bangladesh.
GS has adopted the IDCOL model as an integrated and sustainable model for
extending biogas programs. The program is functioning well with a marketbased approach. It seems to be a facilitator rather than a provider, not providing
any subsidy but arranges for subsidies, grants and soft loans for users, in
addition to giving a five year guarantee after implantation of a biogas plant. The
users pay back the credit on 25% of the total cost as a down payment and the
remaining 75% of the cost is to be repaid through 24 installments with an 8%
service charge (flat rate) within two years. This repayment schedule is strictly
maintained by GS (GRAMEEN SHAKTI, 2012). Figure 1 shows the gradual
increasing nature of biogas technology adoption in Bangladesh.
6000
5680
Biogas plants
5000
4605
4000
3000
2548
2000
1590
1000
453
30
0
2005
2006
2007
2008
2009
2010
Year
Figure 1: Year wise biogas plant constructions under Grameen Shakti
It also offers free post-construction services including monthly visits by GS
engineers. It has also created a bridge between biogas technology and emerging
poultry, livestock and agricultural businesses. It has applied a community-based
approach to sharing the costs and benefits of new biogas plants.
Excessive farming and chemical fertilizer application have degraded
Bangladeshi soil fertility. Thus, GS has undertaken a program to develop
organic fertilizers from biogas byproducts, namely slurry, and marketed these as
a supplement to chemical fertilizers. Selected entrepreneurs promote and
distribute GS-developed organic fertilizers while GS supports the necessary
technical assistance and ensures quality control. The quality of slurry, verified
5
by the Soil Research Departments of Dhaka University and Bangladesh
Agricultural University, as organic fertilizers developed by GS have found very
little harmful ingredients in poultry litter and cattle dung-based slurry.
Nevertheless, poultry-based organic fertilizer is very useful for reducing high
acidity and aluminum poisoning.
GS has signed agreements with two organizations to manufacture and promote
organic fertilizers. This is the first step taken by GS in Bangladesh towards
reaching the goal of providing farmers with environmentally friendly and high
quality organic fertilizer (GRAMEEN SHAKTI, 2012).
1.4 Raw Material and plant size requirement for a biogas plant
LAM and FELIX (2012) found the minimum daily input for operating a smallscale domestic biogas digester in Bangladesh to be 20-25 kg of animal dung
(cattle, poultry, pigs, buffalos) and where gas demand per person for cooking
and lighting is 0.33-0.40 m3/day. The daily input of dung required is about 6 kg
per m3 of a plant, and water and raw material ratio depends on the solid
percentage however, normally in Bangladesh, it is practiced 1:1 ratio (MENDIS
and VAN NES, 1999).
Family size and gas demand only determine plant size if there are plenty of
cattle (SNV, 2012)
Table 3: Design parameter of biogas plant
Design parameter
Dung / water ratio [d/w -vol]
Specific gas production [m3/kg]
Minimum daily gas production [m3/day]
Maximum retention time [days]
Minimum retention time [days]
Gas storage volume [% of max dgp]
Source: F.T.Heegde (2010)
Warm
1.00
0.040
1.00
60
40
60%
Climate
Temperate
1.00
0.040
1.00
75
50
50%
6
The biogas users in Bangladesh are following to construct the biogas plant under
Table 4 circumstances.
Table 4: Plant size range under warm climate
Plant volume (dm3)
3900
Gas storage volume (dm3)
900
Digester volume (dm3)
3000
Min feeding (kg/day)
25
Max feeding (kg/day)
38
Min daily gas production (m3/day) 1.00
Max daily gas production (m3/day)
Avg feeding (kg/day)
Avg gas production (m3)
Source: Heegde, F.T. (2010)
1.50
31
1.25
5850
1350
4500
38
56
1.50
8775
2025
6750
56
84
2.25
13163
3038
10125
84
127
3.38
2.25
47
1.88
3.38
70
2.81
5.06
105
4.22
Usually the following fix dome biogas plants have been practiced in the
Bangladesh. Water and manure mixture are load into the inlet and it falling
down in the digest and after retention, biogas would be formed and pressure to
slurry going out through outlet (Figure 2). Biogas pipe is used to flow the gas to
kitchen stoves.
Figure 2. Domestic biogas plant practiced in Bangladesh
7
1.5 Benefits of biogas
Benefits from biogas can be divided into two groups: direct and indirect
benefits. It is not only a matter of gas and organic fertilizer production but the
topic has a lot of physical, social, economic, environmental and even political
implications within society. The following discussion will present the different
direct and indirect advantages of biogas technology.
1.5.1 Direct benefits
At first, Biogas plants are forming gas and releasing bio-slurry that provides
direct benefits to society. Before being used as a raw material for biogas
production, cattle dung was either used for cooking or as fertilizer on
agricultural fields. After implementation of a biogas plant, households get twofold direct benefits from using biogas:
1.5.1.1 Biogas production
New technology has introduced into rural areas of Bangladesh what is called
biogas applicable for cooking and heating purposes. In Bangladesh, there is
great potential to produce 2.7 billion m3 from 4 million small-scale biogas
plants, which is equal to 1.5 million tons of kerosene, using livestock resources
(BAHAUDDIN and SALAHUDDIN, 2012).
1.5.1.2 Organic fertilizer or bio-slurry
Soil fertility in Bangladesh is gradually diminishing. One of the reasons is overuse of chemical fertilizers. The by-product of a biogas plant, namely slurry, can
be the best alternative supplement to chemical fertilizers for maintaining the
fertility of soil. It has no toxic or harmful effects, the nutrient quality of slurry is
higher than that of compost manure and chemical fertilizer, as the minimal loss
of nitrogen in slurry is more effective as fertilizer than composted cattle dung
(ISLAM, 2006; BCAS, 2009). Undesirable plant seeds are killed inside the
digester during the retention time for biogas production. Thus, less labor is
needed for weeding in agricultural production for whoever uses this slurry.
Besides that, the demand for organic products is becoming more popular around
the world.
1.5.2 Indirect benefits
It has a lot of beneficial dimensions which serve the well-being of the whole
global society. Few of the following notable indirect benefits from biogas have
been discussed:
8
1.5.2.1 Health benefits
Indoor air pollution from biomass burning is a major cause of acute respiratory
infections, constituting the main cause of death in young children in developing
countries (MURRAY and LOPEZ, 1996) where natural gas is significantly cleaner
than biomass as a burning fuel.
1.5.2.2 Improved education
Energy deficit is one of the causes for the low literacy rate in developing
countries. There is a severe shortage of energy for lighting in rural areas. This
makes for a big problem for children or younger people who should be involved
in education-related tasks in the evening. BCAS (2009) conducted a survey
among biogas users and concluded that 65.6% of total respondents said that
biogas technology installation saved time that could be used for children, 3.4%
found a decrease in available time and 31% found no change.
1.5.2.3 Employment generation
Currently, renewable energy is a new sub-sector in Bangladesh as well as other
developing countries where employment generation activities are present due to
adoption of biogas plants in and around households. About 11,000 people are
employed in the biogas sector in Nepal (BAJGAIN et al., 2005) and a notable
number of employees are found to working this sub-sector in Bangladesh but
proper data could not be found.
1.5.2.4 Sex benefit
Since women and female children are involved in collecting firewood, they
would be able to reduce their workload by 3 hrs. per day with the installation of
a biogas plant in a home (DAHAL, 2005). This is equivalent to saving about
120,000 hrs. per day based on the approximate 40,000 biogas plants in
Bangladesh.
1.5.2.5 Reduce biomass consumption
Firewood is a major component of biomass and is one of the major sources of
cooking and heating fuel in developing countries. Combustion of biomass has
adverse impacts on public health, economic development and local ecology
(PEIPERT, et al., 2012). Adoption of biogas plants has automatically protected
forest resources. It has been found from study that a biogas plant annually saves,
on average, 2 tons of biomass per household (EAST CONSULTANT, 2004).
Nevertheless, the majority of people are dependent on biomass fuel for cooking
- 97% in Bangladesh where more than 40 million tons of biomass fuel are being
used every year in this regard (HAQUE, 2008).
9
1.5.2.6 Reduce use of dried dung
On average 0.7 kg of cattle dung is saved from being dried and burnt in
inefficient cooking stoves in every biogas household. For this reason,
agricultural residues and cattle manure are converted into efficient energy in the
form of methane gas (BSP, 2006). Open burning of dried dung results in carbon
emission and badly effects human society and effectively deprives the soil of a
source of fertility.
1.5.2.7 Reduction of chemical fertilizer use and improved soil fertility
The fertility of the soil has been diminishing steadily by prolonged use of
chemical fertilizers in Bangladesh. SINHA and RAHMAN (2005) stated that the
organic matter content in a soil should be over 3%, however it is now less than
1.5% in many places. Providing the bio-slurry from biogas plants will serve to
generate organic matter in the soil. Along with methane gas, a biogas digester
produces slurry having high nitrogen, potassium and phosphorus contents.
Prices of chemical fertilizers have been increasing over the years so that
households cannot cope with price hikes and maintain optimum levels of
production (BER, 2011). This slurry can be used as an alternative source of
fertilizer in agricultural fields. It will drastically reduce demand for foreign
currency due to decreased amounts of chemical fertilizer imported from abroad.
1.5.2.8 Time savings
It is a simple principal that biogas production can relieve people of the hard job
of fuel collection as well as the continuous attention required during the cooking
period. DAHAL (2005) found that a biogas plant can save on average 3 hrs. per
day in time for fuel wood collection in addition to reducing the time needed for
cooking. BCAS (2009) also received a more or less similar response from
biogas users in the study area where 96.2% of total respondents said that after
installation, biogas plants reduced the time needed for cooking.
