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Pyrolysis kinetics and thermodynamic parameters of castor (Ricinus communis) residue using thermogravimetric analysis
Accepted Manuscript Pyrolysis kinetics and thermodynamic parameters of castor (Ricinus communis) residue using thermogravimetric analysis Ravneet Kaur, Poonam Gera, Mithilesh Kumar Jha, Thallada Bhaskar PII: DOI: Reference:
S0960-8524(17)32081-3 https://doi.org/10.1016/j.biortech.2017.11.077 BITE 19227
To appear in:
Bioresource Technology
Received Date: Revised Date: Accepted Date:
25 September 2017 18 November 2017 22 November 2017
Please cite this article as: Kaur, R., Gera, P., Jha, M.K., Bhaskar, T., Pyrolysis kinetics and thermodynamic parameters of castor (Ricinus communis) residue using thermogravimetric analysis, Bioresource Technology (2017), doi: https://doi.org/10.1016/j.biortech.2017.11.077
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Pyrolysis kinetics and thermodynamic parameters of castor (Ricinus communis) residue using thermogravimetric analysis Ravneet Kaur1,2, Poonam Gera1, Mithilesh Kumar Jha1, Thallada Bhaskar2, 3* 1
Dr B R Ambedkar National Institute of Technology, Jalandhar 2
3
CSIR-Indian Institute of Petroleum, Dehradun
Academy of Scientific and Innovative Research (AcSIR), New Delhi *
Corresponding author: [email protected];[email protected] Phone: +91 135 2525820, Fax: +91 135 2660202
ABSTRACT Castor plant is a fast-growing, perennial shrub from Euphorbiaceae family. More than 50% of the residue is generated from its stems and leaves. The main aim of this work is to study the pyrolytic characteristics, kinetics and thermodynamic properties of castor residue. The TGA experiments were carried out from room temperature to 900°C under an inert atmosphere at different heating rates of 5, 10, 15, 20, 30 and 40°C/min. The kinetic analysis was carried using different models namely Kissinger, Flynn- WallOzawa (FWO) and Kissinger-Akahira-Sunose (KAS). The average Eɑ calculated by FWO and KAS methods were 167.10 and 165.86 kJ/mole respectively. Gibbs free energy varied from 150.62-154.33 and 150.59-154.65 kJ/mol for FWO and KAS respectively. The HHV of castor residue was 14.43 MJ/kg, considered as potential feedstock for bio-energy production. Kinetic and thermodynamic results will be useful input for the design of pyrolytic process using castor residue as feedstock.
Keywords: Castor residue, Thermogravimetric Analysis, Model-free methods, Activation Energy, Thermodynamic parameters
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1.
Introduction Environmental problems coupled with fossil fuel depletion has stimulated research to
develop biofuels. Biomass is one of the most important renewable energy sources which is rich in cellulose and other organic compounds used to produce chemical products and energy (Van Rossum et al., 2007). Extensive studies have been done worldwide on the recovery of energy from waste materials including plastics, rubbers, waste paper, wood etc. Biomass is getting much attention as a renewable green energy source due to its advantages. Lignocellulosic biomass contains cellulose (32-45%), hemicellulose (1925%) and lignin (14-26%). Cellulose is a linear chain polysaccharide having several β(1→4) linked D-glucose units. Cellulose exhibits more thermal resistance and its degradation temperature range varies from 315-400°C (Islam et al., 2015; Yang et al., 2007). Hemicellulose is the polymers made up of sugar units, amorphous in nature, has branched structure and degrades easily at temperate of around 220-315°C. Lignin is a crosslinked, complex polymer having phenylpropane units and has decomposition range of 150-900°C (Yang et al., 2007). Thermogravimetric analysis (TGA) is the most common technique used to investigate the decomposition behaviour of a substance with respect to temperature and has no limitations in heat and mass transfer at low heating rates (Kovfopanos et al., 1989; Muller-Hagedorn et al., 2003; Mansaray and Ghaly, 1998). TGA is preferred because it is simple and a highly -precise method to study biomass kinetics. The steps involved in thermal degradation of biomass to its components are (i) moisture evolution (ii) hemicellulose degradation (iii) cellulose degradation (iv) lignin degradation (Raveendran et al., 1996). Different thermochemical processes being used to convert biomass into bioproducts and bioenergy are Pyrolysis, Liquefaction, Combustion, and Gasification. Pyrolysis is the process where biomass is heated in the absence of oxygen to obtain bio oil, solid residue, and gas. These products can be used as biofuels, biochemicals and value-added products. Biomass pyrolysis involves complex reactions by which reaction mechanism and kinetic modeling become difficult. For a better understanding of reaction mechanism different kinetic models have already been designed by different researchers. India ranked first in the world for castor seed production (2236000MT) in 2016 (Comprehensive Castor Oil Report, April 2017). The three parts of castor plant are
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stem, leaves, and seeds. The residue generated per ton of castor plant stems 388 kg, leaves 144 kg, and seeds 468 kg (Bateni et al., 2014). Castor oil has many industrial and medicinal applications. The kinetic study of castor bean presscake was reported by different researchers (Thiagarajan, 2016; Santos, 2015). The castor seed cake was pyrolyzed at different reaction conditions. Highest amount of bio oil (63% w/w) was obtained at 400°C for 60 min (Aldobouni et al., 2015). Regardless of numerous studies on biomass pyrolysis kinetics, no kinetic study has been reported yet using castor plant wastes (leaves and stems) as raw material. The stems and leaves of castor plant are not much utilized and considered as a waste. More than 50% of residue is generated from stems and leaves. This study is an attempt to know the pyrolytic behavior of castor residue. In this study the kinetic parameters (Activation Energy and Pre-exponential factor) have been calculated by using model-free methods. Thermodynamic parameters such as Enthalpy (∆H), Gibbs free energy (∆G), and Entropy change (∆S) were also determined.
2.
