b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 3 ) 1 e9
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Study on kinetic parameters of different biomass
samples using thermo-gravimetric analysis
Prakash Parthasarathy a, K. Sheeba Narayanan a,*, Lawrence Arockiam b
a
Fossil & Alternate Fuel Processing Laboratory, Department of Chemical Engineering, National Institute of
Technology, Tiruchirappalli 620015, Tamil Nadu, India
b
Bharat Heavy Electricals Ltd., Tiruchirappalli 620014, Tamil Nadu, India
article info
abstract
Article history:
In this study, thermogravimetric analysis of three different biomass samples such as rice
Received 21 February 2012
husk, saw dust and wheat husk is carried out to understand its thermal behaviour.
Received in revised form
Analysis is carried out in an inert nitrogen atmosphere from ambient temperature to 800 C
22 July 2013
at a heating rate of 10 C/min. It is observed that all the three biomass samples displayed
Accepted 2 August 2013
similar weight loss trend. Three reaction zones corresponding to dehydration,
Available online xxx
hemicellulose-cellulose degradation and lignin degradation are observed for all the three
biomass samples. The kinetic parameters such as activation energy, pre-exponential factor
Keywords:
and order of the reaction of samples are determined using modified form of equation.
ª 2013 Elsevier Ltd. All rights reserved.
Rice husk
Saw dust
Wheat husk
Thermal degradation
Thermogravimetric analysis
Kinetic parameters
1.
Introduction
Biomass conversion to convenient fuels by pyrolysis is a
promising concept. Pyrolysis is a precursor process to all
thermochemical processes such as combustion, gasification,
liquefaction etc [1]. However, biomass pyrolysis is an
extremely fiddly process which undergoes a sequence of reactions and its reaction kinetics being influenced by many
factors [2e5]. It is thus critical to gain a comprehensive
knowledge into the basics of biomass pyrolysis process.
Biomass is composed of three major components: cellulose, hemicellulose and lignin. These components usually
exist in biomass in the range of 32e45%, 19e25% and 14e26%
(by weight) respectively [6]. Previous attempts in biomass
pyrolysis have revealed that the thermal degradation of
biomass components follows the following trend: moisture
evolution, hemicellulose degradation, cellulose degradation
and finally lignin degradation [7,8].
White et al. [9] identified some factors viz: physical and
chemical nature of the biomass, heat and mass transfer limitations, operating conditions (heating rate, operating atmosphere) and methodical errors influencing the biomass
reaction kinetics. Excluding the above, certain factors like
biomass type, instrument employed and methodology adopted
in analysing also have some influence on reaction kinetics.
Thermogravimetric analysis (TGA) is a testing method done
on samples to determine change in weight with respect to
change in temperature. TGA relies on critical measurements
* Corresponding author. Tel.: þ91 431 2503113; fax: þ91 431 2500133.
E-mail address: sheeba@nitt.edu (K.S. Narayanan).
0961-9534/$ e see front matter ª 2013 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.biombioe.2013.08.004
Please cite this article in press as: Parthasarathy P, et al., Study on kinetic parameters of different biomass samples using
thermo-gravimetric analysis, Biomass and Bioenergy (2013), http://dx.doi.org/10.1016/j.biombioe.2013.08.004
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b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 3 ) 1 e9
such as weight, temperature and time. The rate of change in
weight which is also a vital measurement is derived from temperature (consecutive) measurements. TGA curve alone may
not be sufficient to interpret the weight loss of sample. Hence, a
derivative thermogravimetric (DTG) curve along with TGA curve
is needed to determine the apparent weight loss of samples.
These days, TGA apart from its usual application is also finding
its claim in the study of kinetics of biomass materials [10e12].
TGA is generally preferred, because of its simplicity and its
reliance on fewer observations to calculate the kinetics for the
complete temperature range [13]. Some of the disadvantages of
TGA include low heating rate, being time consuming and its
ability to handle only small amount of samples.
Determination of kinetic parameters such as activation
energy, pre-exponential factor and order of reaction are
crucial in forecasting the thermal response of sample. Determination of activation energy helps in finding out the minimum amount of energy needed to initiate a chemical change.
Pre-exponential factor and the order of reaction help in
calculating the reaction rate. These kinetic parameters can be
used in predicting the thermal behaviour of the samples and
the outcome of the findings can be taken as the basis for pyrolysis studies.
