International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 9, September 2014)
Characterization of the Physical Parameters of Coffee Husks
towards Energy Production
M. W. Mbugua1, M. W. Kimani2, B. N. K. Njoroge3, A. N. Gitau4, J. M. Mutua5, A. K. Luvai6
1.4.5,6
Department of Environmental and Biosystems Engineering
Department of Real Estate and Construction Management
3
Department of Civil and Construction Engineering
University of Nairobi, P.O Box 30197-00100 Nairobi, Kenya
2
Worldwide, biomass fuels are used for cooking in
households, institutions and cottage industries ranging from
brick and tile making, metalworking, bakeries, food
processing, weaving, restaurants and so forth. More
recently, many new plants are being set up to provide
energy from biomass directly through combustion to
generate electricity or in combined heat and power (CHP)
facilities or ethanol via fermentation.
Globally, biomass utilization worldwide remains steady
because of three broad reasons: population growth,
urbanization and improvement in living standards and
increasing environmental concerns [8]. Cogeneration
process has been identified as an alternative of reducing
costs in industrial processes. In this regard, stakeholders
have argued that this process will increase their
competitiveness while they sell excess power to the
national power grid alongside solving waste management
problems. From an economic point of view, the use of
biomass offers many benefits such as reducing dependence
on imported fuel resources and increasing local economic
sustainability. It generates high environmental benefits
through the mitigation of greenhouse Gases (GHG)
emissions and a substantial reduction of sulphur oxides
(SOx) and nitrogen oxides (NOx) emissions, when
compared to the use of fossil fuels [10].
Coffee milling produces a substantial amount of waste
(coffee husks). This waste can be used as a fuel to produce
power through biomass cogeneration. The environmental
implications of cogeneration stem not just from its inherent
efficiency but also from its decentralized character.
Decentralized energy is the best way to generate clean and
green energy. Even though the initial investment cost of
cogeneration systems is higher than purchasing all electric
power needs the life-cycle cost of the systems is often
lower. Cogeneration provides an indigenous source of
electrical energy, saves on foreign exchange, is a tool for
employment and wealth creation and an agent for
abatement of environmental degradation [21].
Abstract—The research was conducted to establish the
potential of coffee husks as a source of fuel for power
generation for the coffee milling industry. The heating values
for coffee husk samples at different moisture contents were
determined experimentally using an adiabatic bomb
calorimeter. The proximate and ultimate analyses were also
used to determine the higher heating values for coffee husks.
Representative samples of sugarcane bagasse and macadamia
nut shells were subjected to the same analysis as the coffee
husks and were used for comparison purposes. The moisture
content and gross calorific values were related by negative
linear relationships with coefficient of determination (R2)
values as 0.991, 0.993 and 0.982 for coffee husks, sugarcane
bagasse and macadamia nut shells respectively. This was an
indication that 99.1%, 99.3% and 98.2% of the variation in
calorific value was explained by variation in moisture content
for coffee husks, sugarcane bagasse and macadamia nut
shells. The optimum moisture content for all the samples was
found to be 0% and this is the value that corresponded to
maximum gross calorific value. The gross calorific values for
coffee husks, sugarcane bagasse and macadamia nut shells
were found to be 19.98, 19.95 and 21.26 respectively. An
Analysis of Variance (ANOVA) using the Statistical Package
for Social Sciences (SPSS) of the calorific values yielded a P
value of 0.7417 which was greater than the significance level
(α = 0.05). This value suggests that there is no significant
difference between coffee husks, sugarcane bagasse and
macadamia nut shells. Coffee husks offer a promising source
of renewable energy and therefore a cogeneration plant would
help the coffee farmer to move up the value chain and
accumulate more value from coffee.
Keywords—Cogeneration, coffee husks, biomass, calorific
value, renewable energy
I. INTRODUCTION
Biomass meets up to 70% of Kenya’s final energy
demand and provides for more than 90% of rural household
energy needs with about one third in the form of charcoal
and the rest from firewood. It is estimated that 80% of
urban households’ wood-fuel demand is met by charcoal
[22].
715
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 9, September 2014)
There is a market for cogenerated electricity owing to
the low levels of electrification in the rural areas. Only 18%
of Kenya’s population has access to grid electricity [13]
[19]. In the rural areas, grid electricity access levels are a
paltry 5% compared to 51% in urban areas [14]
Cogeneration in rural-based agro industries could
potentially assist in widening rural access to electricity.
Furthermore, the government has zero rated tax and
accrued revenue from the capital invested in cogeneration
i.e. dividends earned are not taxed. The government of
Kenya has also drafted legislation that promotes
cogeneration such as Sessional Paper No. 4 of 2004 on
Energy [16], Feed – in Tariff Policy for Renewable Energy
[17] [18]. In addition, technical and financial support is
available to assist the local groups and other investors
interested in investing in the development and promotion of
cogeneration [12].