Materials and methods
2.1
Sample preparation and characterization The castor residue (leaves and stems) used in the study as lignocellulosic biomass
was collected from NIT boundary (31.3962° N, 75.5354° E) Jalandhar, Punjab. The sample was first washed with water to remove dust, dried and then crushed into powder form. Sieving of the powdered sample was done to an average size of 50µm. Moisture content, Ash content and Volatile matter were determined using ASTM D-3173, ASTM D-3174, and ASTM D-3175 respectively. Fixed carbon (FC) was calculated by FC (wt.%) =100 - (Moisture (wt.%) + Ash (wt.%) + Volatile Matter (wt.%))
(1)
Ultimate/Elemental analysis of raw material was done using Thermo Scientific (FLASH 2000) CHN analyzer. Extractives present in the biomass was calculated using NREL procedure or ASTM standard Test Method E 1690. Lignin and cellulose content present in raw material was determined using Tappi T222 and Tappi T202 method respectively. Chloride method (Wise and John, 1952) was used to determine holocellulose (cellulose + hemicellulose) content present in biomass. HHV of the raw material was calculated by using Dulong’s formula. Heating value(MJ/kg) = 0.338C+ 1.428 (H-O/8) + 0.095S
(2)
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where, C, H, O and S were weight percentages of elemental compositions in materials. 2.2
Analysis The thermogravimetric analysis of raw material was carried out in Shimadzu DTG-
60 instrument. A fine castor powder of 6-8 mg was placed in a small alumina crucible and heated from room temperature to 900°C at different heating rates of 5, 10, 15, 20, 30 and 40 °C/min. Nitrogen was used as an inert gas with a flow rate of 100 ml/min. The experiments were replicated at least thrice for the accuracy of results.
2.3
Kinetic theory
The primary pyrolysis is represented by the following reaction mechanism: k
Biomass
Volatiles + char
(3)
where volatiles include the sum of gas and tar and k is stated as the rate constant. The rate of conversion from solid-state to the volatile product can be described by the following reaction: ɑ
= ɑ
(4)
Conversion (ɑ), is assigned a form of weight loss data of decomposed sample and is defined as follows:
ɑ=
−
−
(5)
where, mi is the sample mass at the beginning, mf is the sample mass at the end of the reaction, and mɑ represents the mass of the sample at time t. T is the temperature, k(T) is the rate constant is expressed by Arrhenius equation.
=
/
(6)
Substituting the value of k in equation (4),
ɑ = . ɑ. /
(7)
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The expression of function f(ɑ) and its derivative f’(ɑ) = -1 are used for explaining solid- state first order reaction; hence many authors define the mathematical function f(ɑ) to the following expression:
ɑ = 1 − ɑ
(8)
Then equation (7) becomes,
ɑ = . 1 − ɑ . /
(9)
Taking into account that the temperature is a function of time and that it is increasing at fixed heating rate, then β can be written as,
=
ɑ = ɑ
(10)
Then equation (9) becomes,
ɑ = . 1 − ɑ . /
(11)
Equation (11) represents the fraction of material consumed as per time. Integrating the equation (11) gives:
! = "
#
! −( = " exp ' * ! + )
(12)
where G(α) is the integral form of the conversion dependence function f(ɑ). This equation (12) has no explicit solution. Some interpolation formulas in terms of Doyle (1965), Agrawal (1987), Gorbatchev (1974), and Frank- Kameneshii (1955) approximations were used. 2.4 Model-free methods Model-free methods does not require assumption of any reaction model. Kinetic parameters are calculated from several curves at different heating rates on the same value of conversion. These methods are highly suggested by the Kinetics Committee of the International Confederation for Thermal Analysis and Calorimetry (ICTAC Kinetics Committee) (Vyazovkin et al., 2011). The main aim of using Model-free methods is their simplicity and avoidance of error related to the choice of kinetic model. The most popular representatives of isoconversional methods are Kissinger, Friedman (FR),
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Kissinger- Akahira- Sunose (KAS), Flynn- Wall-Ozawa (FWO), and Vyazovkin (V). The model-free methods Kissinger, Kissinger- Akahira- Sunose (KAS), Flynn- WallOzawa (FWO) have been used in this study. 2.4.1 Kissinger Method Kissinger (1956) formulated a model-free nonisothermal method where activation energy is assumed to be constant at a given conversion. This method allows to calculate the activation energy from a plot of ln (β/T2m) vs. 1/Tm for different heating rates (β), Tm is the peak temperature of the DTG curve. The equation of Kissinger method is:
,- '
. 23 45 * = ,- ' * − 1 /0 4 3/0
(13)
Activation Energy is calculated from slope equal to−( ⁄). 2.4.2 Flynn- Wall- Ozawa method The FWO method (Flynn and Wall, 1966; Ozawa, 1965) is used to calculate the apparent activation energy (Eɑ) from a plot of ln β vs. 1/Tɑi, which depicts the linear relation with a given value of conversion at different heating rates. Using Doyle’s approximation (Doyle, 1965), the final form of FWO equation is:
,-.7 = ,- '
2ɑ 4ɑ 4ɑ * − 9. ::; − ;. <91 38ɑ 3/ɑ7
(14)
The subscripts i and ɑ denotes given value of heating rate and conversion respectively. The activation energy Eɑ is calculated from the slope -1.052 Eɑ/R. 2.4.3 Kissinger- Akahira- Sunose The KAS method (Kissinger, 1956; Akahira and Sunose, 1971) is one of the most widely used for biomass pyrolysis kinetic study in literature. By introducing Doyle’s approximation (Doyle, 1965), final equation is as follows:
,- =
. 2ɑ 3 4ɑ 1 > = ,- 4 8 − 3/ /ɑ7 ɑ ɑ 57
(15)
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A The apparent activation energy can be calculated from a plot of ln ⁄ vs. 1/Tɑi for
a given value of conversion, ɑ, where the slope is = -Eɑ/R.
