ARTICLE IN PRESS
Energy 32 (2007) 1660–1669
www.elsevier.com/locate/energy
Thermodynamic equilibrium model and second law analysis
of a downdraft waste gasifier
S. Jarungthammachote, A. Dutta
Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology,
P.O. Box 4, Klongluang, Pathumthani 12120, Thailand
Received 9 August 2006
Abstract
The management of municipal solid waste (MSW) and the current status of world energy resources crisis are important problems.
Gasification is a kind of waste-to- energy conversion scheme that offers the most attractive solution to both waste disposal and energy
problems. In this study, the thermodynamic equilibrium model based on equilibrium constant for predicting the composition of producer
gas in a downdraft waste gasifier was developed. To enhance the performance of the model, further modification was made by
multiplying the equilibrium constants with coefficients. The modified model was validated with the data reported by different researchers.
MSW in Thailand was then used to simulate and to study the effects of moisture content (MC) of the waste on the gasifier’s performance.
The results showed that the mole fraction of H2 gradually increases; CO decreases; CH4, which has a very low percentage in the producer
gas increases; N2 slightly decreases; and CO2 increases with increasing MC. The reaction temperature, the calorific value, and the second
law efficiency, decrease when MC increases.
r 2007 Elsevier Ltd. All rights reserved.
Keywords: Downdraft waste gasifier; Thermodynamic equilibrium model; Second law analysis; Municipal solid waste; Waste to energy
1. Introduction
The management of municipal solid waste (MSW) is one
of the most important problems especially for developing
countries. The quantity of solid waste generated by human
activities has increased dramatically and its characteristics
depend on the location and people’s lifestyles. In general,
there are five main categories of acceptable waste handling
options available; namely (1) prevention, (2) re-use and
recycling, (3) composting, (4) incineration, and (5) landfilling. In many countries, landfills are the most frequently
used option to dispose MSW. Lately, incineration is
considered to be one of the most effective means of dealing
with waste [1]. Incineration not only reduces volume of
solid waste but also converts wastes to an energy form.
This scheme is popularly known as waste-to-energy (WTE)
conversion. However, due to the environmental problems
that go hand-in-hand with incineration, waste incinerators
Corresponding author. Tel.: +66 2 524 5403; fax: +66 2 524 5439.
E-mail address: [email protected] (A. Dutta).
0360-5442/$ - see front matter r 2007 Elsevier Ltd. All rights reserved.
doi:10.1016/j.energy.2007.01.010
are required to install with sophisticated exhaust gas
cleaning equipment. Depending on the regulations of the
country, this gas cleaning equipment can be large and
expensive [2].
Gasification is another kind of WTE conversion that is
very attractive. In the old days, gasification was widely
used for producing gases from coal and biomass but now
gasification of waste has become one of the growing
interests of many organizations and researchers. Moreover,
due to the world’s energy crisis, finding new energy
resources is very important. For these reasons, it is
apparent that gasification of waste is a solution for both
MSW management and finding option for new energy
resources. Furthermore, it also proves to be more environmental friendly compared to other options.
Since waste is inherently non-homogeneous material, the
composition of MSW varies significantly and depends on
many factors. These are location, local policy, origin of the
waste, etc. For a techno-economical evaluation, actual
construction of a gasifier is not always feasible and
economically sound because experimentation usually
ARTICLE IN PRESS
S. Jarungthammachote, A. Dutta / Energy 32 (2007) 1660–1669
Nomenclature
C
C̄ p
D
E
Exp
Dḡof
DGTo
o
h̄f
Dh̄T
H
HHV
K
LHV
m
Mod
n
N
O
P
R̄
RMS
s̄
mass fraction of carbon
specific heat at constant pressure, kJ/kmol K
number of data
exergy, kJ
experimental data
standard Gibbs function of formation
standard Gibbs function of reaction at temperature T
enthalpy of formation, kJ/kmol
enthalpy difference in any given T and at 298 K,
1 atm, kJ/kmol
mass fraction of hydrogen
higher heating value, MJ/kg
equilibrium constants
lower heating value, kJ/kmol
kmol of oxygen per kmol of feedstock
predicted value from model
numbers of mole
mass fraction of nitrogen
mass fraction of oxygen
pressure, atm
universal gas constant, 8.314 kJ/kmol K
root-mean-square
specific entropy, kJ/kmol K
involves much greater time, effort, and cost. Thus, a
mathematical model for such analysis is more useful.