Biogas users, especially women, utilize the saved time for income generating
activities like handcrafts, small business, livestock rearing, or, alternativels,
more attentiveness to their children’s education and homework, more recreation,
small gardening etc.
1.5.2.9 Protection from environmental degradation
Global warming and mitigation of greenhouse gases are major issues in the
current world. The practice if burning biomass is one of the major causes of
global warming, where renewable energy could be a solution for maintaining a
sustainable environment. It is a logical argument that CO2 emissions are reduced
by using biogas as an alternative to biomass directly. It is possible that 1 ton of
10
cattle dung can produce 37 m3 of biogas and if the cattle dung is used for
cooking directly, then CO2 emission from 1 ton of dung is equal to 0.648 tons, if
dung is used for biogas, and then CO2 emission per ton of dung is equal to
0.0677 tons. By using these values, reduced CO2 emission through biogas plants
from 1 ton of dung is 0.5803 tons. Total CO2 emission could be reduced by
46.58 million tons per year due to introducing biogas plants (BAHAUDDIN and
SLAHUDDIN, 2012). SNV/IDCOL also stated that proper application of small
scale biogas digesters can prevent the release of 2.5 tons of CO2 per year by
avoiding the burning of biomass (TORN, 2010).
11
2 METHODOLOGY AND STUDY DESIGN
2.1 Study area
The research areas in Bangladesh are adequate in terms of livestock availability
and other agricultural production. The study sites Mymensingh, Pabna,
Thakurgaon and Dinajpur districts were chosen. Mymensingh district is located
in central Bangladesh, Pabna district in western and Thakurgaon and Dinajpur
districts are in northern Bangladesh (Fig.2).
Figure 2: Study areas (spotted) of Bangladesh
Biomass is the major raw material for cooking and heating in the rural areas in
Mymensingh. Teguria is a union of Phulpur Upazila in this district that has
already been declared by GS as a biogas village. Pabna district is very famous
12
for livestock production. Pabna district produces surplus milk which supplies the
whole country. Ramchandrapur is a village in Pabna district that has been
declared as a biogas union. It has cattle dung and poultry litter-based biogas
plants. This village was also chosen for collecting data.
Dinajpur and Thakurgaon are surplus- producing agricultural areas in
Bangladesh. Rural households still have a notable number of livestock resources
used as draft animals for agricultural production or reared for commercial
purposes.
2.2 Sampling design and survey tools
2.2.1 Sampling design
Select 3 top-ranking divisions
from total of 7 divisions
Purposive selection: greatest biogas
coverage and potential
Purposive select 4 districts
from the 3 divisions: Pabna,
Mymensingh, Thakurgaon and
Dinajpur
Purposive selection: top-ranked biogas producing and
potential districts from each division. However,
Thakurgaon and Dinajpur were selected from Rangpur
division due to the high number of biogas plants and
potential compared to other districts of Bangladesh
1 FGD conducted in each
district:
Purposively select 8 members for FDG: 4, 3 and 1
from biogas users, non-users and local elite,
respectively
Kotowali and Phulpur sub-districts
from Mymensingh, Chatmohar
and Atghoria from Pabna, Sadar
from Thakurgaon and Bochaganj
from Dinajpur
biogas users (150
HHs)
Small
users (75)
Mid-sized
users (42)
non-users (150
HHs)
Large
users (33)
Purposive selection: two sub-districts from
each district of Mymensingh and Pabna; 1 subdistrict from each Thakurgaon and Dinajpur
Purposive selection: total of 300 in
sample: 150 user households with
neighboring 150 potential biogas user
households
Purposively select from three groups of
biogas users; small (2.4 m3) mediumsized (3.2 m3) and large (4.8 m3)
Figure 3: Schematic presentation of sampling technique
personally communicated with the key informants from each locality.
13
2.3 Data processing: Descriptive analysis
These steps are critically important in identifying related variables in addition to
preparing conclusions relevant to policy makers (HAQUE, 2011). Data were
selected on the basis of the objectives of the study. Both quantitative and
qualitative data were incorporated into the analysis to reach the goals of this
study.
After collecting the data from field study the data were coded and edited (for
spelling) and entered into an Excel spreadsheet. STATA 10 was chosen for
conducting the econometric analysis.
A logistic model was developed for determining the factors affecting the
adoption of biogas plants in Bangladesh. Decision-making tools like NPV, IRR,
PBP and NBI were applied for estimating the analysis of different assumptions
of cost and benefits and finally STATA 10 and Stochastic Frontier, Version 4.1,
was applied for estimating the efficiencies of slurry-based and conventional
agriculture.
14
3 ADOPTABILITY OF BIOGAS TECHNOLOGY
This chapter will deliberately present what factors are working behind
motivating rural people toward adoption of the biogas plants. Energy is the main
power behind economic growth, and it has indispensable effects on social,
political and environmental factors including livelihoods, access to water, better
education, increased agricultural productivity, good health and general issues
(AMIGUN et al, 2008). Thus, provision of affordable, efficient and reliable
energy, with minimal effect on the environment is very important. Rural
dwellers of developing countries are normally dependent on fossil fuels and day
by day the rate of fossil use is increasing, leading to ecological and environment
problems (KAREKEZI, 2002).
3.1 Empirical analysis of the models
3.1.1 Logistic model
A dichotomous binary approach was applied to investigate the biogas
technology adoption process. Both logit and probit are well-recognized
approaches in adoption studies (BURTON et al., 1999). It estimates the odds of a
certain event occurring. The dependent variable is a logit that is the natural log
of the odds:
P
ln(
)  a  bX
1 P
P
e abX
1  e abX
(1)
Where P is the probability of the event occurring, X are the independent
variables, e is the base of the natural logarithm and a and b are the parameters of
the model. The empirical form of the model used in the study is as follows:
Pr Y 
1
1 e
(2)
( a bX )
Where, Y is the logit for the dependent variable. The logistic prediction
equation for the present study was
Y=ln(odds(event))=ln(prob(event)/prob(nonevent))
= ln(prob(event)/[1-prob(event)]
 b0  b1 X 1  b2 X 2  .......... .....  bn X n
(3)
15
Where b0 is the constant with X1……..Xn explanatory variables influencing the
probability of choice of biogas technology and b1…bn were the coefficients
estimated. The dependent variable was modeled as: Y= adoption of biogas
technology= Pr Y; (1= household chooses to produce and use biogas
technology, 0= not to choose the biogas production).
3.2 Variables explaining adoption of biogas energy
Adoption of biogas technology in this study is defined as the production and
consumption of biogas from a small-scale bio-digester by a household. Several
factors are involved in motivating rural households to adopt a biogas plant. The
entire list of selected determinants of biogas adoption generated from the data
set and their definitions are presented in Table 5.
Table 5: Definition of explanatory variables for biogas technology adoption
model
Variable
Type
Description
Age
Continuous
Age of household head in years
Education
Continuous
Educational level of household head in years
Familysize
Continuous
Total number of family members in the household
Sex
Binary
Sex of household head; a proxy variable for sex
relations (1=male; 0= female)
Farmsize
Continuous Total land area cultivated by the household in acres
Cattle
Continuous
Total number of cattle owned by household
Poultry
Continuous
Total number of fowl owned by household (.00)
Income
Continuous
Total yearly income (.0000 BDT)
3.3 Profile of biogas users in study areas
The following Table 6 shows that out of 300 biogas users and non-users, 290
were headed by men and the remaining 10 by females. Age, family size and
number of poultry birds show no significant difference between biogas users and
non-users. On the other hand, biogas users show a significant difference from
non-users based on farm size, income, number of cattle, and years of schooling.
Besides, non-users of biogas technology had more poultry compared to biogas
users.
16
Table 6: Descriptive statistics of selected variables of biogas technology
adoption
Variable
Users
Non-users
Total sample
Age (years)
41.71
41.47
41.59
Farm size (acres)
3.56
2.77
3.24*
Family size (no. of members)
5.37
5.14
5.26
Sex
Male
140
150
290
Female
10
10
Education (years)
10.06
7.43
8.75*
Cattle (no.)
4.48
3.29
4.33*
Poultry bird (.00 no.)
3.46
4.08
461.24
Income (.0000 BDT/year)
27.39
21.15
25.31*
* Indicates that the difference between biogas users and non-users is statistically significant at
P<0.05 (t- test used for the difference in mean)
3.4 Results and discussion
3.4.1 Factors influencing biogas energy adoption
Among the eight variables included in the model, four of these indicated a
statistically significant effect on adoption of biogas technology. These included
sex of the family head, years of education of the family head, number of cattle
and income of the family.
Table 7: Logistic regression estimates of biogas energy adoption
Variable
Coefficient Standard Odds ratio Coefficient from
(I)
(II)
error
(IV)
odd ratio
(III)
(V) = (IV-1)
CONSTANT
-.383
1.20
0.681
-0.318
SEX
-1.443
0.867
0.235
-.764***
EDUCATION
0.172
0.036
1.189
0.189*
AGE
0.003
0.013
1.003
0.003
FAMILYSIZE
0.027
0.085
1.027
0.027
FARMSIZE
0.001
0.053
1.058
0.059
CATTLE
0.110
0.051
1.116
0.117**
POULTRY (,00 no)
-.0193
0.029
0.980
-0.019
INCOME (,0000 BDT)
-.0225
0.012
1.022
0.023***
*, **, *** denote significant difference at p<0.01, 0.05, and 0.10, respectively
Iteration 0= Log likelihood =--204.47672
………
Iteration 4= Log likelihood =-173.00674
LR chi2= 62.94, Prob> chi2=0.0000
Pseudo R2= 0.1539
Number of observations=295
17
% of total correct prediction = 98.3% (295 households out of 300)
On the other hand, family size, age, farm size and number of poultry birds are
not statistically significant. Increasing years of education of a household head,
the number of cattle and family income are positively correlated with adopting
biogas plants at 1%, 5% and 10% levels of statistical level of significance,
besides, the sex of the family head is negatively related to adoption of biogas
technology at the 10% level of significance.