Pre-exponential factor (A) in Arrhenius equation was calculated by:
45 2 = .. 45. BCD ' * /3. /10 3. /0
(16)
The thermodynamic parameters like Enthalpy (∆H), Gibbs free energy (∆G) and the changes of Entropy (∆S) were calculated by following equations:
∆F = 45 − 3/
∆G = 45 + 3. /0 . IJ ' ∆N =
∆F − ∆G /0
(17)
KL . /0 * M. 2
(18) (19)
where, KB = Boltzmann constant (1.381*10 -23J/K); h= Plank constant (6.626*10-34 J.s); Tm = Peak temperature. 3. 3.1
Results and Discussions Characterization of raw material The Ultimate, Proximate, and Component analysis and HHV of castor residue are
shown in Table 1. The carbon, hydrogen, nitrogen and oxygen content of castor residue was 43.59 wt.%, 5.56 wt.%, 4.69 wt. %, and 46.16 wt.% respectively. The HHV of castor residue was 14.43 MJ/kg. Higher content of oxygen may impart negative effect on the HHV. The nitrogen content present in castor residue is high, which may produce NOx emissions during combustion (Damartzis et al., 2011). Biomass having low lignin content is generally preferred as lighter products are formed from it and obtained biooil can be used as a fuel (Ghetti et al., 1996). Castor residue has volatile content of ~ 7275% which is good for combustion and gasification process. The ash content of castor residue is 5.4% which is low as compared with literature (Dhyani and Bhaskar, 2017). High ash content may affect the burning rate and cause aggregation and fouling problems. The other disadvantages of high ash content are: it increases the processing costs, poor combustion, reduced energy conversion and disposal problems (Mckendry,
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2002; Sait et al., 2012). Inorganic minerals (alkaline and alkaline – earth) present in ash affects the mechanism of biomass pyrolysis (Kan et al., 2016). “Table 1 here’’
3.2 Thermal degradation process Fig. 1(a). shows the weight loss curves obtained during the pyrolysis of castor residue under an inert atmosphere. The samples were heated from room temperature to 900˚C at heating rates of 5, 10, 15, 20, 30 and 40 ˚C/min constantly. Castor residue is a lignocellulosic biomass composed of cellulose, hemicellulose, and lignin. Each component has different decomposition temperature region (Yang et al., 2006). The variation in pyrolysis of biomass is due to its chemical composition of components present in it. The decomposition process of castor residue was done in three stages. In the first stage (1) release of weakly bonded water molecules and hydrolysis of some extractives was observed with a small hump at temperature up to 128˚C. This stage is known dehydration stage. (2) Active Pyrolysis involves the decomposition of hemicellulose, cellulose and small amount of lignin at temperature range of 160-520˚C. The first peak represents the decomposition of hemicellulose and second peak corresponds to the decomposition of cellulose. The decomposition of cellulosic part occurs in two ways: (i) Formation of CO, CO2 and carbonaceous by breakdown of bonds and polymers at low temperature; (ii) Integration of bonds at high temperature leads liquid formation (Çepelioǧullar and Pütün, 2013); (3) The decomposition of lignin was observed in passive pyrolysis at temperature range of 150-900˚C. Char is the major product produced during passive pyrolysis (Zabaniotou et al., 2008). “Figure 1(a) here’’ The information about the effect of heating rate is necessary as it affects the conversion, product distribution and gives an idea about the reactor to be used (Garcı, 2000). Fig. 1(b) shows the derivative thermal profiles of the decomposition of castor residue at different heating rates (5, 10, 15, 20, 30 and 40 °C/min). It was observed that the increase in heating rates shifts the peak temperature to higher value. The change in behaviour is due to poor heat transfer and change in the reaction mechanism. Lower heating rates were generally preferred as heating of biomass particles occurs constantly,
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and it provides better heat transfer to the inner part of the biomass (Chutia et al., 2013). Increasing the heating rate releases more volatile materials and less residues were left after the pyrolysis. “Figure 1(b) here’’ 3.3 Kinetic Analysis The Kinetic study is an important parameter in the efficient design of thermochemical processes for the conversion of biomass. The kinetic parameters like activation energy and pre-exponential factor of castor residue were calculated using model-free methods. Fig. 1(c). shows the change of conversion with respect to temperature at different heating rates. Fig. S(1) shows Kissinger plot for the calculation of kinetic parameters. The activation energy, pre-exponential factor and correlation factor calculated using equation (13) were 192.809 kJ/mol, 5.34E+13 and 99.06 respectively. Isoconversional FWO and KAS linear model equations were used to calculate the apparent activation energy based on conversion. Fig. 2(a) and Fig. 2(b) shows FWO plot and KAS plot respectively. “Figure 1(c) here’’ “Figure 2(a) here’’ “Figure 2(b) here’’ The kinetic parameters calculated using equations (14), (15) and (16) are shown in Table 2. Conversion value of 0.2-0.8 is used as below 0.2 and above 0.8 the value of correlation factor is very low (Damartzis et al., 2011). Activation energy is defined as the minimum amount of energy required to start a reaction. It is difficult to start a reaction that requires high activation energy. Activation energy is also used to know the reactivity of a fuel (Gai et al., 2013). An increase in apparent activation energy was observed during the initial stages of pyrolysis. As the conversion increases, the apparent activation energy decreases. The change in activation energy with respect to conversion is shown in Fig. 3. An increase in activation energy from 0.2-0.5 shows the presence of endothermic reactions while the decrease in activation energy from 0.6-0.8 indicates the presence of exothermic reactions. This fluctuation in activation energy is due to the complex reaction schemes shows the involvement of parallel, complex and competitive
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reactions under inert atmosphere (Ma et al., 2015). The variation in activation energy w.r.t. conversion is also due to percentage of components present in biomass and their interactions among themselves. The activation energies of cellulose, hemicellulose and lignin degradation are in the range of 145-285, 90-125 and 30-39 kJ/mol respectively (Vamvuka et al., 2003). It was observed that castor residue has more cellulose content (38.42 %) so it requires more activation energy for decomposition which was increased at ɑ= 0.4 to 0.5. The same was observed in the case of chestnut shells (Özsin and Pütün, 2017). Another study on Hazelnut husk (Ceylan and Topcu, 2014) also confirms the same where apparent activation energy calculated using FWO and KAS method is less as the residue has less cellulose content (34.5 %) compared to castor residue. The activation energy calculated from model-free methods were also found similar to the literature values which reveals that there was decomposition of biomass components i.e., cellulose, hemicellulose, and lignin (Balogun et al., 2014; Damartzis et al., 2011; Gai et al., 2013). The average activation energy calculated over whole conversion range using KAS and FWO method was 165.86 and 167.10 kJ/mol respectively. The difference in activation energies is due to approximations and calculations used to solve temperature integral of the model-free methods. The