The equilibrium model has been used by many researchers for the analysis of the gasification process. Those
models were based on the minimization of Gibbs free
energy [3–7]. This is a constrained optimization problem
that generally uses the Lagrange multiplier method. An
understanding of some mathematical theories is necessary
for solving optimization and non-linear equation problems.
The other kind of equilibrium model is based on
equilibrium constant. However, it is important to note
that an equilibrium model based on the minimization of
Gibbs free energy and one based on equilibrium constants
are of the same concept. Zainal et al. [8] used the latter type
of equilibrium model to predict the composition of the
producer gas for different biomass materials. The amount
of oxygen in that model was eliminated by defining it in
terms of some components in the producer gas; however, it
was not shown when they compared their model with the
experimental data. This is what makes the model developed
in this study different. The relationship between the
amount of oxygen and the reaction temperature has been
explored. This model can predict the reaction temperature
by knowing the amount of oxygen, and vice versa. To
further improve the model, the equilibrium constants were
multiplied by the coefficients determined from the comparison of the predicted results with the experimental results
S
T
w
x
1661
mass fraction of sulfur
temperature, K
kmol of moisture per kmol of feedstock
mole fraction
Greek letters
n
e
Z
stoichiometric number
specific exergy, kJ/kmol
efficiency
Superscripts
quantity per unit mole
Subscripts
ch
dry
ex
feed
fg
i, j, k
ph
o
chemical
dry basis
exergy
feedstock
difference in property between saturated liquid
and saturated vapor
i, j, kth gas species
physical
standard reference state
from other works. Data on MSW of Thailand was used in
the modified model for the simulation to study the effects
of moisture content on the composition of the producer
gas, on the reaction temperature, and on the calorific value.
Finally, the second law efficiency of the gasification process
was estimated for the solid waste with 20%, 25%, and 30%
moisture content.
2. The model
To develop the model, the chemical formula of feedstock
is defined as CHxOyNz. The global gasification reaction can
be written as follows:
CHx Oy Nz þ wH2 O þ mðO2 þ 3:76N2 Þ
¼ nH2 H2 þ nCO CO þ nCO2 CO2 þ nH2 O H2 O
z
þ 3:76m N2 ,
þ nCH4 CH4 þ
2
ð1Þ
where x, y, and z are the number of atoms of hydrogen,
oxygen, and nitrogen per number of atom of carbon in the
feedstock, respectively; w is the amount of moisture per
kmol of feedstock; and m is the amount of oxygen per kmol
of feedstock. All inputs on the left-hand side of Eq. (1) are
defined at 25 1C. On the right-hand side, ni are the numbers
of mole of the species i that are also unknown.
ARTICLE IN PRESS
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1662
2.1. Mass balance
To find the five unknown species of the producer gas,
five equations were required. Those equations were
generated using mass balance and equilibrium constant
relationships. Considering the global gasification reaction
in Eq. (1), the first three equations were formulated by
balancing each chemical element as shown in Eqs. (2)–(4).
Carbon balance:
f 1 ¼ 0 ¼ nCO þ nCO2 þ nCH4 1.
f 4 ¼ 0 ¼ K 1 ðnCO ÞðnH2 O Þ ðnCO2 ÞðnH2 Þ,
(11)
f 5 ¼ 0 ¼ K 2 ðnH2 Þ2 ðnCH4 Þðntotal Þ.
(12)
(2)
Eqs. (13) and (14) were used for the equilibrium state of
ideal gas mixture because of the requirements of K1 and K2
values
(3)
DG oT
,
R̄T
X
ni Dḡof;T;i ,
DG oT ¼
Hydrogen balance:
f 2 ¼ 0 ¼ 2nH2 þ 2nH2 O þ 4nCH4 x 2w.
where xi is mole fraction of species i in the ideal gas
mixture, n is stoichiometric number (positive value for
products and negative value for reactants), Po is standard
pressure, 1 atm, and ntotal is total mole of producer gas.