Biomass samples such as rice husk, saw dust and wheat
husk are taken for this study. The reason for studying these
biomass is to find-out a better mean of utilization (biomass) as
they are often used as direct fuels (low in energy density) and
as cattle feeds. In addition to that, their availability is abundant
in Trichy, Tamilnadu, South of India. Rice being the major crop
in Trichy, the rice husk availability is guaranteed round the
year. Similarly, saw mills in and around Trichy, provides the
continuous source for saw dust. The collected saw dust is from
Tectona Grandis (Teak) wood which is a tropical hardwood
species. Though wheat is not cultivated in Trichy, wheat husk
is being commonly used as food supplement for cattle.
Though previous literatures have thrown light on the
TGA of different biomass samples, only few works have
succeeded in determining all the kinetic parameters (activation energy, pre-exponential factor and order of reaction)
of all the components of biomass. This work is an attempt
made to find-out all the kinetic parameters of the biomass
components.
1.1.
Objectives
The specific objectives of the work include:
1To conduct TGA on three different biomass samples (rice
husk, saw dust and wheat husk) at a heating rate of 10 C/min
in an inert nitrogen atmosphere. (A lower heating rate ensures
that heat and mass transfer not to be rate limiting steps and
facilitates to study true reaction kinetics. One more advantage
is that slower heating rate provides distinct degradation zones
of biomass components in the ThermogravimetriceDerivative
Thermogravimetric (TGeDTG) curve) [14];
To determine the degradation temperature range of biomass
components, their initial degradation temperature and their
corresponding weight loss when the sample is heated from
ambient temperature to 800 C. (Increase in temperature beyond
800 C does not contribute for further weight loss of sample [14]);
3To determine the residual weight of samples after its complete degradation;
4To determine the kinetic parameters (activation energy, preexponential factor and order of reaction) for the samples.
1.2.
Theoretical backdrop
The common pyrolysis mechanism while dealing with lignocellulosic biomass suggested by Babu and Mohan et al.
[15,16], is briefed below
i. Heat from a heat sources raises the inside temperature
of the fuel.
i. The commencement of primary pyrolysis reactions at
higher temperatures leaves out volatiles and forms char
ii. The movement of hot volatiles causes heat transfer between hot volatiles and cooler unpyrolysed fuel
iii. Condensation of some of volatiles occurs when it contacts cooler parts of fuel, followed by secondary reactions generating tar
iv. Parallel occurrence of autocatalytic secondary pyrolytic
reactions and primary pyrolytic reactions
v. More thermal decomposition, reforming, water gas
shifts reactions, radical recombination and dehydration
can also occur which are based upon process’s residence
time, temperature and pressure profile.
A generalised pyrolysis reaction can be given by the below
equation [17].
Cn Hm Op /CO2 þ H2 O þ CH4 þ CO þ H2 þ ðC2 C5 Þ
(1)
Sequence of pyrolysis reactions at different temperatures is
given in Table 1 [18].
Nachenius et al. [19] illustrated sequence of pyrolysis reactions using TGA. Their observations are briefed as below.
Initially up to 100 C biomass tend to lose its weight due to
evaporation of water. Then till 160 C, biomass weight loss is
attributed due to bound water. The major biomass components cellulose, hemicellulose and lignin start to deteriorate
above 180 C. During their decomposition, biomass release
non-condensable gases and condensable vapours. Above
400 C, less volatile components are released producing a solid
product rich in fixed carbon and less in volatile carbon content. The temperature above 600 C makes the primary condensable components in gas phase to undergo cracking and
polymerization reactions reducing bio-oil yield.
In this study, determination of the kinetic parameters from
TGA technique is based on the modified form of Arrhenius
equation proposed by Goldfarb et al. and Duvvuri et al. [20,21].
Global kinetics of the devolatilization reaction can be
written as
dX
¼ kXn
dt
(2)
Applying the Arrhenius equation,
E=
RT
k ¼ Ae
(3)
Substituting the value of k in (1)
Please cite this article in press as: Parthasarathy P, et al., Study on kinetic parameters of different biomass samples using
thermo-gravimetric analysis, Biomass and Bioenergy (2013), http://dx.doi.org/10.1016/j.biombioe.2013.08.004
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Table 1 e ePyrolysis reactions at different temperatures.