In Table 7, indicates that though negatively correlated with the likelihood of
adopting biogas energy, sex of the household head, a proxy variable for sex
influence on the decision to adopt, was statistically significant at the 10% level.
This result indicates that female-headed households are distinctly encouraged to
adopt biogas technology. This particularly encourages development regarding
the promotion of biogas technology in an environment where women have at
least access to control of resources, yet provide most of the labor required for
production of biogas.
Logistic results revealed that years of education of the household head was
positively related at a 1% level of significance, such that the likelihood of
adoption of biogas energy increased by 18.9% with the addition of one year of
education.
in this study increasing farm size by one acre increases the likelihood of a
household adopting biogas technology by about 6% (Table 7).
An increase by one of cattle owned by a household increases the likelihood of a
household adopting biogas by about 12% at a 5% level of significance (Table 6).
Actually, cattle dung is one of the main sources of raw materials for biogas
production in Bangladesh. The number of cattle owned by a household thus has
a significant impact, at a 5% significance level, on the adoption of biogas
technology. This study found poultry to have no significant influence on
adoption of a biogas plant. Household income proved to be key factor in a
household’s decision to implement a biogas plant.
Thus, logistic regression suggests that if the income level of a household
increases by 10,000 BDT per year, the chance of adopting a biogas plant
increases by 2 percent at a 10% level of significance (Table 6). In Bangladesh,
initial investment is also considered high but IDCOL issues a certain level of
subsidy as well as soft loans to rural households to cover the initial high
investment costs. Thus, households do not suffer any monetary complications
during the plant implementation period.
18
4 SLURRY BASED EFFICIENCY AND
PROFITABILITY OF RICE
4.1 Introduction
Agriculture is identified as a series of operations that necessitates the efficient
mobilization of resources especially in most Asian countries where these
resources are scarce (RUBINOS, et al., 2007). It is common that farmers in
developing countries rationally want to maximize total agricultural output using
limited resources through adopting conventional or semi-modern practices.
Agriculture is the sole source of livelihood-generating strategy in these
developing countries, especially Bangladesh. Boro rice is a major crop which
contribute more than 50% of total rice production in Bangladesh.
4.2 Model specification
A Translog frontier model is applied for analyzing a biogas user frontier model,
biogas non-user model and a pooled model. Slurry is treated as a continuous
variable for the biogas user model due to the common practice of slurry
application to rice fields. For the pooled and biogas non-user models, slurry is
incorporated as a dummy variable: 1 means slurry is used and 0 otherwise. For
pesticide use, often farmers use pesticides to rescue a crop from pest attack,
while some biogas users do not use pesticides, therefore pesticide use is applied
as a dummy variable for the biogas users and pooled models, and it is used as a
continuous variable for the biogas non-users model.
The general form of the Translog stochastic production frontier for the i th farm
in the pooled and biogas non-user models is defined as:
6
ln y i   0    j ln xij 
j 1
1 6

2 j 1
6

k 1
jk
ln xijk ln xijk   sl SL   pt PEST  vi  u i
(4)
Where the dependent variable y i is the quantity of total rice production (kg per
farm), x i represents the different production inputs and SL , PEST are the dummy
variables for slurry and pesticide use, respectively. The input variables used in
the pooled and biogas Translog production frontiers are: quantity of seed (kg per
farm), quantity of chemical fertilizers (kg. per farm) quantity of labor (man-days
per farm), cost of land preparation and different equipment used (BDT per
farm), quantity of land (acres per farm) and cost of irrigation (BDT per farm).
The random error variables v i and u i are defined above.
19
For biogas users, the following Translog function was developed:
7
ln y i   0    j ln xij 
j 1
1 7

2 j 1
7

k 1
jk
ln xijk ln xijk   pt PEST  vi  u i
(5)
Here, only slurry is added as a continuous variable and the other dependent
variable and independent variables are the same as in Equation (4).

All the input variables in both models are mean-corrected ( xik  x k ) prior to
estimation. This is done so that the coefficients of the first order terms can be
treated directly as elasticities.
The model for technical inefficiency of both seasons can be defined as:
5
u i   0    d z ij  i
(6)
d 1
Here the socio-economic characteristics of the farm used to explain inefficiency
are represented by z i . The socio-economic variables included in the model are:
years of education of the household head, off-farm income (BDT) of a
household, age of the household head, farm size in acres and family size. The
random variable  i is the unobservable random error assumed to be
independently distributed with a positive, half normal distribution.
4.3 Results and discussion
4.3.1 Descriptive statistics of the variables of translog production function
and technical efficiency effect models of Boro production
Table 8 presents the overall rice production by biogas users is greater than that
of biogas non-users and the pooled data. Pooled data in Table 8 explains the
mean value of respective variables as well as shows the statistical mean
difference tests of biogas users and non-users.
Biogas users produce more Boro rice per acre compared to biogas non-users.
But it was not found that significantly more production comes from biogas users
or non-users in the sample areas. The rate of education is also higher than the
national average and finally, biogas users applied slurry for greater production
as well as maintaining soil fertility.
The area of land used for Boro production was found in this study to be 40.13
and 33 decimals for biogas users and non-users, respectively, showing a
significant difference between the two groups. Usually, biogas non-users
20
employ more labor to produce a certain level of Boro production compared to
biogas users, due to often having more weed problems in their fields. Biogas
users are also use less seed compared to biogas non-users. Land preparation cost
implies the use of power tillers or the cost of animal draft that is part and parcel
for land preparation in Boro plantations. In this aspect, biogas users also spend
significantly less money for producing Boro. Considering the summary statistics
of Boro production, biogas users applied inputs more rationally in contrast to
biogas non-users.
Table 8: Summary statistics of the variables used in the production function
Variables
Biogas user
Biogas non-user
Pooled user
Rice production (kg)
1007 (323)
841 (177)
921 (191)
Rice production per
2.53 (0.07)
2.43 (0.04)
2.48 (0.04)
acre (ton)
Land (decimal)
40.13 (8.72)
34.52 (3.33)
37.23* (0.51)
Labor (man-days)
18.72 (8.81)
24.94 (10.48) 21.93** (0.71)
Seed (kg)
9.66 (3.91)
11.73(4.82)
10.73*(0.32)
Chemical
Fertilizer
29.63 (16.15)
71.84 (17.71) 51.41*** (1.94)
(kg)
Irrigation (000. BDT)
1.50 (0.32)
1.29(0.37)
1.39(0.20)
Land preparation and
641 (173)
798 (131)
722** (12)
equipment (BDT)
Slurry per year (ton)
25.95 (2.47)
0
13.01
Farmers
using
92
100
96
pesticide (%)
Note: Figures in the parentheses indicate standard error; and
*, **, and *** indicate significance levels at 10%, 5%, and 1%, respectively.
Table 9 shows that the biogas users predominantly received more years of
general schooling compared to non-users. Biogas users learned for around 10
years where biogas non-users dealt with about 7.43 years of schooling. The
average number of years of education is far more than the national average
(BBS 2011). This significant difference leads to more efficient use of inputs in
agricultural production.
Age could not have any difference between the two groups. Agriculture is a
major source of income, but people want to secure their lifestyle by participating
in other income-generating activities. This study found that farm households
often cultivate their own land for agricultural production.
21
Table 9: Descriptive statistics of the variables used in the technical efficiency
model
Variable
Biogas users
Biogas non-users
Pooled
Education (yr)
10.06 (4.48)
7.43 (4.74)
8.75***(0.35)
Age (yr)
41.71(11.07)
41.47 (10.87)
41.59 (0.79)
Off-farm income
14.72 (13.72)
11.90 (17.37)
13.26**(1.14)
(0000. BDT)
Farm size (Acre)
3.56 (3.73)
2.77 (4.57)
3.24***(0.30)
Family size (No)
5. 37 (2.30)
5.14 (1.98)
5.26(0.15)
Note: Figures in the parentheses indicate standard error and *,**, and *** indicate
significance levels at 10%, 5%, and 1%, respectively.
Table 9 shows biogas users to be cultivating more agricultural land than nonusers at 3.56 acres and 2.77 acres, respectively. Statistics could not find any
difference in mean values of the two groups.
4.3.2 Parameter estimates of the stochastic production frontier
The maximum likelihood method estimates a translog production frontier for
Boro rice, presented in the following. Table 10 presents two types, biogas users,
non-users and pooled users.
-Biogas users: Labor, seed, irrigation, land preparation and equipment and
slurry are found to be significant in Boro production by biogas users. Among the
interaction variables: land × land, chemical fertilizer × chemical fertilizer, land ×
seed, Land × irrigation, labor × seed, chemical fertilizer × slurry, irrigation ×
land preparation have positive significant impacts on Boro rice. But the
interaction of seed × seed, land preparation × land preparation, slurry × slurry,
labor × irrigation, seed × land preparation and irrigation × slurry are negatively
significant for biogas users in Boro production.
- Biogas non- users: Similar to the biogas user Boro translog production
frontier, the biogas non-user production frontier has a good number of
independent factors which have a significant impact on Boro production levels.
Table 10 presents that among the variables land, labor, fertilizer, and pesticides
have positive, significant impacts on Boro production, in contrast to seed and
irrigation, which have negative, significant impacts in the same frontier.