Eqs. (9) and (10) can be modified as
ln K ¼ Oxygen balance:
f 3 ¼ 0 ¼ nCO þ 2nCO2 þ nH2 O w 2m y.
(4)
(13)
(14)
i
2.2. Thermodynamic equilibrium
Chemical equilibrium is usually explained either by
minimization of Gibbs free energy or by using an
equilibrium constant. To minimize the Gibbs free energy,
constrained optimization methods are generally used which
requires an understanding of complex mathematical
theories. For that reason, the present thermodynamic
equilibrium model is developed based on the equilibrium
constant and not on the Gibbs free energy. The remaining
two equations, were obtained from the equilibrium
constant of the reactions occurring in the gasification zone
as shown below
Boudouard reaction :
C þ CO2 ¼ 2CO;
(5)
Water2gas reaction :
C þ H2 O ¼ CO þ H2 ,
(6)
Methane reaction :
C þ 2H2 ¼ CH4 .
CO2 þ H2 O ¼ CO2 þ H2 .
(8)
For the model in this study, the thermodynamic
equilibrium was assumed for all chemical reactions in the
gasification zone. All gases were assumed to be ideal and all
reactions form at pressure 1 atm. Therefore, the equilibrium constants, which are functions of temperature for
the water–gas shift reaction and the methane reaction are:
The equilibrium constant for water–gas shift reaction
P ni
Y
i
P
ðnCO2 ÞðnH2 Þ
K1 ¼
.
(9)
ðxi Þni
¼
o
P
ðnCO ÞðnH2 O Þ
i
The equilibrium constant for methane reaction
P ni
Y
i
P
ðnCH4 Þðntotal Þ
ni
K2 ¼
ðxi Þ
¼
,
o
P
ðnH2 Þ2
i
The values of coefficients a0 –g0 and the enthalpy of
formation of the gases are presented in Table 1 [10].
For calculating K1 and K2, the temperature in the
gasification or reduction zone must be known. In this
study, it was determined using energy balance method as
explained in Section 2.3.
(7)
Zainal et al. [8] and Higman and van der Burgt [9]
presented that Eqs. (5) and (6) can be combined to give the
water–gas shift reaction by subtracting Eq. (5) from Eq. (6)
Water2gas shift reaction :
where R̄ is the universal gas constant, 8.314 kJ/(kmol K),
DGTo is the standard Gibbs function of reaction, and Dḡof;T;i
represents the standard Gibbs function of formation at
given temperature T of the gas species i which can be
expressed by the empirical equation below
0
0
c
d
o
Dḡof;T ¼ h̄f a0 T lnðTÞ b0 T 2 T3 T4
2
3
0
e
þ
ð15Þ
þ f 0 þ g0 T.