average activation energy of castor residue was less than from Para grass (Ahmad et al., 2017), rice husk and elephant grass (Braga et al., 2014). Lower E values of castor residues reflect that it may be used for cofiring with other biomasses having lower or higher E values. The above finding makes the castor residue suitable for thermal conversion of biomass to value-added products/bioenergy. “Figure 3 here’’ The pre-exponential value ranges from 108-1018 and 10 7-10 18 were determined using FWO and KAS methods respectively. Low pre-exponential factors generally (<109s-1) shows the surface reaction. When the reaction is not dependent on surface area, then the low value of pre-exponential factor shows the closed complex. Higher value of A indicates simple complex. The empirical first-order pre-exponential factor range may vary from 104 to 1018 s-1 (Turmanova et al., 2008). Variation in pre-exponential values with conversion is due to the complex composition of biomass sample and complex reactions take place during decomposition. Fig. S(2) and S(3) shows the compensation effects between the activation energy and pre-exponential factor at different heating
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rates. It was observed that the value of pre-exponential factor increases with increase in heating rate which may be due to increase in collision intensity at high heating rate. The A values of castor residue were almost equal to Para grass (Ahmad et al., 2017) and higher than RPW, rice bran, rice straw and Chicken manure (Maia and de Morais, 2016; Xu and Chen, 2013). This behavior showed the complex nature of castor residue and the components present in biomass follows multi-step degradation reaction chemistry. 3.5 Thermodynamic Parameters Equations (17), (18), (19) were used to calculate thermodynamic parameters and corresponding results are shown in Table 2. Enthalpy is the thermodynamic property which represents the total heat content of a system. For pyrolysis, enthalpy means the total energy consumed by the biomass for its conversion to various products like oil, gas, and char (Daugaard and Brown, 2003). The change in enthalpy with respect to the conversion is also shown in Fig. 4. It was observed that the little change in the enthalpy and activation energy (~5-6 kJ/mol) at each conversion point is due to the energy difference between the activated complex and the reagent. Less energy difference boosts the formation of activated complex (Vlaev et al., 2007). The closeness of ∆H values vs. Eɑ values states that product formation may be done by providing an amount of 5 kJ/mol of additional energy (Mehmood et al., 2017). It was noticed that the enthalpy variation for castor residue was 162.15 and 160.91 kJ/mol using FWO and KAS respectively while for RPW (red pepper waste) (Maia and de Morais, 2016), Rice Bran, Rice Straw, Chicken Manure, Dairy Manure (Xu and Chen, 2013) and Para grass (Ahmad et al., 2017) was 23.37-142.21, 111.03,162.23, 170.29, 153.10 and 173.66 kJ/mol respectively. “Figure 4 here’’ Gibbs free energy is also known as Free Enthalpy means the total increase in energy of the system for the formation of the activated complex (Kim et al., 2010; Sheng et al., 2014; Turmanova et al., 2008). Fig. 5(a) and (b) represents the change of Gibbs free energy at different heating rates calculated by FWO and KAS method respectively. The ∆G value of castor residue was 150.62-154.33 and 150.59-154.65 kJ/mol calculated using FWO and KAS respectively. The change in Gibbs free energy for RPW(Maia and de Morais, 2016), Rice Bran, Rice Straw, Chicken Manure, Dairy
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Manure (Xu and Chen, 2013) and Para grass (Ahmad et al., 2017) were 71.77-207.03, 167.17, 164.59, 175.29, 176.60 and 169-173 (KAS) 168-172 (FWO) kJ/mol respectively. The average ∆G value for castor residue (152.00 kJ/mole) was higher than the average ∆G value of RPW (139.40 kJ/mole). “Figure 5(a) here’’ “Figure 5(b) here’’ Fig. 6 (a) and (b) represents the positive and negative values of change of entropy calculated by FWO and KAS method respectively. It was observed that the castor residue has both negative (-108.02 J/mol) and positive values (102.82 J/mol). Negative values of ∆S shows the degree of disorder of products produced through bond dissociations were lower than initial reactants. The low ∆S means the material just passes through some physical and chemical changes, bringing it to state near to its thermodynamic equilibrium. In this state, material shows little reactivity and takes more time to form activated complex. On the other hand, high ∆S means reactivity will be high and less time is consumed to form activated complex. “Figure 6(a) here’’ “Figure 6(b) here’’ “Table 2 here’’ Conclusions Castor residue has high volatile content and high heating value (14.43 MJ/kg). Sulphur content was not detected in castor residue. There is a little variation in the apparent activation energy (Eɑ) calculated by FWO (167.10 kJ/mole) and KAS (165.86 kJ/mole) methods. Pre-exponential factor (A) results varies from 10 8-1018 and 107-1018 for FWO and KAS methods respectively. The average ∆G value of castor residue (152 kJ/mole) shows more available energy to be considered as a raw material for bioenergy production. It is observed that the castor residue has significant potential to be used as a feedstock for bioenergy/biofuels production. Acknowledgement
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The authors gratefully acknowledge the Director, CSIR-Indian Institute of Petroleum (IIP) and Director, National Institute of Technology, Jalandhar for constant endorse in all ways. RK thanks the TPA group of Bio-Fuels Division at CSIR-Indian Institute of Petroleum (IIP) for providing analytical support. RK acknowledges MHRD, Govt of India for rendering fellowship and NIT Jalandhar for their financial support for carrying out this work. References [1] Agrawal, R.K., Sivasubramanian, M.S., 1987. Integral approximations for nonisothermal kinetics. AIChE J. 33, 1212–1214. doi:10.1002/aic.690330716 [2] Ahmad, M.S., Mehmood, M.A., Al Ayed, O.S., Ye, G., Luo, H., Ibrahim, M., Rashid, U., Arbi Nehdi, I., Qadir, G., 2017. Kinetic analyses and pyrolytic behavior of Para grass (Urochloa mutica) for its bioenergy potential. Bioresour. Technol. 224, 708–713. doi:10.1016/j.biortech.2016.10.090 [3] Akahira, T., Sunose, T., 1971. Method of determining activation deterioration constant of electrical insulating materials. Res. Rep. Chiba Inst. Technol. (Sci. Technol.) 16, 22–31. [4] Aldobouni, I.A., Fadhil, A.B., Saied, I.K., 2015. Conversion of de-oiled castor seed cake into bio-oil and carbon adsorbents. Energ. Source Part A 37, 26172624. doi:10.1080/15567036.2012.733482 [5] Balogun, A.O., Lasode, O.A., McDonald, A.G., 2014. Devolatilisation kinetics and pyrolytic analyses of Tectona grandis (teak). Bioresour. Technol. 156, 57– 62. doi:10.1016/j.biortech.2014.01.007 [6] Bateni, H., Karimi, K., Zamani, A., Benakashani, F., 2014. Castor plant for biodiesel, biogas, and ethanol production with a biorefinery processing perspective. Appl. Energy 136, 14–22. doi:10.1016/j.apenergy.2014.09.005 [7] Braga, R.M., Melo, D.M., Aquino, F.M., Freitas, J.C., Melo, M.A., Barros, J.M., Fontes, M.S., 2014. Characterization and comparative study of pyrolysis kinetics of the rice husk and the elephant grass. J. Therm. Anal. Calorim. 115, 1915-1920. [8] Çepelioǧullar, Ö., Pütün, A.E., 2013. Thermal and kinetic behaviors of biomass and plastic wastes in co-pyrolysis. Energy Convers. Manag. 75, 263–270.