Of the 50,000 tonnes of parchment coffee that Kenya
produces annually, some 25% is discarded as husk (also
known as parchment). For instance, Thika Coffee Mills
Company Limited processes 20% of the national output
and generates some 2,500 tonnes of husks per annum. The
husk is normally available throughout the year in
reasonable quantity and the peak supply starts from January
to May [5]. The factory gets coffee from all over the coffee
growing areas and therefore coffee husk samples were
representative, and thus the reason for the choice of the
mill. The overall objective of this research paper was
therefore to establish the potential for coffee husks as a
source of fuel for power generation in the coffee milling
industry. Further, this research aimed at identifying the
physical properties of coffee husks pertinent to biomass
cogeneration, establishing the calorific value and optimum
moisture content of coffee husks and developing a model
relating the calorific value and the moisture content.
Determination of Moisture Content: The standard test
methods for determination of moisture content using a
microwave oven by American Society for Testing and
Materials Committee E48.05 on biomass conversion was
used [4]. Moisture content of the samples was calculated as
the percentage difference between the wet weight and the
dry weight using equations 1 and 2 proposed by Maker
[15].
(
( )
)
( )
Where, Mwb is wet basis moisture content, Mw is mass of
moisture in kg, mdm is mass of dry matter in kg, Mdb is dry
basis moisture content.
Adjustment of Moisture Content: The moisture content
was regulated using the procedure proposed by [1]. A
known quantity of distilled water was added to the sample.
The sample and the distilled water were then mixed, put in
labelled air-tight plastic containers and stored for 48 hours
to allow for uniform distribution of the moisture. The
quantity of water to be added was determined using
equation 3 proposed by [1].
(
)
( )
Where, mw is mass of distilled water added, ms is mass of
sample at moisture content MCi, MCf is required moisture
content (% wb) and MCi is initial moisture content (% wb).
Determination of Ash Content: Ash content is the noncombustible residue left after fuel is burnt. It represents the
bulk mineral matter after carbon, oxygen, sulphur and
water have been driven off during combustion. The ash
content was calculated from the residue that remained after
samples were samples were heated in a furnace [2].
II. MATERIALS AND METHODS
A. Determination of Physical Parameters
The proximate analysis of the samples was carried out in
the Chemistry Laboratory at the Department of Food
Science, University of Nairobi while ultimate analysis was
carried out at Kenya Industrial Research and Development
Institute (KIRDI) Laboratories. The proximate analysis was
used to determine the moisture content, volatile content,
free carbon, and ash. The ultimate analysis was used to
determine carbon, hydrogen, oxygen, nitrogen and sulphur.
Determination of Volatile Matter and Fixed Carbon
Content: The content of volatile matter was determined by
heating the samples out of contact with air in a furnace to
900°C ±10°C for seven minutes [4]. The percentage mass
of volatile matter was calculated from the loss in mass of
the sample after reducing the loss in mass due to moisture.
The percentage of sample mass that remained after removal
of volatile matter and ash content was determined to give
the fixed carbon content. Each parameter was determined
in triplicates.
716
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 9, September 2014)
Ultimate Analysis: This analysis involved the
determination of contents of carbon, hydrogen, oxygen,
nitrogen and sulphur. The contents of hydrogen, carbon and
nitrogen were determined simultaneously using the
instrumental method [3]. The carbon dioxide, water vapour
and nitrogen mass fractions were then determined
quantitatively by instrumental gas analysis, from which the
percentage of carbon, hydrogen and nitrogen was
calculated. The sulphur content was determined following
the procedure outlined in [4] while the oxygen content was
calculated from the fraction of the sample mass that
remained after subtracting the percentage of carbon,
hydrogen, nitrogen, sulphur and ash [11]. Each parameter
was determined in triplicate and the mean calculated.
(
)
(
)
( )
Where, LHV is lower heating value in kJ/kg (wb), HHV
is higher heating value in kJ/kg (db), Mwb is moisture
content measured wt % (wb) and H is hydrogen content wt
% (db).
B. Modeling
Regression Analysis: The experimental results of the
gross calorific value were plotted against the moisture
content. A model relating the calorific values and the
moisture content was formulated by finding a linear
function that approximates the trend in the data.
Computation of Gross Calorific Value: The Gross
Calorific Values/Higher Heating Values from the bomb
calorimetry results were calculated using equation 4.
Correlation Analysis: Correlation analysis was used to
measure the strength of the association (linear relationship)
between the moisture content and gross calorific value. The
range of correlation coefficient (r) is between -1and 1.
When the value of r is to -1, the negative linear relationship
is usually stronger and the closer the value to +1, the
stronger the positive linear relationship. Similarly, when
the value of r is closer to 0, the linear relationship appears
weaker [7].