Condition
Below 300 C
Between 300 C
and 450 C
Above 450 C
Above 500 C
Condensation
Processes
Products
Free radical formation, dehydration of
water and depolymerisation
Breaking of glucosodic linkages of
polysaccharide by substitution
Dehydration, rearrangement and
breaking of sugar units
A mixture of all above processes
Unsaturated products condense
and forms char
Formation of carbonyl and carboxyl, evolution of CO and CO2,
forming charred residue
Mixture of levoglucosan, anhydrides and oligosaccharides
as tar fraction
Formation of carbonyl compounds-acetaldehyde, glyoxal
and acrolein
A mixture of all above products
A highly reactive char residue containing cleave to
the char trapped free radicals
dX E= n
¼ Ae RT X
dt
Taking ln on both sides
ln
dX
E
¼ ln A þ n⁡ln X
dt
RT
(4)
sheet using Linest function. Thus, by finding out the values of
constants, the kinetic parameters of the thermal decomposition such as pre-exponential factor, activation energy and
order can be determined and accordingly the reaction characteristics can be predicted.
X can be written as
X¼
w wf
w0 wf
2.
Experimental
2.1.
Material preparation
The (3) can be written in linear form as
1
dw
E
w wf
¼ ln A þ n⁡ln
ln
wo wf dt
RT
w0 wf
(5)
Eq. (4) is of the form
y ¼ B þ Cx þ Dz
(6)
The parameters y, x, z, B, C and D in Eq. (6) are defined as
follows:
1
dw
y ¼ ln
w0 wf dt
x¼
1
RT
z ¼ ln
w wf
w0 wf
To begin with, all the three biomass samples are analysed for
their moisture content. The moisture level is brought down to
less than 15% by solar drying. The proximate analysis is performed in line with the ASTM standards viz. Moisture - ASTM
D 3173, Ash- ASTM D 3174, Volatile matter ASTM D 3175, Fixed
carbon- by difference. The elemental/ultimate analysis is
carried out using Elementar Vario EL III analyzer. The proximate analysis and ultimate analysis findings are presented in
Tables 2 and 3 respectively. The samples are subjected to sieve
analysis to determine the average particle size [22]. The
screens of size 125, 150, 180, 212, 355, 600, 1400 microns are
used in sieve analysis since large portion of the samples are
fine. The average particle size of the biomass samples is provided in Table 4. The particle size distribution of the samples
is illustrated in Fig. 1. The wet chemical analysis of the samples is provided in Table 5.
2.2.
B ¼ ln A
C ¼ E
D¼n
The constants B, C, D are estimated by multiple-linear
regression of the TGA data for each stage in Microsoft-Excel
Thermogravimetric analysis
The TGA is carried out in Perkin Elmer-Pyris 7 Thermogravimetric analyzer. The specification and test conditions of the
Thermogravimetric analyzer are presented in Table 6. The
standard experimental procedure for Thermogravimetric
analyzer is followed in this study. Before each run, temperature calibration of the analyzer is made by measuring the
Table 2 e Proximate analysis of the samples.
Rice husk
Elements
Moisture content
Volatile matter
Fixed carbon
Ash
Saw dust
Wheat husk
Weight basis (%)
Elements
Weight basis (%)
Elements
Weight basis (%)
6.80
66.99
7.77
18.45
Moisture content
Volatile matter
Fixed carbon
Ash
13.13
61.62
14.14
11.11
Moisture content
Volatile matter
Fixed carbon
Ash
13.33
68.57
5.71
12.38
Please cite this article in press as: Parthasarathy P, et al., Study on kinetic parameters of different biomass samples using
thermo-gravimetric analysis, Biomass and Bioenergy (2013), http://dx.doi.org/10.1016/j.biombioe.2013.08.004
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Table 3 e Ultimate analysis of the samples.