2T
(10)
2.3. Energy balance
The temperature of the gasification zone needs to be
calculated in order to calculate the equilibrium constants
(Eqs. (13)–(15)). For this reason, either energy or enthalpy
balance was performed for the gasification process which
was usually assumed to be an adiabatic process [8]. When
the temperature in gasification zone is T and the
temperature at inlet state is assumed to be 298 K (25 1C),
the enthalpy balance for this process can be written as
X o
X
o
o
ni ðh̄f;i þ Dh̄T;i Þ,
(16)
h̄f;j ¼
j¼react
i¼prod
o
h̄f
where
is the enthalpy of formation in kJ/kmol and its
value is zero for all chemical elements at reference state
(298 K, 1 atm), and Dh̄T represents the enthalpy difference
between any given state and at reference state. It can be
approximated by
Z T
C̄ p ðTÞ dT,
Dh̄T ¼
(17)
298
ARTICLE IN PRESS
S. Jarungthammachote, A. Dutta / Energy 32 (2007) 1660–1669
1663
Table 1
o
The value of h̄f (kJ/mol) and coefficients of the empirical equation for Dḡof;T (kJ/mol)
o
Compound
h̄f
a0
b0
c0
d0
e0
f0
g0
CO
CO2
H2O
CH4
110.5
393.5
241.8
74.8
5.619 103
1.949 102
8.950 103
4.620 102
1.190 105
3.122 105
3.672 106
1.130 105
6.383 109
2.448 108
5.209 109
1.319 108
1.846 1012
6.946 1012
1.478 1012
6.647 1012
4.891 102
4.891 102
0.0
4.891 102
8.684 101
5.270
2.868
1.411 101
6.131 102
1.207 101
1.722 102
2.234 101
Table 2
The coefficients of specific heat for the empirical equation
Gas species
a
b
c
d
Temperature range (K)
Hydrogen
Carbon monoxide
Carbon dioxide
Water vapor
Methane
Nitrogen
29.11
28.16
22.26
32.24
19.89
28.90
0.1916 102
0.1675 102
5.981 102
0.1923 102
5.204 102
0.1571 102
0.4003 105
0.5372 105
3.501 105
1.055 105
1.269 105
0.8081 105
0.8704 109
2.222 109
7.469 109
3.595 109
11.01 109
2.873 109
273–1800
273–1800
273–1800
273–1800
273–1500
273–1800
where C̄ p ðTÞ is specific heat at constant pressure in
kJ/kmol K and is a function of temperature. It can be
defined by the empirical equation below
C̄ p ðTÞ ¼ a þ bT þ cT 2 þ dT 3 ,
(18)
where T is the temperature in K and
Z T
C̄ p ðTÞdT ¼ aT þ bT 2 þ cT 3 þ dT 4 þ k,
(19)
2.4. Calculation procedure
298
where k is a constant obtained from the integration and a,
b, c, and d are the specific gas species coefficients, which are
shown in Table 2 [11].
Eq. (16) can be rewritten as
X o
X
o
h̄f;j ¼
ni h̄f;i
j¼react
i¼prod
2
3
P
P
2
3
n
a
n
b
þ
n
c
T
þ
T
i i
i i
i i T 7
6
i
i
6 i
7
7.
þ6
6 P
7
P
4þ
5
4
nd T þ nk
P
i i
i
To solve the values of nH 2 ; nCO ; nCO2 ; nH2 O and nCH4 an
initial temperature was assumed and substituted into
Eqs. (13) and (15) to initially calculate K1 and K2. Then,
both equilibrium constants were substituted into Eqs. (11)
and (12), respectively. Finally, the five simultaneous
equations, Eqs. (2), (3), (4), (11), and (12), were used and
solved by Newton–Raphson method. For calculating the
new value of temperature, Eq. (20) was used. The outlined
procedure was repeated until the temperature value was
converged. The detail of the calculation procedure is
illustrated in Fig. 1.
i i
i
3. Validation and modification of the model
ð20Þ
De Souza-Santos [12] suggested the relationship for
finding the enthalpy of formation for solid fuel in reactant
that is
X
o
o
h̄f;fuel ¼ LHV þ
½nk ðh̄f Þk ,
(21)
k¼prod
o
ðh̄f Þk
calculated from Eq. (20) using Newton–Raphson method.
This relationship can predict the reaction temperature by
knowing the amount of air. This makes the model a good
tool to show the variation of reaction temperature when
mole of air is changed.
where
is the enthalpy of formation of product k under
complete combustion of the solid fuel and LHV is the
lower heating value of the solid fuel in kJ/kmol. Now that
the enthalpies of formation in Eq. (16) can be solved, the
temperature in the gasification zone can finally be
3.1. Validation
The model developed in this study was tested by
comparing the calculation results with data from other
researchers. Nine experimental data reported by Jayah
et al. [13] were used to compare with the results from the
model developed. The comparison is shown in Table 3. The
comparison was done by setting the temperature used for
the developed model fixed at 1100 K as reported by Jayah
et al. [13]. Table 4 shows the comparisons of results
between the model developed and the experimental data.