Besides, the interaction effects of seed × seed, land preparation × land
preparation, land × irrigation, seed × chemical fertilizer, seed × land preparation,
chemical fertilizer × preparation and irrigation × land preparation have positive
impacts at 1%, 5% or 10% levels of significance, and oppositely, labor × labor,
22
land × chemical fertilizers, land × pesticide, labor × seed and labor × pesticide
have negative impacts on Boro production at either 1%, 5% or 10% levels of
significance.
- Pooled users: Pooled data could give a better representation of the whole
research area. Table 10 shows that land, labor, irrigation, land preparation and
slurry have positive, significant affects on Boro production, and the other way
around, chemical fertilizer has a negative impact in the Boro frontier production
function. For the interactions of labor × labor, irrigation × irrigation, land
preparation × land preparation, land × land preparation and labor × irrigation
have positive impacts in the Boro production frontier at one of 1%, 5% or 10%
levels of significance. Conversely, the interaction of land x land, land × labor,
labor × seed, chemical fertilizer × irrigation, seed × irrigation and irrigation ×
land preparation have negative impacts in the Boro production frontier with 1%,
5% and 10% levels of significance.
Further, this study used two dummy variables, slurry for pooled users and pests
for biogas users and pooled users. The pesticide impact on the biogas-user Boro
rice production frontier is negative and insignificant. The negative sign of the
coefficient means a loss of production with pesticide application in Boro
production, perhaps linked with the use of lesser quantities than is required
and/or poor quality of pesticide (ANIK, 2012).
4.3.2.1 Interaction impacts of biogas users
The following couple of interactions of inputs have, whether negative or
positive, significant influences on Boro production. The land × land interaction
shows a vital role, at the 1% level of significance, where Boro production could
be extended further by more land. Another interaction, seed × seed, is negatively
significant at the 1% level of significance, meaning that overuse of seed reduces
total production where a plant would not get healthier space for growing. The
co-efficient of the square of land preparation and equipment explains that land is
already well-prepared for production, so it does not need further care for
production. The interaction of slurry × slurry of biogas users is also negative and
significant in its impact on Boro rice production. This means that the land
already receives sufficient use of slurry, and that another pot of slurry will lead
to a reduction of total Boro rice production. Thus, overuse of slurry is observed
to decrease total production.
23
Table 10: Maximum likelihood estimates for parameters of translog stochastic
production function and technical inefficiency effect model
Variable
Biogas users Biogas non-users Pooled users
Coeff.
SE
Coeff.
SE
Coeff.
SE
75.93***
0.97
-62.46***
0.98
14.94**
0.98
Constant
Land (dec)
Labor (man-days)
Seed (kg)
Che. Fert. (kg)
Irrigation (BDT)
Land Prepar. and equipment
(BDT)
Slurry
Pesticide
Land × Land
Labor × Labor
Seed × Seed
Che. Fert × Che. Fert
Irrigation × Irrigation
Preparat. × Preparat.
Slurry × slurry (for biogasusers)
Pesticide × Pesticide (for
non-users)
Land × Labor
Land × Seed
Land × Che. Fert
Land × Irrigation
Land × Preparat.
Land × Slurry (for biogasusers)
Land × pesticide (for nonusers)
Labor × Seed
Labor × Che. Fert
Labor × Irrigation
Labor × Preparat.
Labor × Slurry (for biogasusers)
Labor× pesticide (for nonuser)
Seed × Che. Fert.
0.43***
0.25**
0.037***
-0.067
-0.19**
0.29***
0.22
0.11
0.01
0.84
0.07
0.08
0.44**
0.15***
-0.05**
0.14**
-0.11***
-0.07
0.21
0.01
0.01
0.06
0.01
0.09
*
0.41**
0.17**
-.10
-.10*
0.32***
.24***
0.21
0.07
0.93
0.04
0.12
0.11
0.20**
-0.006
0.59***
0.086
-0.26***
0.11
-0.59
-0.28**
-0.04***
0.10
0.01
0.04
0.08
0.85
0.04
.48
0.13
0.01
0.25*
-0.24
-0.31**
0.23**
-0.37
-0.26
0.92***
-
0.13
0.53
0.12
0.100
0.21
0.15
0.18
-
0.02***
0.01
-0.13*
0.06**
-0.02
-.04
0.28***
0.12*
-
0.006
0.081
0.07
0.03
0.15
0.15
0.06
0.07
-
-
-
-0.05
0.13
-
-
-0.58
0.12*
0.035
0.16*
0.58
-0.88
0.67
0.07
0.36
0.09
0.86
0.53
-0.19
-0.11
-0.65**
0.21**
-0.72***
-
0.10
0.96
0.12
0.09
0.09
-
-.72*
0.77
0.34
0.53
0.13**
-
0.42
0.53
0.33
0.82
0.06
-
-
-
-0.24**
0.09
-
-
0.11***
0.046
-0.116*
0.63
0.02
0.03
0.23
0.061
0.42
0.29
-0.67**
0.33
0.62
0.46
-
0.23
0.57
0.45
0.44
-
-0.28*
0.41
0.77*
0.18
-
0.15
0.33
0.37
0.12
-
-
-
-0.71**
0.25
-
-
0.27
0.20
0.10**
0.044
-0.47*
0.26
24
Seed × Irrigation
Seed × Preparat.
Seed × Slurry(for biogasusers)
Seed × pesticide (for nonusers)
Che. Fert × Irrigation
Che. Fert × Preparat.
Che. Fert × Slurry (for
biogas-users)
Che. Fert × pesticide (for
no-users)
Irrigation × Preparat.
Irrigation × Slurry (for
biogas-users)
Irrigation × pesticide(for
non-users)
Preparat.
×
Slurry(for
biogas-users)
Preparat. ×
non-users)
pesticide(for
-0.48
-0.78*
0.32
0.68
.41
0.37
-0.81
0.14**
-
0.31
0.43
-
-0.47
-0.12
-
0.36
0.24
-
-
-
-0.44
0.27
-
-
0.18
-0.34
0.30*
0.36
0.27
0.16
-0.73
0.24***
-
0.62
0.05
-
-.70***
-0.27
-
0.19
0.26
-
-
-
-0.55
0.65
-
-
0.13**
-0.16**
0.06
0.05
0.24***
-
0.45 -0.24***
-
0.03
-
-
-
-0.12
0.43
-
-
-0.33
0.35
-
-
-
-
-
-
0.49
0.53
-
-
0.37**
-0.02***
0.18
0.01
-0.069
-0.02**
0.174
0.076
0.011 -0.0424**
0.15
0.02
-0.001
0.02
0.029**
0.014
0.0028
0.01
-0.001*
0.000
69
-0.0006
0.006
-0.00265
0.005
0.0016
0.003
-0.0004
0.002
0.00210
0.003
-0.002**
0.001
0.001
0.002
0.00266*
*
0.001
0.016**
0.005
0.039***
0.004
0.25
0.48
0.70***
0.17
Technical inefficiency predictors
Constant
Farm size (Acres)
Family size (No.)
family
head
education
(years)
Age of family head (years)
Off-farm
(0000.BDT)
income
 2   u2   v2
   u2 /( u2   v2 )
Log likelihood function
Total number of observation
0.016***
0.097
0.36
60.49
69.48
58.31
91
97
188
Note: All input variables are mean–differenced prior to estimation and therefore the
coefficients on the first order term can be read directly as an elasticity at the sample mean,
and *,**, and *** indicate significance levels at 10%, 5%, and 1%, respectively.
25
The positive sign of the interaction between land × seed implies that increasing
these two inputs increases total production. If land is extended, it needs more
seed to increase Boro production. The explanation is similar as that of land ×
irrigation, labor × seed and irrigation × land preparation. On the other hand, the
negative sign of the interaction between labor and irrigation means that
increasing one requires the reduction of another to increase output, ceteris
paribus.
4.3.2.2 Interaction impacts of biogas non-users
Labor is significant in linearly and a squared term of labor is negative, making it
confusing whether increasing labor will result in higher output, ceteris paribus.
It might be due to overuse of labor in Boro fields. The interaction of seed
squared and land preparation squared are significant, at the 5% and 10 % levels,
respectively. Proper planting of seed increases total productivity. RUBINOS et al.,
(2007) stated that increasing the seeding rate will lead to closer planting
distance, protecting the plantation from weeds. According to DE DIOS et al.,
(2000) a higher seeding rate is favorable for production where no weed control
is planned. The coefficient of land × chemical fertilizer interaction is negative
at the 5% level of significance while it leads to increasing costs of chemical
fertilizers required to increase total production, ceteris paribus. A similar
explanation is applicable for land × land preparation, land × pesticide, labor ×
seed, and labor × pesticides at significant levels. On the other hand, the
coefficient sign of land × irrigation interaction is positive, meaning that
increasing land and increasing irrigation will increase the production of Boro
rice. This explanation may also apply to the interaction of seed × chemical
fertilizer, seed × land preparation,
chemical fertilizer × land preparation, and irrigation × land preparation with
different significant levels.
4.3.2.3 Interaction impacts of pooled users
The coefficient of land squared is negative, making it confusing whether
increasing land will result in higher output, ceteris paribus. Besides, the value of
the labor squared interaction is positive at the 5% level of significance, making
it clear that increasing labor will result in increased production. This
interpretation is often similar to the interpretation of irrigation squared and land
preparation squared interactions with several significance levels.
The interaction of land and labor is negative at the 10% level of significance,
which states that an increase in the amount of labor is required to decrease the
land area and increase output, also leading to confusion. On the other hand, the
interaction of amount of land and preparation of land is positive with a 5% level
26
of significance, implying that increasing the amount of land with good
preparation of land leads to more output. The interaction value of irrigation and
chemical fertilizer is negative at the 1% level of significance, meaning that
increasing the cost of irrigation with an increase in chemical fertilizer use may
reduce total production for pooled users.