Rice husk
Saw dust
Wheat husk
Elements Weight Elements Weight Elements Weight
basis (%)
basis (%)
basis (%)
Carbon
Hydrogen
Nitrogen
Oxygen
Sulphur
Ash
37.17
5.16
0.29
38.92
18.45
Carbon
Hydrogen
Nitrogen
Oxygen
Sulphur
Ash
34.65
4.83
0.68
47.85
0.88
11.11
Carbon
Hydrogen
Nitrogen
Oxygen
Sulphur
Ash
40.58
6.83
2.52
38.92
12.38
melting point of aluminium metal sheets. Nitrogen is used as
the purge gas. The purge gas flow rate, desired end temperature and heating rate are set in the analyzer. Nitrogen is
passed through the system for a certain period before
switching on the analyser. Prior to sample filling in the
alumina pan, the pan weight is calibrated to zero. Then pan is
filled with the sample and its initial weight is recorded. Subsequently, the analyzer is started. The Pyris 7 software in the
analyzer provides a continuous record of temperature and
weight loss data throughout the study. Though the run gets
over at the desired end temperature, the purge gas is passed
through the system till the system attains ambient temperature. Finally analyzer is switched off and purge gas supply is
ceased. The TGA is repeated till data are consistent.
3.
Results & discussion
3.1.
Degradation temperature range of biomass
components
Earlier study on pyrolysis of biomass reported that hemicellulose degradation at a temperature lower than 350 C, cellulose degradation between 250 and 500 C and lignin
degradation at a temperature above 400 C [23].
Biomass is composed of different components viz: moisture, extractives, cellulose, hemicellulose, lignin and ash.
These components degrade at different temperatures and
hence the same kinetic parameters can’t be used to study the
thermal behaviour of the whole biomass Based on peaks in
derivative plots, zones were split and degradation temperature ranges of components were identified and quantified.
DTG curves (Figs. 2e4) exhibit two distinct reaction zones
during the thermal degradation of biomass samples. Because
of the two-step nature of process (decomposition), the same
kinetic parameters cannot be applied to predict the thermal
behaviour of the samples throughout its temperature range. It
Table 4 e Sieve analysis of the samples.
Samples
Rice husk
Saw dust
Wheat husk
Mean particle diameter (mm)
485
346
270
is thus, necessary to separate the curves into zones and to
determine the kinetic parameters for each individual zone.
The methodology followed elsewhere is adopted here [24].
The TGA-DTG curves of rice husk (Fig. 2) shows the first
stage of weight loss from 25.77 to 133.38 C which is clearly
distinct from the other stages of weight loss. The derivative
plot (DTG) had a separate peak for this zone of weight loss. It is
due to the evolution of water and light volatile compounds in
the biomass sample.
Following the first stage, there is negligible weight loss in
the temperature range of 133.38-212.41 C. The second phase
of weight loss starts around 212.41 C. The derivative plot of
the region between 212.41 C and 800.00 C showed only one
observable peak. When the data between 212.41 C and
800.00 C is used for determining parameters of reaction kinetics, the r2 values (coefficient of determination) for the
multiple-regression is found to be less than 0.80. This suggested that there may have been two different reaction stages
of weight loss occurring in this region (212.41e800.00 C) [24].
Then, this region is divided into two regions (stages) by
the intersection of the tangents from the descending part of
the peak and the linear part of the DTG plot. The tangents
intersected the region into two halves with one half ranging
212.41-393.20 C and the other between 393.20 and 797.03 C.
Separate reaction kinetics for this temperature range of the
above halves resulted in very high r2 values (0.95, 0.97). The
second reaction zone (212.41e393.20 C) corresponds to
hemicellulose-cellulose degradation while third reaction
C)
corresponds
to
lignin
zone
(393.20e797.03
decomposition.
Similarly, DTG curve for saw dust (Fig. 3) shows two
distinct peaks. The first reaction zone due to the release of
moisture is observed between 30.62 and 113.72 C following
which some negligible weight loss occurred between 113.72
and 182.69 C. Since only one observable peak is found between 182.69 and 797.33 C in the derivative plot, the region is
divided into two regions as like the previous case. The second
reaction zone due to hemicellulose-cellulose degradation is
noticed between 182.69 and 372.14 C whereas the third reaction zone due to lignin deterioration ranged between 372.14
and 797.33 C. The segregation of zones showed improved r2
values (0.94, 0.91).
As like rice husk and saw dust, DTG curve of wheat husk
(Fig. 4) is divided into three zones. The first reaction zone is
noticed between 31.98 and 150.35 C, second reaction zone
between 171.53 and 364.16 C and third reaction zone between
364.16 and 797.49 C. The separation of zones yielded better r2
values (0.95, 0.91).