These two comparisons are the best and the worst cases
ARTICLE IN PRESS
S. Jarungthammachote, A. Dutta / Energy 32 (2007) 1660–1669
1664
INPUT:
initial temperature T
m, and w
START
CALCULATE:
the equilibrium K1 and K2 by using
Eqs. (15), (14), and (13)
T=Tnew
Abs (T-Tnew)
<0.1 K
END
CALCULATE:
ni by using Eqs. (2), (3), (4), (11),
and (12)
CALCULATE:
the temperature Tnew by using Eq. (20)
Fig. 1. The calculation procedure.
Table 3
The RMS error from comparison between predicted results and data
from [13]
Run no.
RMS error
1
2
3
4
5
6
7
8
9
Avg RMS error
1.585
1.484
1.066
0.882
2.474
3.917
1.219
2.746
2.717
2.010
Table 4
The comparison of predicted results with the experimental data from [13]
Gas
composition
% mol dry
basis
The present model
Experimental data
RMS error
MC
16.0%
MC
14.0%
MC
16.0%
MC
14.0%
16.0% 14.0%
H2
CO
CH4
CO2
N2
ma
18.04
17.86
0.11
11.84
52.15
0.4647
18.03
18.51
0.11
11.43
51.92
0.4591
17.00
18.40
1.30
10.60
52.70
0.3361
12.50
18.90
1.20
8.50
59.10
0.3927
a
Tables 3 and 4 show that the predicted results generally
agree with other experimental data, except for the case of
CH4. The slight difference in the results may have came
from the assumptions defined in simplifying the model,
such as all gases are assumed to be ideal, no residue,
absence of tar, etc. The interesting points in the comparisons are the amount of H2 and CH4. The model predicted
higher amounts of H2, but the predicted amounts of CH4
are lower than all experimental data. It is important to note
that equilibrium models from the literatures reviewed
[3–6,8,14] predicted the H2 concentration higher and the
CH4 concentration lower than the measured data from
experiment. Bacon et al. [14] also reported a substantially
higher CH4 in the product gas than what was estimated
from his equilibrium model calculation. A possible
explanation to this is that the state of equilibrium was
not met during the experiment. Gumz [15] as cited by
Bacon et al. [14] stated that a modified equilibrium
constant can be defined as the true equilibrium constant
multiplied by the degree of approach to equilibrium.
In calibrating the model of Jayah et al. [13], the amount
of methane predicted was adjusted in such a way that it
was equal to the amount of methane measured in the
product gas.
0.882 3.917
The amount of oxygen in Eq. (1).
chosen from Table 3, correspond to the highest and the
lowest error. The error in this comparison is estimated by
the root-mean-square (RMS), defined as
sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
PN
2
i ðExpi Modi Þ
,
(22)
RMS ¼
D
where Exp is the value from the experimental results, Mod
is the predicted value from the model, and D is the number
of data.
3.2. The modified model
Since downdraft gasifiers are different in designs, the
producer gases generated by them are also different in
composition. To increase the results’ accuracy, some
models were developed and modified for specific gasifier.
Jayah et al.’s model was calibrated by fixing the amount of
methane in the model to a value derived from one of their
experimental results [13]. Experimental data reported at
Zainal et al. [8], Altafini et al. [5], and Jayah et al. [13] were
used to modify the model. This combination gives a total of
eleven cases to use as experimental data. A coefficient of
11.28, was used to multiply with K2 in the calculation
procedure in order to improve the performance of the
model. This coefficient came from the average value of the
ratio of CH4 from the eleven experimental data and CH4
ARTICLE IN PRESS
S. Jarungthammachote, A. Dutta / Energy 32 (2007) 1660–1669
calculated from the model. For CO concentration, the
equilibrium model normally predicts a slightly lower value
than that from the experiments. In some cases the
equilibrium model also predicts the CO2 concentration
barely higher than those from the experiments [3–6,8].
Therefore, a coefficient less than 1.0 was multiplied with K1
which was obtained the same way as finding the coefficient
for K2 based on the amount of CO. A value 0.91 was
defined to be the coefficient for modifying K1.