4.4 Determinants of technical inefficiency
The lower section of Table 10 presents the results of a technical inefficiency
effect model for biogas users, biogas non-users and pooled users. Only farm size
has a significant effect on the inefficiency for the three groups. Among other
inefficiency variables for biogas users, years of family-head education and offfarm income significantly affect farm inefficiency. For the biogas non-user
group, family size is seen to have a notable impact on the inefficiency of Boro
production and finally, for the pooled user group, off-farm income has a
significant influence on efficiency in this model.
Farm size, for all groups, is significant at the 1% to 5% levels and the coefficient
values are negative, implying that households become more efficient with
increasing farm size.
The number of years of education obtained by a family head, compared to
efficiency in Boro rice production shows a significant relationship only with
Biogas users, the other two groups show no significant relationship. The result
implies that increasing education reduces the inefficiency for the biogas user
group.
Biogas user households are negatively related with inefficiency at the 5% level
of significance. In addition, for pooled users, off-farm income has a positive
relationship with inefficiency of Boro production. This result can also be
explained in another direction - earning more off-farm income reduces
efficiency. One argument for this issue is that households participate more in
off-farm activities and pay less attention to rice product on. Both user and nonuser groups were noticed having more household income per year compared to
the national average. Also, biogas user households want to ensure their food
security first and then give their remaining time to non-farm activities.
4.5 Technical efficiency in Boro rice production
The summary statistics of technical efficiency of Boro rice production are
presented in Table 11. The mean technical efficiency scores are 0.91, 0.87 and
27
0.78 for biogas users, biogas non-users and pooled users, respectively. The mean
technical efficiency of other previous studies was also found to be at high levels
of efficiency in Boro rice production in Bangladesh. The efficiencies of this
study are more or less similar to the studies of WADUD and WHITE (2000);
RAHMAN (2003), ASSADULLAH and RAHMAN (2006), BALA et al., (2010); MIAH
et al., (2010); and ANIK (2012).
Table 11: Technical efficiency in Boro rice production
Variable
Biogas users
Biogas non-users
Efficiency level
Up to 70%
2.20
3.30
70-80%
12.09
19.68
80-90%
16.48
29.47
90% and above
69.23
53.55
Efficiency Score
Mean
0.91
0.87
SE
0.01
0.01
Min
0.62
0.57
Max
0.98
0.98
Pooled users
35.64
18.09
19.68
26.60
0.78
0.014
0.313
0.99
Source: Author’s calculation (2013)
4.6 Profitability of Boro rice production
Table 12 presents the total costs, total revenue and finally accounts the gross
margin with statistical differences. There are notable significant differences in
cost of labor, seed, land preparation, chemical fertilizer, pesticide, total cost,
gross margin and BCR at the 1% and 5% levels between biogas users and biogas
non-users, besides, there was not find any statistical differences of land,
irrigation and total revenue.
It could be stated that slurry practice reduces the manifold cost items in Boro
rice production in Bangladesh. Households are often relieved of the heavy
burden of chemical fertilizers, pesticides and labor costs through practicing bioslurry application. Thus, farmers should be encouraged to produce more rice to
meet the deficit in supply of food in Bangladesh. Similarly, it also tends to lead
to organic production and this will encourage farmers to cultivate organic crops.
28
Table 12: Summary of input values, gross margin and BCR of rice production
(per acre)
Biogas users
Biogas non-users
Variable
Mean
SD
Mean
SD
Labor cost (BDT)
7783***
2576
9529
3830
Seed cost (BDT)
788***
161
1045
745
Land preparation (BDT)
1669***
645
2514
570
Slurry cost (BDT)
1669
536
Chemical fertilizer cost (BDT)
1891***
1767
4067
1496
Irrigation (BDT)
4266
2195
3850
1922
Pesticide cost (BDT)
815***
600
1125
733
Total variable cost (BDT)
19343***
4588
22232
5371
Total revenue (BDT)
42969
7669
42605
8258
Gross margin (BDT)
23626**
8134
20372
6741
BCR
2.32***
0.06
1.99
0.04
Note: *,**, and *** indicate significant difference of the two samples at 10%, 5%, and 1%,
respectively.
Thus, It could be stated that slurry based boro rice is more profitable than
chemical fertilizer based rice production.
29
5 COST-BENEFIT ANALYSIS
5.1 Introduction
This chapter is considered five assumptions for accounting of costs and benefits
under various conditions, as well as five scenario characteristics also included to
provide some uncertainty analysis regarding on biogas energy in Bangladesh.
The objective is to assess the economic viability of biogas energy production of
family-size digesters, attempting to take into account all the costs and benefits
accruing to overall biogas production in Bangladesh. Households need to
estimate how sustainable it is to produce and utilize biogas, relative to
alternative energy sources, based on their resource endowments.
In this analysis, a broad estimation of costs of the most common biogas plant
capacity designs (2.4 m3, 3.2 m3 and 4.8 m3) is undertaken, followed by the
economic valuation of benefits of this technology.
5.2 Analytical Approach of cost-benefit estimation model
5.2.1 Financial evaluation
Small-scale biogas plants are often justified on the basis of the private cost and
benefit accruing to the individual household (SRINIVASAN, 2008). A financial
cost-benefit analysis takes account only of the costs and benefits of the project
to the private farm - its effect on revenues and costs and ultimately attention to
getting maximum profit.
Financial estimation of a biogas plant includes four assumptions: with subsidy
(base assumption), without subsidy, health facility issues, and income generating
issues. In this study without subsidy means a situation where no outreach
incentive is incorporated into the calculation of a biogas plant, rather, the normal
manner a human uses for incentives for adopting new technology. Without
subsidy estimation of a biogas plant gives the real lesson too society for the
adoption of biogas. Hence, to know the actual cost to be incurred for installation
of a biogas plant, any subsidy money is subtracted from the calculated cost of
each capacity and each model.
Expanding new technology needs new initiatives to encourage people to adopt,
like subsidy, a very strong instrument urging people to make the decision in
favor of new technology adoption.
The use of biogas has contributed to notable benefits regarding health, socioeconomic status, women’s and children’s work load, plus agricultural and
30
environmental issues. Households have stated significant benefits resulting from
reduced air pollution and associated eye and respiratory diseases. The
atmosphere has become cleaner, a positive impact on the health of households
(IDE, 2011). Thus, biogas users pay less money for medical purposes due to
imroved health.
5.2.2 Economic evaluation
In contrast, economic cost-benefit analysis takes a wider or more social
perspective - it measures and compares the costs and benefits experienced by all
members of society. DINWIDDY and REAL (1996) illustrate that earlier, costbenefit appraisal methodology was typically applied to industrial and
agricultural projects for society’s interest. Now it includes the external factors
like the cost of environment pollution, natural resource management,
employment generation and poverty alleviation, whose effects are termed social
costs and benefits to distinguish them from purely private costs and benefits of a
project. Finally, economic cost-benefit analysis is applied to appraise private
projects from a social point of view as well as to appraise public projects
(CAMPBELL and BROWN, 2003).
Biogas technology is also associated with positive externalities to serve the wellbeing of the society. It reduces the emission of CO2, CH4, and NO that
ultimately contributes to diminishing global warming (LOVRENCEC, 2010).
In this section, the carbon trading issue is considered in economic assumption
evaluation in this section.
PEAR (2010) proposed that estimated GHG emission reduction from biogas is
3.82 tons of CO2/household/year and the price of CO2 emission reduction is 10
$/ton. PEAR (2010) estimated Grameen Shakti was involved with construction of
about 15,000 small-scale biogas plants since 2006 throughout the country
(GRAMEEN SHAKTI, 2012). In this analysis, GHG emission reduction accounts for
3.0, 3.8 and 5.0 tons of CO2 for 2.4 m3, 3.2 m3 and 4.8 m3 capacity plants,
respectively, with the price of reduction charged at 10 $/ton.
5.3 Economic viability of energy production from a biogas plant
After quantification and valuation of the costs and benefits of biogas technology,
four economic decision criteria are used in the analysis for analyzing economic
viability, including net present value (NPV), internal rate of return (IRR),
payback period (PBP) and net benefit increase (NBI).
31
5.3.1 Net Present value (NPV)
Net present value (NPV) is a way of comparing the present and future values of
cash flows by using the discount rate and a time constraint. It refers to the sum
of the present values of each year’s net cash flow, less the initial cost of
investment (TORRIES, 1998; BRIGHAM and EHRHARDT, 2011).
The useful economic life of a fixed-dome domestic biogas plant is assumed to
be up to 15 years, similar with the considerations of VAN EIJE (2012). In
Bangladesh indeed, biogas activities are run by IDCOL with the support from
Netherlands Development Organization (SNV). Both IDCOL and SNV
considered the length of time to be 15 years for a biogas digester in Bangladesh.
Assuming the initial flow means the initial investment cost I0 is always negative
and not discounted (TORRIES, 1998; BRIGHAM and EHRHARDT, 2011). The
equation for NPV can be written as:
 n CFt 
NPV  
 I 0 …………………………………….(7)
t 
 t 1 (1  t ) 
Source: (TORRIES, 1998. pp 39)
Where, CFt, I, n, and I0 represent cash flow in year t, discount rate and the total
number of years for project and initial investment cost, respectively. A project
will be accepted if the value of NVP is positive (>0) from both an financial and
economic point of view but if NPV is negative (<0) then the project will not be
accepted by private owners, economic analyzers then have to consider several
externalities to decide whether adopt or not.