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17
Figure Captions Fig. 1(a) Thermogravimetric curves (b) Derivative Thermogravimetric curves (c) Extent of conversion curves for the devolatilization process of castor residue at different heating rates. Fig. 2. Linear plot for determining activation energy of castor residue calculated by (a) FWO (b) KAS method. Fig. 3. Activation Energy as a function of conversion. Fig. 4. Change in Enthalpy as a function of conversion. Fig. 5. Change in Gibbs Energy as a function of conversion calculated by (a) FWO (b) KAS method. Fig.6. Change in Entropy as a function of conversion calculated by (a) FWO (b) KAS method.
18
Table 1 Elemental, Proximate, Component analysis of castor residue Elements
wt.%
wt.%
43.59
Proximate Analysis Moisture
Carbon Hydrogen
5.56
Ash
Nitrogen
4.69
Sulphur
ND
Oxygen*
46.16
Volatile 74.30 Matter Fixed 9.16 Carbon * by difference ND: Not Detected
HHV(MJ/kg) 14.43
11.14
Component Analysis Extractives
wt.% 16.40
5.40
Cellulose
38.42
Hemicellulose
22.40
Lignin
20.20
19
Table 2 Conversion points, Kinetics and corresponding thermodynamic parameters Conversion Activation Preexponential R2 ∆H* ∆G* ∆S* Points (α) Energy factor* (kJ/mol) (kJ/mol) (kJ/mol) (kJ/mol) (s-1) FWO method 0.2 127.81 7.28E+10 0.99 122.86 153.20 -51.01 0.3 143.57 1.98E+12 0.99 138.62 152.63 -23.54 0.4 214.33 4.85E+18 0.99 209.38 150.64 98.74 0.5 215.56 6.26E+18 0.99 210.61 150.62 100.86 0.6 206.24 9.09E+17 0.99 201.29 150.84 84.82 0.7 160.32 6.55E+13 0.99 155.37 152.08 5.53 0.8 101.87 3.06E+08 0.99 96.92 154.33 -96.51 Average 167.10 162.15 152.05 KAS method 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Average
126.17 142.14 216.02 216.70 206.78 157.83 95.35 165.85
5.17E+10 1.47E+12 6.88E+18 7.92E+18 1.02E+18 3.89E+13 7.68E+07
0.99 0.99 0.98 0.99 0.99 0.99 0.98
121.22 137.19 211.07 211.75 201.83 152.88 90.40 160.91
153.27 152.68 150.61 150.59 150.82 152.16 154.65 152.11
-53.87 -26.03 101.65 102.82 85.76 1.20 -108.01
*results calculated at 10°C/min.
20
Fig.1(a) 100
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
90 80
Weight loss (%)
70 60 50 40 30 20 10
1(a) 0 200
400
600
800
Temperature (°C)
Fig.1(b)
21
0.000 -0.002 -0.004
DTG (mg/sec)
-0.006 -0.008
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
-0.010 -0.012 -0.014 -0.016 -0.018
1(b) -0.020 200
400
600
800
Temperature (°C)
Fig.1(c)
22
1.0
1(c)
Conversion(α)
0.8
0.6
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
0.4
0.2
0.0 200
400
600
800
Temperature (°C)
Fig.2(a)
23
4.0
0.2 0.3 0.4 0.5 0.6 0.7 0.8
3.5
ln(β)
3.0
2.5
2.0
1.5
2(a) 1.2
1.4
1.6
1.8
2.0
2.2
-1
1/T (K )
Fig.2(b) -8.5
0.2 0.3 0.4 0.5 0.6 0.7 0.8
-9.0
2
ln(β/T )
-9.5
-10.0
-10.5
-11.0
-11.5
2(b) 1.4
1.6
1.8
2.0
2.2
-1
1/T (K )
Fig.3
24
250
Activation Energy (kJ/mol)
3
KAS FWO
200
150
100
50 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Conversion (α)
Fig.4
25
250
4
FWO KAS
200
∆H(kJ/mol)
150
100
50
0 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Conversion (α)
Fig.5(a)
26
5(a)
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
∆G(kJ/mol)
155
153
151
149 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Conversion(α)
Fig.5(b).
157
5(b)
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
156 155
∆G(kJ/mole)
154 153 152 151 150 149 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Conversion(α)
27
Fig.6(a). 100
6(a)
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
∆S(J/mole)
50
0 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Conversion (α) -50
-100
Fig.6(b).
100
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
5(b)
∆S(J/mole)
50
0 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Conversion(α) -50
-100
28
Highlights • • • •
The first study on pyrolysis kinetics of castor residue (leaves and stems). The thermal conversion of castor residue was characterized by TG-DTG. The thermodynamic parameters (∆H, ∆G, ∆S) were calculated. Castor residue has potential to be used as biofuel or bioenergy production.