( )
Where, T is temperature rise, MT is total water
equivalent, Ws is weight of sample, SpHw is specific heat
capacity of water. Similarly, the higher calorific values
were calculated from proximate and ultimate analysis using
equation 5.
Coefficient of Determination, R2: The coefficient of
determination is the proportion of the total variation in the
dependent variable that is explained by least square
regression line. It provides a quantitative measure of how
well the regression line fits the scatter plot i.e. the strength
that exists between gross calorific value and the moisture
content. Microsoft Excel Software was used to obtain
calculations for the values of correlation analysis,
coefficient of determination R2 and to plot the trend line.
( )
Where, HHV is higher heating value/Gross calorific
value, C is weight fraction of carbon; (wt % db), H is
weight fraction of hydrogen; (wt % db), O is weight
fraction of oxygen; (wt % db), A is weight fraction of ash;
(wt % db), S is weight fraction of sulphur (wt % db) and N
is weight fraction of nitrogen appearing in the ultimate
analysis (wt % db). This formula was selected because it
gives an average error of 1.45 %, typical of the error of
most measurements. This equation permits using heat
values in calculations and models of biomass processes [6].
Analysis of Variance: The one-way analysis of variance
(ANOVA) was used to determine any significant
differences between the means of calorific values at
different moisture content for coffee husks, macadamia nut
shells and the sugarcane bagasse.
Computation of Lower Heating Values: Lower heating
value (LHV) or net calorific value (NCV) from the
proximate and ultimate analysis results was computed
using equation 6 [21].
717
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 9, September 2014)
TABLE 1
RESULTS FOR PROXIMATE AND ULTIMATE ANALYSIS
CH
SB
ẋ
s
Proximate Analysis
TN
0.21
0.026
(%)
M
9.96
0.941
(%)
VM
80.9
1.12
(%)
FC
1.7
0.106
(%)
Ultimate Analysis
TC
51.39
2.29
(%)
S
0.26
0.072
(%)
H
3.34
0.159
(%)
AC
5.47
0.173
%
O%
39.8
2.29
CV
17.67
0.106
Kcal
/g
MS
P
ẋ
s
ẋ
0.34
0.06
0.36
0.017
0.007
10.27
1.017
8.82
1.162
0.2765
78.6
2.55
79.1
3.06
0.5345
1.8
0.13
2.6
0.1
0.0001
51.14
2.464
49.85
1.57
0.6589
0.22
0.026
0.24
0.02
0.5927
3.49
0.288
5.83
0.471
0.0002
2.57
0.55
0.42
0.066
0.0001
42.8
17.50
2.066
1.074
43.9
19.74
1.18
0.84
0.0892
0.9998
s
21
Gross Calorific Value (MJ/kg)
Par
B. Modelling
From the correlation analysis the correlation coefficient
(R2) of moisture content and the gross calorific value for
coffee husks, sugarcane bagasse and Macadamia shells
were found to be -0.995, -0.996 and -0.991 respectively.
The relationship between moisture content and the gross
calorific were strong negative linear relationships. From the
results, the calorific value is a function of moisture content
decreasing linearly with increase in moisture content. The
regression lines were generated using Microsoft Excel.
Figures 1, 2 and 3 indicate that the maximum gross
calorific values were obtained at zero moisture content. The
Y-intercept (maximum gross calorific value) was found to
be 19.981 KJ/kg, 21.263 KJ/kg and 19.953 KJ/kg for coffee
husks, macadamia nut shells and the sugarcane bagasse
respectively. The gradient of the regression lines were 0.1426,-0.1443 and -0.1251 for coffee husks, macadamia
nut shells and the sugarcane bagasse respectively.
Key: Par-parameter; TN – total nitrogen; M – moisture;
VM – volatile matter, FC – fixed carbon; TC- total carbon;
S – sulphur; H- hydrogen; A C- ash content; O – oxygen;
CV-calorific value; CH - coffee husks; SB - sugar
bargasse; MS-macadamia nut shells; P- significance level,
ẋ - average value; s- standard deviation
20
GCV = -0.1426 MC + 19.981
R² = 0.991
19
18
17
16
15
14
13
5
10
III. RESULTS AND DISCUSSIONS
15
20
25
30
35
40
45
Moisture Content wt %wb
A. Results of proximate and ultimate analyses
Figure 1 Relationship Between Gross Calorific Value And Moisture
Content For Coffee Husks
The results of proximate and ultimate analysis as well as
the statistical significance analysis of coffee husks,
sugarcane bagasse and macadamia husks are given in table
1. The results presented are the mean and standard
deviations of three replicates of each parameter. The
significance value, P from one-way analysis of variance
(ANOVA) of 0.2765, 0.5345, 0.6589, 0.5927, 0.0892 and
0.9998 for moisture content, volatile matter, total carbon,
sulphur, oxygen and gross calorific values respectively are
an indication that they are not significantly different.