5.3.2 Internal rate of return (IRR)
Internal rate of return (IRR) is a financial analysis tool that estimates the interest
which would make the present value of a stream of net cash revenues equal to
zero (TORRIES, 1998; BELLI et al., 2001). It is calculated as:
n
CFt 
NPV  0  
 I 0 ………………………………….(8)
t 
 t 1 (1  IRR ) 
Source: (TORRIES, 1998. pp 39; BRIGHAM and EHRHARDT, 2011, PP 381)
Where, i is the internal rate of return, If the IRR is higher than the discount rate
of return, it means the investment is profitable and people can further continue
business activities. Thus, the decision rule is that if the IRR is greater than the
discount rate or opportunity cost of capital, the business will be profitable and
NPV will also be positive (DRURY, 2008).
32
5.3.3 Payback period (PBP)
Payback period (PBP) refers to the number of years it would take for an
investment to return its original cost of investment through the annual net cash
revenues it generates (GROPPELLI and NIKBAKHT, 2006; BALAKRISHNAN, et al.,
2009; HANSEN and MOWEN, 2009). If the net cash revenues are constant each
year, the PBP can be calculated as:
PBP= TI/NR
(9)
Where, TI= Amount of total investment, NR= Annual net revenue (profit) which
is annual gross income less annual operational cost. Where the net cash revenues
are not equal, it should be summed year by year to the year where the total is
equal to the amount of investment. A short PBP is more preferable for an
economic activity. In this study, annual net revenue is assumed to be equal and
undiscounted payback period (IPBP) is also used in the analysis (except
considering the interest accrued for two years ) because a constant rate is
suitable for computations where annual benefits and annual operating costs are
assumed uniform over the lifespan of a project. It is calculated as:
PBP= (last year with a negative NCF) + (Absolute value of NCF in that year/
Total cash flow in the following year)
(10)
Where, NCF presents net cash flow. The shortest PBP is always preferable for a
new project installation.
The PBP is useful in assessing, appraising and controlling risk, minimizing the
impact of an investment on a firm’s liquidity and minimizing the risk of
obsolescence (HANSEN and MOWEN, 2009, PP 940).
5.4 Systematic profile of costs and benefits of biogas plants
Data on inputs for the adoption of a fixed-dome biogas plant are mainly
obtained from the household survey. The costs of investment and maintenance
of a biogas digester are related to the specific type and size of the digester
(CAEEDAC, 1999). These include investment cost and operating and
maintenance (O&M) costs.
5.4.1 Costs of a biogas plant
Investment cost and current variable cost are estimated for total cost and a very
limited example of negative externalities is illustrated in below:
33
5.4.1.1 Investment cost
As mentioned earlier, the sizes of domestic biogas plants based on the
recommendations of IDCOL are 2.4, 3.2 and 4.8 m3 functioning in rural areas of
Bangladesh. Table 13 presents that the investment cost of a large biogas plant is
higher than a medium plant, followed by a small plant.
Table 13: Cost and capacity of biogas plants
Variable
Different types of plants
Mean
3
Size (m )
Small (2.4) Medium(3.2) Large(4.8)
3.19
Investment Cost
29949
31909
41972 33692
(BDT)
Loan received
21249
24904
32563 24762
(BDT)
Subsidy (BDT)
8700
8964
8954 8830
SE
0.076
560
4434
130
Source: Author’s calculation (2011)
Usually IDCOL has been endorsing a subsidy of 9,000 BDT to each domestic
biogas plant since 2005-2006, but the existing study has observed that
households received on average 8,830 BDT, in addition to being offered another
facility of soft loans with only 8% interest with a simple rate. On average, the
households’ received loans of about 24,762 BDT.
5.4.1.2 Operating and maintenance costs
Acquisition of the raw materials for the substrate, water for mixing materials,
feeding and operation of the plant, regular maintenance, supervision, storage and
disposal of the slurry, gas distribution and utilization, and administration are
some of the O&M costs associated with continuing operation of a biogas plant
(CAEEDAC, 1999).
A biogas plant is sited within the homestead near the cattle station. This makes
the task of collecting the dung or poultry litter for the plant very easy and
simple. So, the cost of family labor for this purpose has been omitted in the
present analysis because not so much labor is required in biogas energy
production. Each biogas user household has at least one drinking tube-well in or
around the house. Hence, the cost of water has not been considered in in this
study.
The cost of fresh dung input for family-sized biogas plants, especially where
cowdung is bought, is considered as the main operating cost. Where it is not
purchased, its economic cost could be estimated on the basis of monetary worth
of (a) equivalent amount of fertilizer saved, (b) equivalent amount of fuel
34
purchased (such as fuel wood, agricultural wastage, kerosene, etc.), and (c)
collected fuel wood (SINHA and KANDPAL, 1990; SINGH and SOOCH, 2004;
PUROHIT and KANDPAL, 2007). An average price derived from the survey results
as the maximum price the household is willing to pay for the cow dung used to
estimate the cost of fresh dung.
In this study, partly following KANDPAL et al., (1991), a figure of 4% of the
capital cost is assumed to be adequate for the maintenance cost because the
approximate cost of these and other routine maintenance costs have been shown
to be roughly proportional to the capital costs of the plant capacity.
Note that the annual maintenance cost and depreciation cost are considered to be
about 4% of the capital cost of the plant. Hence, once the capital cost is known,
the total annual maintenance cost, Mc, for a biogas plant of capacity V m3 can be
estimated as:
Mc= 0.04C
(11)
Dc=0.04C
(12)
Where Mc and Dc are the annual maintenance and depreciation costs for a biogas
plant of capacity V m3, respectively, and C is its total investment cost. The total
annual operating and maintenance costs (AOTc), for a plant of capacity V m3
with capital cost C, could thus be:
AOTc= 365WPwdu + Mc + Dc
(13)
Where W is quantity (kg) of wet dung required to produce 1 m3 of gas, Pwdu is
the price of the dung in BDT/kg and 365 refers to the days in a year. The cost of
dung is considered to be worth 0.18 BDT/kg. Because the fresh cowdung has
opportunity cost, the price of cowdung per kg in Bangladesh follows SINGH and
SOOCH (2004) using RS 0.1251. The cost of depreciation and maintenance are
furthermore calculated as fixed percentages of the capital costs (KANDPAL et al.,
1991).
5.4.2 Benefits of a biogas plant
Quantification of the benefits of a biogas system is a crucial step in the
economic viability evaluation of biogas generation. The benefits accruing from
establishing and running a biogas digester fall into two basic categories:
monetary and environmental. The monetary benefits are saved costs on fuels
substituted by biogas, and on fertilizer costs substituted by digester slurry
1
1 Indian Rupee= 1.44 BDT
35
(BISWAS and LUCAS, 1997; PUROHIT and KANDPAL, 2007). Environmental
benefits included several other indirect benefits like less CO2 emission. Biogas
could serve for benefits through the connection to greenhouse gas (GHG)
release from open decomposition of animal wastes and avoided CO2 release
from burning firewood (SRINIVASAN, 2008). Furthermore, reduced use of
firewood as an ultimate result of biogas use protects from deforestation.
Attributing market prices to the major benefits of biogas plants, the biogas and
digester manure (slurry) and other indirect benefits are rather difficult to
estimate (DAXIONG et al., 1990; SINHA and KANDPAL, 1990; KANDPAL et al.,
1991). Some households don't appreciate the monetary value of biogas
production because having adequate supplies of biomass at almost no cost, they
attach little or no value to the time spent gathering the biomass (SINHA and
KANDPAL, 1990; BISWAS and LUCAS, 1997). Hence, it is essential to find an
indirect method to evaluate the benefits, and the most logical method is to place
market values in term of alternative fuels for a given end-use (KANDPAL et al.,
1991; RUBAB and KANDPAL, 1995; SINGH and SOOCH, 2004).
The opportunity of renewable energy like biogas technology can be evaluated on
a random basis considering technology and its use. Thus, there is no universal
method to evaluate the benefits of biogas use, (ISLAM and ISLAM, 2005) where
research could follow a rational strategy for assessing the benefits of biogas use.
5.4.2.1 Valuation of a biogas plant
The benefits of a biogas system in this study are estimated as the equivalent
quantity of agricultural waste use, including rice hulls, rice straw, jute sticks,
fuel wood, and dry dung, etc. BALA and HOSSAIN (1992) evaluated the
economics of domestic biogas plants in Bangladesh by means of the value of
firewood and fertilizer.
In this study it is assumed that with the beginning of biogas generation, the dung
previously used directly for cooking and heating purposes or as farmyard
manure, is reserved for the generation of biogas energy as well as the release of
slurry.
In this study, the benefit of biogas is estimated by how much money is spent on
firewood, agricultural wastes and dry dung. The following Equation 14 is used
for calculating the benefits of biogas:
Bb  ( B pp  B pe )(C f  Cab  Cdd  Cot )
(14)
36
Where Bb, Bpp , and Bpe represent total benefits of biogas per year, previous cost
of biomass items per year, and existing cost of biomass items per year,
respectively, Cf, Caw, Cdd and Cot denote major cost items of biomass like
firewood, agricultural by-products, dry dung and other biomass per month,
respectively.
5.4.2.2 Valuation of slurry as organic fertilizer
If composting is appropriate, farmyard manure will have almost the same N, P
and K values as fresh manure (RUBAB and KANDPAL, 1995) and the quantity of
residual slurry is the same as that of the cow dung fed into a biogas plant (SINHA
and KANDPAL, 1990).
In this study, the total benefits from slurry used are accounted for by the money
saved per year by reducing application of chemical fertilizer. But, it is
inconvenient to calculate the exact N, P and K saved by reducing use of
chemical fertilizer. Therefore, the benefit from slurry-use is calculated as:
Bs= (TCcp-TCcc)- TCS
(15)
Where Bs represents benefits from slurry used, TCcp, TCcc, and TCs represent the
total cost of previous chemical fertilizers used per crop yield, the total cost of
current chemical fertilizers used per crop yield, and the total cost of slurry used
per crop yield, respectively.