The modified model was then used to simulate and
compare with Jayah et al’s work. Furthermore, the
modified model was also compared with SynGas model
and the experimental data at 1073 K, 10% MC from
Altafini et al. [5]. As presented in previous sections, the
amount of oxygen used in the gasification process is
the necessary input for the model simulation. Thus, the
experimental result from Zainal et al.’s work was not used
for the comparison because the amount of air used was not
indicated. The results of the comparisons are shown in
Tables 5–7, respectively.
Table 5 shows that after modifying the model, the
amount of H2 significantly reduced as compared to the
predicted value from the unmodified model. The amount of
CH4 dramatically increased and was found closer to the
experimental values. For some cases, CO remained
constant, while for other cases it predicted slight increase
Table 5
The comparison of results from modified model with the data from [13]
Gas
composition
% mol dry
basis
The present model
Experimental data
RMS error
MC
16.0%
MC
14.0%
MC
16.0%
MC
14.0%
16.0% 14.0%
H2
CO
CH4
CO2
N2
m
16.81
17.86
1.05
12.10
52.18
0.4472
16.8
18.52
1.06
11.68
51.94
0.4415
17.00
18.40
1.30
10.60
52.70
0.3361
12.50
18.90
1.20
8.50
59.10
0.3927
0.700 3.652
Table 6
The RMS error from comparison between modified model and data
from [13]
Run no.
RMS
1
2
3
4
5
6
7
8
9
Avg RMS error
1.555
1.615
1.021
0.700
2.057
3.652
0.747
2.334
2.333
1.779
1665
Table 7
The comparison of results from modified model with the data from [5]
Gas
composition
% mol dry
basis
Modified
model
H2
CO
CH4
CO2
N2
m
18.24
23.34
1.66
9.82
46.93
0.3578
Altafini et al.
RMS error
SynGas
model
Experiment Modified
model
20.06
19.70
0.00
10.15
50.10
0.329
14.00
20.14
2.31
12.06
50.79
0.307
2.845
SynGas
model
2.780
in values from the unmodified model. One reason is that
the coefficient used to modify K1 is 0.91, which is almost
close to unity, thus, the value of CO in modified model
should not dramatically change. Some of the values were
the same as that of unmodified model because of the fact
that equation forming K1 has a direct relationship with the
amount of H2 produced, which is also depended on K2.
When K2 was modified using the coefficient 11.28, the value
of H2 reduced. However, since hydrogen has to be
conserved, amount of H2O is increased. In addition, the
amount of K1 has a specific value at a certain temperature
(around 0.82 for 1100 K after modification). Thus, the
amount of CO did not increase much and some values are
the same as predicted by the unmodified model. This effect
can be observed from the increasing values of CO2, though
the increment was insignificant.
Table 6 presents that the predicted results of the
modified model were better compared to unmodified
model. The results from the modified model are satisfactorily close to the experimental value as shown in Table 7.
The predicted mole fractions of H2 and CO are higher
but the predicted mole fraction of CO2 is lower than
the experimental data. The RMS error between the
modified model and SynGas model were also found
comparable.
Another important parameter of gasification process is
HHV of producer gas. In the experiment of Altafini et al.’s
study, the average HHV measured from the experiment was 5.276 MJ/N m3 while the HHV calculated
from this model was 5.507 MJ/N m3. The data from
Tables 6 and 7 confirm that the modified model developed
in this study can predict agreeable results with experimental values.
4. The effect of moisture content
The municipal solid waste from developing countries
normally has high level of moisture when compared to
those from developed countries [16]. As for the case of
Thailand, the main composition of municipal solid waste is
food [17], thus it mainly consists of moisture. Therefore,
the effect of moisture content on the composition of
producer gas from waste gasification is an interesting
ARTICLE IN PRESS
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aspect. Table 8 shows the average composition of MSW
from eleven provinces in Thailand.
In this study, all noncombustible and recyclable materials except paper were excluded. Paper was included because
it can produce high levels of H2, CO, and CH4 [8].