29
S0960-8524(17)32081-3 https://doi.org/10.1016/j.biortech.2017.11.077 BITE 19227
To appear in:
Bioresource Technology
Received Date: Revised Date: Accepted Date:
25 September 2017 18 November 2017 22 November 2017
Please cite this article as: Kaur, R., Gera, P., Jha, M.K., Bhaskar, T., Pyrolysis kinetics and thermodynamic parameters of castor (Ricinus communis) residue using thermogravimetric analysis, Bioresource Technology (2017), doi: https://doi.org/10.1016/j.biortech.2017.11.077
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Pyrolysis kinetics and thermodynamic parameters of castor (Ricinus communis) residue using thermogravimetric analysis Ravneet Kaur1,2, Poonam Gera1, Mithilesh Kumar Jha1, Thallada Bhaskar2, 3* 1
Dr B R Ambedkar National Institute of Technology, Jalandhar 2
3
CSIR-Indian Institute of Petroleum, Dehradun
Academy of Scientific and Innovative Research (AcSIR), New Delhi *
Corresponding author: [email protected];[email protected] Phone: +91 135 2525820, Fax: +91 135 2660202
ABSTRACT Castor plant is a fast-growing, perennial shrub from Euphorbiaceae family. More than 50% of the residue is generated from its stems and leaves. The main aim of this work is to study the pyrolytic characteristics, kinetics and thermodynamic properties of castor residue. The TGA experiments were carried out from room temperature to 900°C under an inert atmosphere at different heating rates of 5, 10, 15, 20, 30 and 40°C/min. The kinetic analysis was carried using different models namely Kissinger, Flynn- WallOzawa (FWO) and Kissinger-Akahira-Sunose (KAS). The average Eɑ calculated by FWO and KAS methods were 167.10 and 165.86 kJ/mole respectively. Gibbs free energy varied from 150.62-154.33 and 150.59-154.65 kJ/mol for FWO and KAS respectively. The HHV of castor residue was 14.43 MJ/kg, considered as potential feedstock for bio-energy production. Kinetic and thermodynamic results will be useful input for the design of pyrolytic process using castor residue as feedstock.
Keywords: Castor residue, Thermogravimetric Analysis, Model-free methods, Activation Energy, Thermodynamic parameters
1
1.
Introduction Environmental problems coupled with fossil fuel depletion has stimulated research to
develop biofuels. Biomass is one of the most important renewable energy sources which is rich in cellulose and other organic compounds used to produce chemical products and energy (Van Rossum et al., 2007). Extensive studies have been done worldwide on the recovery of energy from waste materials including plastics, rubbers, waste paper, wood etc. Biomass is getting much attention as a renewable green energy source due to its advantages. Lignocellulosic biomass contains cellulose (32-45%), hemicellulose (1925%) and lignin (14-26%). Cellulose is a linear chain polysaccharide having several β(1→4) linked D-glucose units. Cellulose exhibits more thermal resistance and its degradation temperature range varies from 315-400°C (Islam et al., 2015; Yang et al., 2007). Hemicellulose is the polymers made up of sugar units, amorphous in nature, has branched structure and degrades easily at temperate of around 220-315°C. Lignin is a crosslinked, complex polymer having phenylpropane units and has decomposition range of 150-900°C (Yang et al., 2007). Thermogravimetric analysis (TGA) is the most common technique used to investigate the decomposition behaviour of a substance with respect to temperature and has no limitations in heat and mass transfer at low heating rates (Kovfopanos et al., 1989; Muller-Hagedorn et al., 2003; Mansaray and Ghaly, 1998). TGA is preferred because it is simple and a highly -precise method to study biomass kinetics. The steps involved in thermal degradation of biomass to its components are (i) moisture evolution (ii) hemicellulose degradation (iii) cellulose degradation (iv) lignin degradation (Raveendran et al., 1996). Different thermochemical processes being used to convert biomass into bioproducts and bioenergy are Pyrolysis, Liquefaction, Combustion, and Gasification. Pyrolysis is the process where biomass is heated in the absence of oxygen to obtain bio oil, solid residue, and gas. These products can be used as biofuels, biochemicals and value-added products. Biomass pyrolysis involves complex reactions by which reaction mechanism and kinetic modeling become difficult. For a better understanding of reaction mechanism different kinetic models have already been designed by different researchers. India ranked first in the world for castor seed production (2236000MT) in 2016 (Comprehensive Castor Oil Report, April 2017). The three parts of castor plant are
2
stem, leaves, and seeds. The residue generated per ton of castor plant stems 388 kg, leaves 144 kg, and seeds 468 kg (Bateni et al., 2014). Castor oil has many industrial and medicinal applications. The kinetic study of castor bean presscake was reported by different researchers (Thiagarajan, 2016; Santos, 2015). The castor seed cake was pyrolyzed at different reaction conditions. Highest amount of bio oil (63% w/w) was obtained at 400°C for 60 min (Aldobouni et al., 2015). Regardless of numerous studies on biomass pyrolysis kinetics, no kinetic study has been reported yet using castor plant wastes (leaves and stems) as raw material. The stems and leaves of castor plant are not much utilized and considered as a waste. More than 50% of residue is generated from stems and leaves. This study is an attempt to know the pyrolytic behavior of castor residue. In this study the kinetic parameters (Activation Energy and Pre-exponential factor) have been calculated by using model-free methods. Thermodynamic parameters such as Enthalpy (∆H), Gibbs free energy (∆G), and Entropy change (∆S) were also determined.
2.
Materials and methods
2.1
Sample preparation and characterization The castor residue (leaves and stems) used in the study as lignocellulosic biomass
was collected from NIT boundary (31.3962° N, 75.5354° E) Jalandhar, Punjab. The sample was first washed with water to remove dust, dried and then crushed into powder form. Sieving of the powdered sample was done to an average size of 50µm. Moisture content, Ash content and Volatile matter were determined using ASTM D-3173, ASTM D-3174, and ASTM D-3175 respectively. Fixed carbon (FC) was calculated by FC (wt.%) =100 - (Moisture (wt.%) + Ash (wt.%) + Volatile Matter (wt.%))
(1)
Ultimate/Elemental analysis of raw material was done using Thermo Scientific (FLASH 2000) CHN analyzer. Extractives present in the biomass was calculated using NREL procedure or ASTM standard Test Method E 1690. Lignin and cellulose content present in raw material was determined using Tappi T222 and Tappi T202 method respectively. Chloride method (Wise and John, 1952) was used to determine holocellulose (cellulose + hemicellulose) content present in biomass. HHV of the raw material was calculated by using Dulong’s formula. Heating value(MJ/kg) = 0.338C+ 1.428 (H-O/8) + 0.095S
(2)
3
where, C, H, O and S were weight percentages of elemental compositions in materials. 2.2
Analysis The thermogravimetric analysis of raw material was carried out in Shimadzu DTG-
60 instrument. A fine castor powder of 6-8 mg was placed in a small alumina crucible and heated from room temperature to 900°C at different heating rates of 5, 10, 15, 20, 30 and 40 °C/min. Nitrogen was used as an inert gas with a flow rate of 100 ml/min. The experiments were replicated at least thrice for the accuracy of results.