However the significance value, P of 0.007, 0.0001, 0.0001
and 0.0002 for total nitrogen, ash content, fixed carbon and
hydrogen shows that they are significantly different.
Gross Calorific Value (MJ/kg)
22
GCV = -0.1443 MC + 21.263
R² = 0.982
21
20
19
18
17
16
15
5
10
15
20
25
30
35
40
45
Moisture Content wt %wb
Figure 2 Relationship Between Gross Calorific Value And Moisture
Content For Macadamia Nut Shells
718
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 9, September 2014)
The gross calorific values for coffee husks, sugarcane
bagasse and the macadamia nut shells were found to be
19.981, 19.953 and 21.263 respectively. Coffee husks offer
a promising source of renewable energy. A cogeneration
plant will help the coffee farmer to move up the value
chain, and accumulate more value from coffee. It would
reduce the cost of production, thus returning value to the
farmer. The analysis of variance (ANOVA) with Statistical
Package for Social Sciences (SPSS) of the calorific values
yielded a p value of 0.7417 which was greater than the
significance level (α = 0.05). This value suggests that no
significant difference exist between coffee husks,
macadamia nut shells and the sugarcane bagasse. The linear
relationship between moisture content and the gross
calorific values were strong negative linear relationships.
The coefficient of determination (R2) for coffee husks,
sugarcane bagasse and macadamia shells were found to be
0.991, 0.993 and 0.982 respectively. This was an indication
that 99.1%, 99.3% and 98.2% of the variation in calorific
value was explained by variation in moisture content for
coffee husks, sugarcane bagasse and macadamia nut shells
respectively.
Large scale energy project development such as power
plant needs appropriate information for decision-making. A
financial-led approach for coffee husks as a source of fuel
for cogeneration need to be studied to offer an alternative
project formulation. A mathematical model can be
developed to determine the size of the power plant that
would give optimal results. A low moisture level in the fuel
is usually preferable because high-moisture fuels burn less
readily and provide less useful heat per unit mass (much of
the energy in wet fuel is used to heat and vaporize the
water). Extremely dry fuel, however, can cause problems
such as dust that fouls equipment or can even be an
explosion hazard.
A cogeneration plant for the coffee mills should be
designed to operate at the lowest moisture content possible
while maintaining low installation and operating costs, low
specific fuel consumption and a high heat recovery rate.
Given that the Kenya Nut Company owns Thika Coffee
Mills and there is no significant difference, there is clearly
some potential for a collaborative effort between the two to
make productive use of both macadamia nut shells and
coffee husk in a joint operation.
21
Gross Calorific Value (MJ/kg)
20
19
GCV = -0.1251 MC + 19.953
R² = 0.993
18
17
16
15
14
13
5
10
15
20
25
30
35
40
45
Moisture Content wt %wb
Figure 3 Relationship Between Gross Calorific Value And Moisture
Content For Sugarcane Bagasse
The relationship between the gross calorific value and
moisture content for coffee husks, macadamia nut shells
and the sugarcane bagasse are explained by equations 7, 8
and 9 respectively.
( )
( )
( )
Where, GCVCH is gross caloric value or the higher
heating value for coffee husks, GCVMS is gross caloric
value or the higher heating value for macadamia nut shells,
GCVSB is gross caloric value or the higher heating value for
sugarcane bagasse and MC is the moisture content.
The coefficient of determination (R2) for coffee husks,
sugarcane bagasse and the macadamia shells were found to
be 0.991, 0.993 and 0.982 respectively. From the results the
coefficient of determination values predicts that 99.1%,
99.3% and 98.2% of the variation in calorific value was
explained by variation in moisture content for coffee husks,
sugarcane bagasse and macadamia nut shells. The ANOVA
analysis with SPSS of the calorific values yielded a p value
of 0.7417 which was greater than the alpha
level/significance level of 0.05. This value suggests that no
significant difference exist between coffee husks,
macadamia nut shells and the sugarcane bagasse.
IV. CONCLUSION AND RECOMMENDATIONS
Acknowledgement
Fuel heating values were inversely proportional to
moisture content. The maximum Gross Calorific Values
were obtained at zero moisture content which is the
optimum moisture content.
We would wish to acknowledge the contribution of
everyone for making this paper a success.
719
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 9, September 2014)
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We would also wish to extend our gratitude to the staff
at the Chemistry Laboratory, Department of Food Science
and Technology for their support during laboratory work.
We would also wish to extend our gratitude to the
management and the staff of The Kenya Institute of
Research and Development for according us vital support
during laboratory analysis of our samples. Our sincere
gratitude goes Thika Coffee Mills Factory, Mumias Sugar
Company Limited and Macadamia Nut Company Limited
for their support during collection of samples for our
research.
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