Table 8
The average composition of MSW in eleven provinces in Thailand (2002)
[17]
Component
(wt%)
Food
Plastic
Paper
Glass, stone and can
Yard waste
Metal
Cloth
Rubber/leather
Other
54.17
12.24
9.80
7.95
3.98
3.15
2.61
2.47
4.13
Table 9
The chemical composition of solid waste on dry ash-free basis
Element
(wt%)
C
H
O
N
S
51.034
6.776
39.178
2.642
0.370
In estimating the chemical compositions on dry ash-free
basis, the information from Tchobanoglous et al. [18]
were employed and the results are shown in Table 9.
The chemical formula of this solid waste, based on a
single atom of carbon, is defined as CH1.5932O0.5758N0.0444.
Sulfur was neglected in this study. The enthalpy of
formation for the waste calculated using Eq. (21) is
107306.269 kJ/kmol. The lower heating value of solid
fuel in MJ/kg was derived using the higher heating value
formula presented by Channiwala and Parikh [19], that is
HHV ¼ 0:3491C þ 1:1783H þ 0:1005S 0:1034O
0:0151N 0:0211Ash;
LHV ¼ HHV ¼ 9mH hfg ,
ð23Þ
where C, H, O, N, S, and Ash are percentages of mass of
carbon, hydrogen, oxygen, nitrogen, sulfur and ash in the
dry solid fuel, mH is mass fraction of hydrogen in solid fuel,
and hfg is enthalpy of vaporization of water.
To study the effect of moisture content of the waste, the
amount of air was fixed at 0.4 of the stoichiometic
requirement (m ¼ 0.444). Fig. 2 shows the effect of
moisture content on the composition of producer gas. It
can be seen that the fraction of H2 gradually increases from
16.04% to 20.11% when MC increases from 0% to 40%.
In the case of CO, it showed an inverse tendency. CO
decreases from 25.01% to 12.01% with an increase in
moisture content. The useful gas CH4, has a very low
percentage in the producer gas, though it showed an
increase from 0.134% to 1.86%. Fig. 2 also illustrates the
fraction of N2 in the producer gas which was almost
Fig. 2. The effect of moisture content on the composition of producer gas.
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Fig. 3. The effect of moisture content on the reaction temperature.
Fig. 4. The effect of moisture content on the calorific value.
constant with only a slight change from 52.80% to 50.25%.
For CO2, it increases from 6.00% to 15.74%. Fig. 3 shows
the variation of the reaction temperature. The temperature
decreases from 1374.0 to 1064.3 K when the MC increases
from 0% to 40%. Fig. 4 displays the effect of moisture
content on the calorific value of producer gas. It can be
observed that the calorific value decreases from 4.93 to
4.42 MJ/N m3 when varying MC from 0% to 40%.
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5. Second law efficiency
Table 11
Second law efficiencies of waste gasification
As mentioned before, developing countries like Thailand
have a high level of moisture in their MSW. For Thailand,
the moisture content of MSW in some provinces is around
20–22% and can be as high as 40% for some provinces
popular to tourists [17]. In the previous section, we have
seen that the moisture content negatively affects the
calorific value of producer gas. For this part of the study,
exergy analysis was used to evaluate the effect of moisture
content on the performance of the gasification process. In
real processes, exergy is not conserved because of
irreversibilities. Exergy efficiency or second law efficiency
is defined as
Zex ¼
E prod
,
E feed þ E medium
(24)
where Eprod and Efeed are exergies of producer gas and
feedstock, respectively. Emedium is the exergy of the
gasifying medium, which in this study can be neglected
because it is the air at atmospheric conditions [20]. In this
case, kinetic exergy and potential exergy are also negligible,
thus the exergy can be divided into two major components
shown below
E ¼ E ch þ E ph ,
(25)
where Ech and Eph are chemical exergy and physical exergy,
respectively. The dead state used in the following calculation is defined at Po ¼ 1 atm, To ¼ 298 K. Kotas [21]
suggested that the specific chemical exergy of ideal mixture
gas, in kJ/kmol, can be calculated by
X
X
¯ ch;M ¼
xi ¯ch;i þ R̄T o
xi ln xi ,
(26)
i
i
where xi is mole fraction of ith component and ech,i is
standard chemical exergy of ith component, in kJ/kmol
and they are presented in Table 10 [21].