2.3
Kinetic theory
The primary pyrolysis is represented by the following reaction mechanism: k
Biomass
Volatiles + char
(3)
where volatiles include the sum of gas and tar and k is stated as the rate constant. The rate of conversion from solid-state to the volatile product can be described by the following reaction: ɑ
= ɑ
(4)
Conversion (ɑ), is assigned a form of weight loss data of decomposed sample and is defined as follows:
ɑ=
−
−
(5)
where, mi is the sample mass at the beginning, mf is the sample mass at the end of the reaction, and mɑ represents the mass of the sample at time t. T is the temperature, k(T) is the rate constant is expressed by Arrhenius equation.
=
/
(6)
Substituting the value of k in equation (4),
ɑ = . ɑ. /
(7)
4
The expression of function f(ɑ) and its derivative f’(ɑ) = -1 are used for explaining solid- state first order reaction; hence many authors define the mathematical function f(ɑ) to the following expression:
ɑ = 1 − ɑ
(8)
Then equation (7) becomes,
ɑ = . 1 − ɑ . /
(9)
Taking into account that the temperature is a function of time and that it is increasing at fixed heating rate, then β can be written as,
=
ɑ = ɑ
(10)
Then equation (9) becomes,
ɑ = . 1 − ɑ . /
(11)
Equation (11) represents the fraction of material consumed as per time. Integrating the equation (11) gives:
! = "
#
! −( = " exp ' * ! + )
(12)
where G(α) is the integral form of the conversion dependence function f(ɑ). This equation (12) has no explicit solution. Some interpolation formulas in terms of Doyle (1965), Agrawal (1987), Gorbatchev (1974), and Frank- Kameneshii (1955) approximations were used. 2.4 Model-free methods Model-free methods does not require assumption of any reaction model. Kinetic parameters are calculated from several curves at different heating rates on the same value of conversion. These methods are highly suggested by the Kinetics Committee of the International Confederation for Thermal Analysis and Calorimetry (ICTAC Kinetics Committee) (Vyazovkin et al., 2011). The main aim of using Model-free methods is their simplicity and avoidance of error related to the choice of kinetic model. The most popular representatives of isoconversional methods are Kissinger, Friedman (FR),
5
Kissinger- Akahira- Sunose (KAS), Flynn- Wall-Ozawa (FWO), and Vyazovkin (V). The model-free methods Kissinger, Kissinger- Akahira- Sunose (KAS), Flynn- WallOzawa (FWO) have been used in this study. 2.4.1 Kissinger Method Kissinger (1956) formulated a model-free nonisothermal method where activation energy is assumed to be constant at a given conversion. This method allows to calculate the activation energy from a plot of ln (β/T2m) vs. 1/Tm for different heating rates (β), Tm is the peak temperature of the DTG curve. The equation of Kissinger method is:
,- '
. 23 45 * = ,- ' * − 1 /0 4 3/0
(13)
Activation Energy is calculated from slope equal to−( ⁄). 2.4.2 Flynn- Wall- Ozawa method The FWO method (Flynn and Wall, 1966; Ozawa, 1965) is used to calculate the apparent activation energy (Eɑ) from a plot of ln β vs. 1/Tɑi, which depicts the linear relation with a given value of conversion at different heating rates. Using Doyle’s approximation (Doyle, 1965), the final form of FWO equation is:
,-.7 = ,- '
2ɑ 4ɑ 4ɑ * − 9. ::; − ;. <91 38ɑ 3/ɑ7
(14)
The subscripts i and ɑ denotes given value of heating rate and conversion respectively. The activation energy Eɑ is calculated from the slope -1.052 Eɑ/R. 2.4.3 Kissinger- Akahira- Sunose The KAS method (Kissinger, 1956; Akahira and Sunose, 1971) is one of the most widely used for biomass pyrolysis kinetic study in literature. By introducing Doyle’s approximation (Doyle, 1965), final equation is as follows:
,- =
. 2ɑ 3 4ɑ 1 > = ,- 4 8 − 3/ /ɑ7 ɑ ɑ 57
(15)
6
A The apparent activation energy can be calculated from a plot of ln ⁄ vs. 1/Tɑi for
a given value of conversion, ɑ, where the slope is = -Eɑ/R.