In all the biomass samples, there are also possibilities that
hemicellulose-cellulose degradation may extend in lignin
degradation temperature zone and lignin degradation starting
in hemicellulose-cellulose degradation. But, comparison of
TGA results with chemical wet analysis illustrated in Fig. 5
infers that overlapping of zones is insignificant (the degradation % of components observed from TGA matches with wet
analysis results). The observed findings for all the three zones
of the samples are given in Table 7. Thermal degradation of
samples is almost complete at the end of the third reaction
zone which is indicated by the linear part of the DTG curve
(Figs. 2e4).
Please cite this article in press as: Parthasarathy P, et al., Study on kinetic parameters of different biomass samples using
thermo-gravimetric analysis, Biomass and Bioenergy (2013), http://dx.doi.org/10.1016/j.biombioe.2013.08.004
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Fig. 1 e Particle size distribution of biomass samples.
3.2.
Initial degradation temperature
The temperature at which the overall degradation starts is
termed as initial degradation temperature. Different components exhibit different degradation temperature which depends on the intrinsic nature of the component. It is observed
that the moisture in the samples is released at temperature
between 25.77 and 31.98 C. The initial degradation of
hemicellulose-cellulose is noticed between 171.53 and
212.41 C. The lignin starts deteriorating between 364.16 and
393.20 C. The variation in the initial degradation temperatures of samples is due to their variance in elemental and the
chemical composition [25].
3.3.
Industrial and commercial processes for gasification, pyrolysis and liquefaction are usually designed for higher temperatures above 600 C at large scale. At these temperatures only
char undergoes heterogeneous reactions fully to leave out
gaseous components. In this study, residual weight of samples is compared at temperature closer to 800 C (797 C). It is
observed that residual weight of rice husk sample (27.65%) is
more than that of saw dust (25.63%) and wheat husk samples
(25.63%). In the residual weight ash accounts for 66.72%,
43.34% and 48.30% in rice husk, saw dust and wheat husk
respectively. Excluding ash, the residual weight may be
Table 5 e Wet chemical analysis of samples.
Rice husk
Saw dust
Wheat husk
Specifications
Make
Model
Balance sensitivity
Balance accuracy
Precision of weighing
Temperature range
Heating and cooling rates
Cool down times
Type of sample
Residual weight
Biomass
Table 6 e Specifications and test conditions of
Thermogravimetric analyzer.
Hemi-cellulose-cellulose (%)
Lignin (%)
53.81
39.87
53.87
14.78
28.87
16.58
TGA atmosphere
Temperature sensors
Cooling medium
and method
Test conditions
Biomass
Rice husk
Wheat husk
Saw dust
Heating rate
Purge gas
Purge gas rate
Initial temperature
of the sample
Final temperature
of the sample
PerkinElmer
Pyris 7 TGA
10 mg (102 mg)
Better than 0.02%
Up to 10 ppm
50 to 1500 C
0.1-200 C min1 in 0.1 C
increments
1500 100 C in less than 15 min
Solids, liquids, powders, films
for fibres
Static or dynamic including
nitrogen, argon, carbon dioxide,
air, oxygen or other inert or
active gases. Analyses may also
be made at normal or reduced
pressure
90% platinum with 10%
rhodiumeplatinum thermocouple
Forced air cooling
Sample size (mg)
17.71
19.42
7.36
10 C/min
Nitrogen
100 ml/min
25.00 C
800.00 C
Please cite this article in press as: Parthasarathy P, et al., Study on kinetic parameters of different biomass samples using
thermo-gravimetric analysis, Biomass and Bioenergy (2013), http://dx.doi.org/10.1016/j.biombioe.2013.08.004
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Fig. 2 e TG-DTG curve of rice husk.
attributed due to the presence of the inorganic mineral contents in the samples.
3.4.
Kinetic parameters
All the biomass samples exhibited three reaction zones. The
kinetic parameters such as preeexponential factor, activation
energy and order of reaction for all three zones of the samples
are determined by multipleelinear regression method in
Microsoft-Excel using Linest function [26]. The initial weight
of samples (w0), final weight of samples (wf), weight of samples undergoing the reaction (w), time taken for the decomposition (t), temperature of decomposition (T ) for every step of
temperature change are made into a Microsoft-Excel sheet.