The physical exergy of each gas species can be calculated
by
¯ ph ¼ ðh̄ h̄o Þ T o ðs̄ s̄o Þ,
(27)
where h̄ and s̄ are enthalpy and entropy at any pressure (P),
temperature (T), h̄o and s̄o are enthalpy and entropy at Po,
To. Kotas [21] also presented the equation for estimating
exergy of solid fuel with mass ratio 2:674O=C40:667,
Table 10
Standard chemical exergy of some substances [21]
Substance
ch;i (kJ/kmol)
H2
CO
CO2
H2O (g)
CH4
N2
238,490
275,430
20,140
11,710
836,510
720
Moisture content (%)
Second law efficiencies (%)
20
25
30
81.54
80.28
78.62
expressed in kJ/kg, as shown
solid ¼ jdry ½LHV þ mw hfg ,
(28a)
where
jdry
¼
1:0438 þ 0:1882ðH=CÞ 0:2509ð1 þ 0:7256ðH=CÞÞ þ 0:0383ðN=CÞ
1 0:3035ðO=CÞ
ð28bÞ
and mw is mass fraction of moisture in the fuel, and hfg is
enthalpy of vaporization, in kJ/kg.
Table 11 presents the second law efficiencies of waste
gasification at moisture contents 20%, 25% and 30%,
respectively. The simulation was performed at temperature
equal to 1073 K.
From Table 11, it can be observed that second law
efficiency slightly decreases from 81.54% to 78.62% when
moisture content increases from 20% to 30%. The reason
of decreasing second law efficiency can be attributed to the
reduction of chemical exergy as the moisture content is
increased. Table 10 shows that the standard chemical
exergies of CH4, CO, and H2 are first, second, and third
highest values among the gases. When MC is increased,
more air is required to maintain the temperature at 1073 K.
This results in a decrease in the mole fraction of useful
gases such as CO, CH4, and H2 when simulations were
performed. Consequently, the first term in the right-hand
side of chemical exergy equation, Eq. (26) also decreased.
The results of this study agree with Kaupp’s study [22] as
he mentioned that in practice, in order to provide the
necessary heat of reaction to reach gasification temperature, an increasing MC necessitates an increasing amount
of air. The disadvantages of increasing the amount of air
shown in this section cause reduction of useful gases, CH4,
CO, and H2. This results in a significant reduction of the
heating value of the producer gas. These all lead to a
conclusion that MC is a very important factor. Therefore,
waste should be suitably dried when it will be used for
gasification purposes.
Drying by exposing the waste to solar radiation is a
simple way but it is suitable only under clear sky and could
take about one or two days. Under this condition, hygienic
problems and foul odor also come up and post major
concerns. Therefore, solar drying of waste before gasification process should be accompanied with waste segregation
and proper management.
ARTICLE IN PRESS
S. Jarungthammachote, A. Dutta / Energy 32 (2007) 1660–1669
6. Conclusion
The thermodynamic equilibrium model was developed
for downdraft gasifier in order to calculate the composition
of producer gas. The coefficients for correcting the
equilibrium constant of water–gas shift reaction and
methane reaction were used to improve the model. Those
coefficients were obtained from the comparison between
the model and the results of the experiments of other
researches. The predicted results from the modified model
satisfactorily agree with experimental results reported by
other researchers.
The modified model was then employed to simulate the
gasification of Thailand MSW. The results showed that the
mole fraction of H2 gradually increases and CO decreases,
when MC increases. CH4, which has a very low percentage
in the producer gas increases, N2 slightly decreases and
CO2 increases with increasing MC. The reaction temperature and the calorific value decrease when MC increases.
Finally, at a constant temperature of gasification process
for waste with MCs of 20%, 25%, and 30%, the second
law efficiency decreases with the increase in MCs. This is
because amount of required air increases when MC
increases in order to maintain the required reaction
temperature, which in this case is 1073 K. However, an
increase in required air causes many disadvantages, and
one of them is the mole fraction reduction of useful gases
which consequently reduces the heating value and the
second law efficiency. This finding just further proved that
waste segregation and solar drying of waste are necessary
steps for effective gasification of MSW.
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