TBb= Bb+Bs
(16)
TBb accounts for total benefits from using biogas technology, Bb denotes the
direct benefits of gas from biomass.
5.6 Summary of all assumptions of costs and benefits of a biogas
plant
The explanation of several assumptions on costs and benefits of biogas plant in
Bangladesh has already implicitly delivered. It could be difficult to recall several
assumptions of the costs and benefits of biogas. The following assumption is
often adopted from previous empirical studies, and the above implicit
explanation is summarized:
 In General:
a) Three types of biogas plants have been observed: 2.4 cubic meter, 3.2
cubic meter and 4.8 cubic meter.
37
b) The price of land occupied by biogas plant is not accounted for in cost
items.
c) Households have access to credit and subsidy facilities.
d) NGOs are strict in payment of 25% of total investment as a down
payment and the remaining money being paid in 24 monthly
installments with an 8% fixed rate interest.
e) Four decision-making tools included are NPV, IRR, PBP and NBI,
applied to examine the future nature of biogas technology in
Bangladesh.
f) Four assumptions under financial evaluation and one assumption under
economic evaluation, in total, five assumptions of cost-benefit analysis
of biogas plants have been observed through decision-making tools.
 Annual O&M costs of a biogas plant
a) Labor cost is not considered for estimation of total cost of a biogas
plant.
b) Cowdung cost is assumed at 0.18 BDT per kilogram.
c) O&M (repair, maintenance and replacement) and depreciation costs are
assumed to be 4% of the total investment cost.
 Annual benefits of biogas
a) The monetary benefit of gas is estimated by the difference in previous
and existing costs of biomass items due to unavailability of measurable
indicators.
b) The monetary benefit of slurry is calculated by the difference between
previous and existing costs of chemical fertilizers, plus the cost of slurry.

Decision-making tools
a) Four decision making tools: NPR, IRR, PBP and NBI are used to appraise
the long-term business of biogas technology in Bangladesh.
b) Discount factor, interest rate and duration of plant functionality are
assumed to be 12%, 8% for two years and 15 years, respectively.
38
5.7 Results and discussion
5.7.1 Assumption Analyses
In this study, biogas plants are divided into three groups - small (2.4 cubic
meter), medium (3.2 cubic meter) and large (4.8 cubic meter) plants.
5.7.1.1 Current costs of a biogas plant
The bulk of capital cost is comprised of civil construction and labor costs. Thus,
one could assume that the larger the capacity of the biogas plant, the higher the
costs of installation and operating the plant (Table 14). The cost of dung is
considered in terms of monetary value - 0.18 BDT/kg adapted from SINGH and
SOOCH (2004). Maintenance as well as depreciation costs account for 4% of
investment costs.
Table 14: Estimation of annual current costs for small scale biogas plants
Name of the component
Biogas plant capacity
Small
Medium
Large
Mean
Cowdung applied (kg/day)
78.28
83.28
94.16
82.22
(63.49) (43.41)
(79.51)
(55.68)
Cowdung cost (BDT/year)
5143
5471
6186
5402
Maintenance cost (BDT/year)
1197
1354
1727
1358
Depreciation cost (BDT/year)
1197
1354
1727
1358
Total cost (BDT/year)
7538
8181
9641
8118
Note: Figures in the parentheses are standard deviations
Source: Author’s calculation (2012)
5.7.1.2 Current benefits of a biogas plants
The total avoided cost of biomass products are counted as benefits of a biogas
plant. The following Table 15 shows the monthly payment for biomass
production before the introduction of a biogas plant. The reduced cost of
chemical fertilizers is accounted for using the cropping intensity of Bangladesh.
Currently, the cropping intensity of Bangladesh is about 191%, meaning about
two crops are cultivating in a year across the country (BBS, 2011). Table 14
illustrates how the major biomass cost items with residual benefits are
considered for the total benefit of biogas plants, including the cost of
agricultural by-products, dry dung cake and firewood, followed by the benefit
from slurry sales and reduced chemical fertilizer costs.
In sum, except the chemical fertilizer reduced cost, the mean costs differences of
the remaining variables are statistically significant in the three cases. It is
39
recognized that biogas is a profitable business where medium & large plants
have significant differences between them. The sum of mean annual benefits for
all is found to be a notable amount in the context of Bangladesh where firewood,
dry cake, agricultural by-products, chemical cost reduction and slurry
contributed about 27%, 9%, 30%, 6% and 28%, respectively (Table 15). Biogas
plant users also saved a good amount each year. So, from the cost items side of
biomass, the contribution to the total benefit of using a biogas plant is 66%
(27% + 9% + 30%) while the residual 34% comes from the direct and indirect
benefits of cowdung use. Chemical fertilizer is used as a substitute for bio-slurry
which, on average, reduced cost by 1,129 BDT per year in Bangladesh. A case
study in Pakistan revealed that slurry can reduce chemical fertilizer use to an
amount of 600 PKR per month (AMJID et al., 2011). In Nepal, ASHDEN AWARDS
(2005); and GAUTUM et al. (2009) also reported that slurry reduced household
dependence on imported chemical fertilizer and helps to save a total amount of
about $300 nationally, providing an opportunity to use indigenous technology.
Table 15: Estimation of annual current benefits of biogas plants (BDT/year)
Items
Biogas plant capacity a
Average b
(%)
Small
Medium
Large
Firewood
4560 (2901) 5185 (3582) 5054 (1052)
5212 (27)
Dry dung cake
1804 (1526) 1814 (1592)
1363 (461)
1750 (9)
Agricultural by5368 (2278) 4600 (2481) 6709 (1107)
5600 (30)
product
Reduce cost of
1238 (1419)
942 (1203)
1095 (886)
1129 (6)
chemical fertilizers
Slurry
5143 (348)
5471 (670) 6186 (1215)
5402 (28)
Total benefit
18113 (3662) 18013 (5093) 20408 (2949) 19093 (100)2
Profit
10574 (2446) 9832 (4550) 10767 (2856)
10391
a
b
: Figures in the parentheses are standard deviations.
: Average means average of each item of biomass .
From the results in Table 15, it also appears that firewood, agricultural waste
and slurry utilization play a major role in the benefits of all categories of biogas
users in Bangladesh. Finally, the highest benefit of biogas utilization was
ensured by large biogas plants followed by small and medium biogas plants.
Large scale plants can spread the greater benefits as well profit over the country.
Both cost and benefits of a biogas plant in Bangladesh as presented in Table
15showing that biogas is a profitable business considering the specific cost and
benefit items involved in the calculations.
2
Percentage share of total benefit of a biogas plant
40
The following section presents the assumption analysis with different aspects of
financial and economic issues.
5.8 Estimation of financial evaluation
As mentioned earlier, financial estimation only considers the direct costs and
benefits of a biogas plant for the interest of individuals, not including some other
external costs and benefits. Here also four categories including small, medium,
large and average biogas users are considered for calculation with the discount
rate 12%, interest paid to the NGOs at 8% for up to 24 installments on a
monthly basis and lifespan of 15 years for a plant.
5.8.1 With subsidy
The base calculation of a decision-making instrument is treated as the first
assumption in this study. As a general trend, the values of NPV of operating
biogas business in Bangladesh for all categories of biogas plants users in this
study are notable positive signs.
Table 16 presents that the estimated value of NPV for small, medium and large
biogas users are mostly similar and comparable to VON EIJE (2012) who also
found NPV in Bangladesh to be about 500 Euro or about 50,000 BDT per biogas
plant.
Table 16: NPV, IRR, PBP and NBI of different biogas plants with subsidy
Name
NPV (BDT)
IRR (%)
PBP (year)
Small plant
49005
46
2.25
Medium plant
51669
34
2.97
Large plant
38985
30
2.45
Mean
43855
39
2.64
Source: Author’s calculation (2012)
IRR also responds more than the discount rate, so it leads again to a positive
sign for adopting the business for all categories of biogas users. VON EIJE (2012)
also measured an IRR in Bangladesh of about 45%.
Under the assumption with subsidy, Table 16 shows that small-scale biogas
users obtain better financial results compared to other groups according to IRR
and PBP. On the other hand, medium-scale users are in a strong financial
situation on the basis of NPV and NBI and only large-scale biogas users have no
better financial situation compared to the other two groups. Therefore,
considering subsidy distribution to biogas users, small and medium-scale users
having more advantages compared to large-scale biogas users in Bangladesh.
41
5.8.2 Without subsidy
Table 17 shows the decision-making activities of different groups of biogas
users in Bangladesh without subsidy.
Table 17: NPV, IRR, PBP and NBI of different biogas plant without subsidy
Name
NPV (BDT)
IRR (%)
PBP (year)
Small plant
40464
33
3.07
Medium plant
38276
32
3.19
Large plant
30194
23
4.24
Mean
31751
25
3.94
Source: Author’s calculation (2012)
Under the assumption without subsidy, biogas users obtain on average 31,751
BDT. Considering the groups of users, the small biogas plant users’ NPV
(40,464 BDT on average) is higher than the medium-sized biogas plant users’
NPV (38,276 BDT on average), which is also higher than the large biogas plant
users’ NPV (30,194 BDT on average). Still, on average, IRR is to found to be
higher than the existing 12% discount rate. Nevertheless, all categories of
biogas plant users can continue their business as profitable enterprises. This
result is similar to previous findings in developing countries such as Ethiopia,
where the cost-benefit analysis of biogas plants highlighted a positive NPV for
households collecting their own energy sources, and results are highly
dependent on slurry being effectively used as a source of fertilizer and on the
price of replaced energy sources (GWAVUYA, et al., 2012). Biogas plants are
highly subsidized and without subsidy the plants are also profitable in nature in
Ethiopia. Hence, small biogas plant users will receive more benefits considering
decision-making tools like NPV, IRR, PBP and NBI compared to other two
groups.