The temperature range of zones (moisture, primary pyrolysis
and secondary pyrolysis) is identified from the peaks of
TG-DTG curve. The values-ln½ð1=wo wf Þðdw=dtÞ, 1=RTand
lnðw wf =w0 wf Þ which corresponds to y, x and z of equation (5) in the manuscript are calculated for each zones of
temperature range. Then Linest function in Microsoft -Excel is
applied to determine the constants A, E and n which corresponds to pre-exponential factor, activation energy and order
of the reaction.
For rice husk, the activation energy for the first reaction
zone (dehydration) is found to be 55.01 kJ/mol where as for the
second reaction zone (hemicellulose-cellulose) it is 84.13 kJ/
mol. Activation energy for the third reaction zone (lignin) is
21.18 kJ/mol. While determining the activation energy for
Fig. 3 e TG-DTG curve of saw husk.
Please cite this article in press as: Parthasarathy P, et al., Study on kinetic parameters of different biomass samples using
thermo-gravimetric analysis, Biomass and Bioenergy (2013), http://dx.doi.org/10.1016/j.biombioe.2013.08.004
b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 3 ) 1 e9
7
Fig. 4 e TG-DTG curve of wheat husk.
lignin it is found that the lignin exhibited negative activation
energy since rate of thermal degradation decreased with
increasing temperature [27]. Reactions exhibiting these
negative activation energies are referred as barrier less reactions in which the reaction proceeding relies on the capture
of molecules [28]. Increasing the temperature reduces the
probability of capturing of molecules [29]. The observed
negative activation energy may be also due to low order of
lignin decomposition reactions. The methodology used in
determination of kinetic parameters could have also lead to
negative activation energy. The pre-exponential factor is
found to be 7.10*1012, 4.46*1011 and 9.25*103 s1 for the first,
second and third reaction zone respectively. The order of reaction for the first, second and third reaction zone is found to
be 1.14, 0.73 and 0.11.
Mansaray et al. [30] did a similar study on rice husk. They
reported activation energy for the hemicellulose-cellulose
degradation between 142.70 and 188.50 kJ/mol and lignin
degradation between 11.00 and 16.60 kJ/mol. The preexponential factor was reported between 1.18*1014 to
1.22*1017 s1 for the hemicellulose-cellulose degradation and
0.03*102 to 0.56*102 s1 for lignin degradation. In their study,
they found the order of reaction for hemicellulose-cellulose
degradation between 0.70 and 0.83 and lignin degradation
between 0.20-0.29.
In the case of saw dust, the activation energy for the first,
second and third reaction zone is found to be 32.10, 62.29 and
6.52 kJ/mol respectively. Since the reaction rate of lignin
decreased with rise in temperature, it displayed low and
negative activation energy. Correspondingly pre-exponential
Fig. 5 e Comparison of TGA results with wet chemical analysis.
Please cite this article in press as: Parthasarathy P, et al., Study on kinetic parameters of different biomass samples using
thermo-gravimetric analysis, Biomass and Bioenergy (2013), http://dx.doi.org/10.1016/j.biombioe.2013.08.004
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Table 7 e TGA findings.
Sample
Rice husk
Saw dust
Wheat husk
Activation
Order of the r2 value for the Residual
Zone Temperature Degradation (%) Pre-exponential
region in the weight (%)
factor (s1)
energy (kJ/mol)
reaction
range ( C)
TGeDTA curve
I
II
III
I
II
III
I
II
III
25.77e133.38
212.41e393.20
393.20e797.03
30.62e113.72
182.69e372.14
372.14e797.33
31.98e150.35
171.53e364.16
364.16e797.49
8.56
47.85
15.34
10.80
30.58
29.97
10.43
49.84
17.76
7.10*1012
4.46*1011
9.25*103
6.67*109
2.14*1010
1.40*105
3.68*108
5.54*109
2.24*103
55.05
84.13
() 21.18
32.10
62.29
() 6.52
28.60
60.14
() 28.09
1.13
0.73
0.11
0.75
0.67
1.01*103
0.81
0.63
5.01*103
0.88
0.95
0.97
0.85
0.94
0.91
0.84
0.95
0.91
27.65
25.63
25.63
factor for the reaction zones is found to be 6.67*109, 2.14*1010
and 1.40*105 s1. The order of reaction for the first, second and
third reaction zones is determined to be 0.75, 0.67 and
1.01*103 respectively.
Han et al. [31] in their work on saw dust reported the
activation energy for the hemicellulose-cellulose degradation
at 102.00 kJ/mol and lignin degradation at 58.00 kJ/mol.
Further, reported pre-exponential factor for hemicellulosecellulose and lignin degradation are 1.30*108 and 1.00*103 s1
respectively. The order of reaction is reported to be 0.65 for
hemicellulose-cellulose degradation and 0.24 for lignin
degradation.
While studying the kinetic parameters of wheat husk, the
activation energy for the first, second and third reaction zone
is found to be 28.60, 60.14 and 28.09 kJ/mol. In this case also,
the activation energy for lignin degradation is observed to be
negative. The corresponding pre-exponential factor is found
to be 3.68*108, 5.54*109 and 2.24*103 s1 respectively. The order
of reaction for the three zones is found to be 0.81, 0.63 and
5.01*103 respectively.
Lanzetta et al. [32] in their work on wheat straw reported
the activation energy for the hemicellulose-cellulose at
64.63 kJ/mol and lignin degradation at 47.30 kJ/mol. Further,
reported pre-exponential factor for hemicellulose-cellulose
and lignin degradation are 2.43*104 and 5.43*101 s1
respectively.
The difference in kinetic parameter values of the current
and the earlier works is due to the difference in physical and
chemical composition of the samples. The variance in analyser type, analysis methodology, heating rate and atmosphere
also has profound influence on the values of the kinetic
parameters.
In all the samples, it is observed that the order of reaction
for the first and second reaction zones of all samples is close to
one while reaction order for the third reaction zone is near to
zero. Since the second reaction zone degrades at a faster rate,
it is referred as active pyrolysis zone. The third reaction zone
whose order of reaction is close to zero is referred as passive
pyrolysis zone.
conducted at a heating rate of 10 C/min in an inert nitrogen
atmosphere. The thermal degradation temperature range of
biomass components, their initial degradation temperature
and their corresponding weight loss to temperature was
determined.
The degradation temperature range of moisture was
observed between 25.77 and 150.35 C while the cellulosehemicellulose degradation was between 171.53 and
393.20 C. The lignin degradation was in the range of
364.16e797.49 C.
The initial degradation of hemicellulose-cellulose in
biomass samples was noticed between 171.53 and 212.41 C
where as lignin deterioration was observed between 364.16
and 393.20 C. The variation in the initial degradation temperatures of samples is due to their variance in elemental and
the chemical composition. Possibility of hemicellulose cellulose degradation overlapping with lignin degradation and
lignin degradation overlapping with that hemicellulose cellulose also exists.
It was observed that residual weight of rice husk sample
(27.65%) was more than that of saw dust (25.63%) and wheat
husk samples (25.63%). This is due to the presence of the
higher ash and inorganic mineral content in the rice husk
sample.
The kinetic parameters such as activation energy, preexponential factor and order of reaction for all the samples
were determined using modified Arrhenius equation. The
biomass and its components exhibited different kinetic parameters. The difference in kinetic parameter is due to the
difference in physical and chemical composition of the
samples.
Thus, the three distinct reaction zones in TG-DTG
curve of rice husk, saw dust and wheat husk represents
the global kinetics of weight loss occurring during their
thermal transition. The observed kinetics can be used to
predict the thermal behaviour of the samples. However, the
results are bound to vary depending on heating rate, operating atmosphere, instrument used and methodology
adopted.
4.
Acknowledgements
Conclusions
Thus thermogravimetric analysis (TGA) on three different
biomass samples (rice husk, saw dust and wheat husk) was
The authors wish to acknowledge Department of Science and
Technology, New-Delhi, India for their financial support
Please cite this article in press as: Parthasarathy P, et al., Study on kinetic parameters of different biomass samples using
thermo-gravimetric analysis, Biomass and Bioenergy (2013), http://dx.doi.org/10.1016/j.biombioe.2013.08.004
b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 3 ) 1 e9
Nomenclature
A
B
C
D
dw/dt
E
K
n
R
T
t
w
wf
wo
X
pre-exponential or frequency factor (min1)
constant
constant
constant
the ratio of change in weight to change in time
activation energy of the decomposition reaction
(kJ mol1)
reaction constant
order of reaction ()
universal gas constant (kJ mol1K1)
absolute temperature (K)
time (min)
weight of sample at time t (kg)
weight of residue at the end of the reaction (kg)
initial weight of sample (kg)
weight of sample undergoing reaction (kg)
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