Finally, it may be recognized on the basis of the above analyses of with and
without subsidy projects considering the three decision-making tools shown that
small-scale biogas projects in rural areas in Bangladesh should be established in
future.
5.8.3 Health benefits
Health benefits from reduced smoke exposure and particle concentration
indoors, resulting in reduced acute respiratory infections and eye ailments, as
well as lower infant mortality rates (ACHARYA et al., 2005).
Thus, the potential to motivate people to make the decision for adoption of
biogas plants due to health benefits is one of the major reasons in the selected
areas of Bangladesh. The average annual savings from medication by using a
42
biogas plant are found to be 1,040 BDT, 850 BDT and 655 BDT for small,
medium-sized and large biogas plants.
Table 18: NPV, IRR, PBP and NBI of different biogas plant with health benefits
Name
NPV (BDT)
IRR (%)
PBP (year)
Small plant
47314
36
2.80
Medium plant
48658
38
2.68
Large plant
34652
25
4.01
Mean
37881
27
3.64
Source: Author’s calculation (2012)
Table 18 shows that medium-sized plants performed better in terms of health
benefits than small plants, followed by large, considering the value of NPV. All
the decision-making tools show that large biogas plants received less value in
comparison to the other groups, nevertheless, these plants could also be
profitable in the future. PBP of medium plants is 2.68 years, whereas large and
small plants are paid back in about 4.01 and 2.80 years, respectively.
5.8.4 Surplus time used for income generation
Rural women and children are found to be more punctual in enhancing the
business of biogas plants in rural areas of Bangladesh. A way to reduce
traditional biomass energy consumption can lead to saving time and offering
better opportunities. These persons could distribute their saved time and utilize it
for other productive purposes including preparing handicraft products, more
involvement in agricultural activities, giving more time to small business,
livestock rearing, home gardening, better care toward child education and
recreation, etc. The present study found that the average annual income from a
small, medium and large plant to be 15,585 BDT, 16,001 BDT and 16,773 BDT,
respectively. Table 5.8 shows a comparison of three biogas plant groups
including the time savings for income generation. Small plant owners are more
productive, in NPV, IRR, PBP and NBI by 146,381 BDT, 84%, 1.20 year and
21,792 BDT, respectively. Similarly, large biogas plant owners have the least
productivity in comparison to the other two groups (Table 19). Besides,
medium-sized plants perform medium-wise concerning all decision-making
tools. The remarkable benefits are found from the socio-economic character of
using biogas. The present study found that the maximum financial benefits
originate from saved time from using a biogas plant. IDE (2011) also found
similar benefits such as 300 households in one year saved up to 23,816 working
days by reducing the time required for cooking and management of fuel.
43
Table 19: NPV, IRR, PBP and NBI of different biogas plants under time surplus
for income generation
Name
NPV (BDT)
IRR (%)
PBP (year)
Small plant
146381
84
1.20
Medium plant
141674
74
1.38
Large plant
140715
59
1.83
Mean
138792
64
1.65
Source: Author’s calculation (2012)
Comparing the above Tables 16 to Table 19, Table 19 shows better performance
results on the basis of NPV, IRR, PBP, and NBI, and also presents in-depth
assumption analysis of several income-generating activities that could be
involved in saving time by using a biogas plant. Consideration of income
generation from saved time gives recognition to biogas users having opportunity
to improve their livelihoods.
5.9 Estimation of economic evaluation
5.9.1 Carbon trading
The Clean Development Mechanism (CDM) is one of the “flexible
mechanisms” under the Kyoto Protocol. It provides for industrialized countries
to invest in emission-reducing projects in developing countries and to use (part
of) the resulting “certified emission reductions” toward their own compliance
with the emission limitation target set forth by the Kyoto protocol
(SCHLAMADINGER and JÜRGENS, 2004).
MULLER et al., (2012) stated that agriculture is currently responsible for 20-30%
of global greenhouse gas emissions (direct and indirect agricultural emissions).
Thus, biomass has often been a part of agricultural activity that is a major cause
of releasing GHG by producing the CO2 throughout the world. It has been
determined that biogas has the capability to produce less CO2 emissions into the
atmosphere. BHATTACHARYA et al., (2002) examined emission factors for CO,
CO2, CH4, total non-methane organic compounds (TNMOC) and NOx of
traditional and improved biogas stoves in Asian developing countries, and
conclude that as the efficiency of cooking stoves increases, the emission factors
in grams per useful biomass energy unit used, for all pollutants, decline. For
participation in carbon emission reduction projects, Grameen Shakti is a major
partner organization of IDCOL and has already submitted the required
documents for registration with the United Nations Framework on Climate
Change (UNFCC) on carbon trading across the developed world. After getting
the registration, CO2 emissions could be sold and would earn foreign currency to
44
distribute to a major portion of the incumbent biogas users. It has been assumed
in this study that small, medium-sized and large farms would reduce by 3.00,
3.80 and 5.00 tons their CO2 emissions, and earn 2,400 BDT, 3,040 BDT and
4,000 BDT per year, respectively. There are substantial reductions in the
emission of greenhouse gases as less firewood and kerosene are used. In Nepal,
BSP estimates also find a net reduction of 4.7 tons/year of CO2 equivalent per
plant, or 660,000 tons/year for all the plants installed to date (UNCTAD, 2010).
Thus, biogas users provide two-fold benefits concerning the issue of earning
foreign currency as well as preparing for a sustainable environmental
atmosphere all over the world. Table 6.10 shows that medium-sized biogas
plants were found to provide better results compared to the other two groups.
Concerning the value of NPV, IRR, PBP and NBI, medium-sized plants
performed a bit better compared to others. Each size of plant is capable of a
payback of the total initial investment in less than 3 years while continuing to
provide value for 15 years. Each group results in more than the existing 12%
discount rate. Plants can thus be run as profitable businesses into the future.
Table 20: NPV, IRR, PBP and NBI of different biogas plants under carbon
trading
Name
NPV (BDT)
IRR (%)
PBP (year)
Small plant
56809
41
2.50
Medium plant
63573
41
2.52
Large plant
59192
34
2.98
Mean
53658
34
2.95
Source: Author’s calculation (2012)
Considering all assumption analyses, Biogas plants can be installed throughout
the country wherever there are a sufficient number of cattle or poultry. As
mentioned previously, biogas has a lot of multidimensional advantages, internal
and external, social and economic, direct and indirect. The following Figure 5
presents the mean value of different decision-making tools including NPV, IRR,
PBP and NBI: all suggest that the positive potential to install at least one smallscale biogas plant in or around the home.
45
140.00
NPV (000BDT)
120.00
IRR (%)
Values
100.00
80.00
PBP (year)
60.00
NBI (000 BDT)
40.00
20.00
0.00
without
subcidy
with subcidy
Health
benefits
time savings
Carbon
trading
Different scenarios
Figure 5: Mean value of NPV, IRR, PBP and NBI of biogas plants in
Bangladesh
Household members, especially women will have more time for economic
activities and to enlarge family income as shown in Figure 5. Thus, income
generation from time savings gives the highest NPV, IRR and NBI and the
lowest PBP compared to the remaining variables.
The study finally concludes that money can be invested in biogas plant
installation in Bangladesh to help alleviate serious energy disturbances across
the whole country, especially in rural areas. It would be good renewable
technology instead of traditional cooking and lighting systems: Protecting the
soil from degradation, increasing children’s education, providing for more
income-generating activities and sustainable environmental atmosphere. The
country will be benefited in several dimensions in the long term.
46
6 Policy recommendations
The following recommendations can be further adopted for betterment of rural
households as well as societal aspects based on the results of the study.
i. Message to the literate households
The study showed that education has influential power in adoption of biogas
technology, as well as an impact on farm production efficiency. Educated people
are mostly professionals engaged in non-farm activities by which they earn more
money and look for healthy environments and better livelihood. Thus, there is a
need for service providers and regulatory bodies to find literate people who have
the ability to understand the reality of current problems and install biogas plants
around the home.
ii. Sex appreciation
Though, Women would often be main beneficiary of using biogas plants in a
household. This study revealed that women can save time through reduced
firewood collection and using a biogas plant and utilize this time for other
income-generating activities that make for better livelihood. Households,
especially women, obtain better health by not breathing smoke, as a result of
using biogas technology. Thus, service providers should give more priority to
women-headed households for adopting biogas technology.
iii. Subsidy and loan repayment:
This empirical study found that people are often inspired to decide in favor of a
biogas plant by access to subsidy. As mentioned, subsidy is hard for government
but serves for better livelihood for people, so it should be continued for a certain
period of time. The repayment per installment is rather high. It is therefore
recommended that the repayment period could be extended to up to 5 years, so
that the installment amount to be repaid is brought within a reasonable limit of
the biogas users, and service providers should also be curious about the postcare of biogas plants.
iv. Role of electronic and print media
The study found that biogas activities are promoted without any assistance from
advertisement through electronic or print media. Virtually, Bangladesh is being
persisted with good number of electronic and print media. Rural Bangladesh has
47
access to television, print media and telecommunication services for receiving
the recent news on social, political, economic, and environment topics, etc.
Relevant renewable energy providing authorities should initiate dissemination of
the biogas advantages across the country, broadcasting through different
advertisement activities of electronic and print media.
v. Awareness and capacity building
Few partner NGOs are working under IDCOL rules and regulation across the
country. These NGOs and private entrepreneurs can arrange the training,
workshops, conferences and seminars on biogas technology by which rural
people will obtain the necessary information and build awareness on the existing
energy crisis, environmental degradation and benefits of slurry use.
48
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