Pre-exponential factor (A) in Arrhenius equation was calculated by:
45 2 = .. 45. BCD ' * /3. /10 3. /0
(16)
The thermodynamic parameters like Enthalpy (∆H), Gibbs free energy (∆G) and the changes of Entropy (∆S) were calculated by following equations:
∆F = 45 − 3/
∆G = 45 + 3. /0 . IJ ' ∆N =
∆F − ∆G /0
(17)
KL . /0 * M. 2
(18) (19)
where, KB = Boltzmann constant (1.381*10 -23J/K); h= Plank constant (6.626*10-34 J.s); Tm = Peak temperature. 3. 3.1
Results and Discussions Characterization of raw material The Ultimate, Proximate, and Component analysis and HHV of castor residue are
shown in Table 1. The carbon, hydrogen, nitrogen and oxygen content of castor residue was 43.59 wt.%, 5.56 wt.%, 4.69 wt. %, and 46.16 wt.% respectively. The HHV of castor residue was 14.43 MJ/kg. Higher content of oxygen may impart negative effect on the HHV. The nitrogen content present in castor residue is high, which may produce NOx emissions during combustion (Damartzis et al., 2011). Biomass having low lignin content is generally preferred as lighter products are formed from it and obtained biooil can be used as a fuel (Ghetti et al., 1996). Castor residue has volatile content of ~ 7275% which is good for combustion and gasification process. The ash content of castor residue is 5.4% which is low as compared with literature (Dhyani and Bhaskar, 2017). High ash content may affect the burning rate and cause aggregation and fouling problems. The other disadvantages of high ash content are: it increases the processing costs, poor combustion, reduced energy conversion and disposal problems (Mckendry,
7
2002; Sait et al., 2012). Inorganic minerals (alkaline and alkaline – earth) present in ash affects the mechanism of biomass pyrolysis (Kan et al., 2016). “Table 1 here’’
3.2 Thermal degradation process Fig. 1(a). shows the weight loss curves obtained during the pyrolysis of castor residue under an inert atmosphere. The samples were heated from room temperature to 900˚C at heating rates of 5, 10, 15, 20, 30 and 40 ˚C/min constantly. Castor residue is a lignocellulosic biomass composed of cellulose, hemicellulose, and lignin. Each component has different decomposition temperature region (Yang et al., 2006). The variation in pyrolysis of biomass is due to its chemical composition of components present in it. The decomposition process of castor residue was done in three stages. In the first stage (1) release of weakly bonded water molecules and hydrolysis of some extractives was observed with a small hump at temperature up to 128˚C. This stage is known dehydration stage. (2) Active Pyrolysis involves the decomposition of hemicellulose, cellulose and small amount of lignin at temperature range of 160-520˚C. The first peak represents the decomposition of hemicellulose and second peak corresponds to the decomposition of cellulose. The decomposition of cellulosic part occurs in two ways: (i) Formation of CO, CO2 and carbonaceous by breakdown of bonds and polymers at low temperature; (ii) Integration of bonds at high temperature leads liquid formation (Çepelioǧullar and Pütün, 2013); (3) The decomposition of lignin was observed in passive pyrolysis at temperature range of 150-900˚C. Char is the major product produced during passive pyrolysis (Zabaniotou et al., 2008). “Figure 1(a) here’’ The information about the effect of heating rate is necessary as it affects the conversion, product distribution and gives an idea about the reactor to be used (Garcı, 2000). Fig. 1(b) shows the derivative thermal profiles of the decomposition of castor residue at different heating rates (5, 10, 15, 20, 30 and 40 °C/min). It was observed that the increase in heating rates shifts the peak temperature to higher value. The change in behaviour is due to poor heat transfer and change in the reaction mechanism. Lower heating rates were generally preferred as heating of biomass particles occurs constantly,
8
and it provides better heat transfer to the inner part of the biomass (Chutia et al., 2013). Increasing the heating rate releases more volatile materials and less residues were left after the pyrolysis. “Figure 1(b) here’’ 3.3 Kinetic Analysis The Kinetic study is an important parameter in the efficient design of thermochemical processes for the conversion of biomass. The kinetic parameters like activation energy and pre-exponential factor of castor residue were calculated using model-free methods. Fig. 1(c). shows the change of conversion with respect to temperature at different heating rates. Fig. S(1) shows Kissinger plot for the calculation of kinetic parameters. The activation energy, pre-exponential factor and correlation factor calculated using equation (13) were 192.809 kJ/mol, 5.34E+13 and 99.06 respectively. Isoconversional FWO and KAS linear model equations were used to calculate the apparent activation energy based on conversion. Fig. 2(a) and Fig. 2(b) shows FWO plot and KAS plot respectively. “Figure 1(c) here’’ “Figure 2(a) here’’ “Figure 2(b) here’’ The kinetic parameters calculated using equations (14), (15) and (16) are shown in Table 2. Conversion value of 0.2-0.8 is used as below 0.2 and above 0.8 the value of correlation factor is very low (Damartzis et al., 2011). Activation energy is defined as the minimum amount of energy required to start a reaction. It is difficult to start a reaction that requires high activation energy. Activation energy is also used to know the reactivity of a fuel (Gai et al., 2013). An increase in apparent activation energy was observed during the initial stages of pyrolysis. As the conversion increases, the apparent activation energy decreases. The change in activation energy with respect to conversion is shown in Fig. 3. An increase in activation energy from 0.2-0.5 shows the presence of endothermic reactions while the decrease in activation energy from 0.6-0.8 indicates the presence of exothermic reactions. This fluctuation in activation energy is due to the complex reaction schemes shows the involvement of parallel, complex and competitive
9
reactions under inert atmosphere (Ma et al., 2015). The variation in activation energy w.r.t. conversion is also due to percentage of components present in biomass and their interactions among themselves. The activation energies of cellulose, hemicellulose and lignin degradation are in the range of 145-285, 90-125 and 30-39 kJ/mol respectively (Vamvuka et al., 2003). It was observed that castor residue has more cellulose content (38.42 %) so it requires more activation energy for decomposition which was increased at ɑ= 0.4 to 0.5. The same was observed in the case of chestnut shells (Özsin and Pütün, 2017). Another study on Hazelnut husk (Ceylan and Topcu, 2014) also confirms the same where apparent activation energy calculated using FWO and KAS method is less as the residue has less cellulose content (34.5 %) compared to castor residue. The activation energy calculated from model-free methods were also found similar to the literature values which reveals that there was decomposition of biomass components i.e., cellulose, hemicellulose, and lignin (Balogun et al., 2014; Damartzis et al., 2011; Gai et al., 2013). The average activation energy calculated over whole conversion range using KAS and FWO method was 165.86 and 167.10 kJ/mol respectively. The difference in activation energies is due to approximations and calculations used to solve temperature integral of the model-free methods. The average activation energy of castor residue was less than from Para grass (Ahmad et al., 2017), rice husk and elephant grass (Braga et al., 2014). Lower E values of castor residues reflect that it may be used for cofiring with other biomasses having lower or higher E values. The above finding makes the castor residue suitable for thermal conversion of biomass to value-added products/bioenergy. “Figure 3 here’’ The pre-exponential value ranges from 108-1018 and 10 7-10 18 were determined using FWO and KAS methods respectively. Low pre-exponential factors generally (<109s-1) shows the surface reaction. When the reaction is not dependent on surface area, then the low value of pre-exponential factor shows the closed complex. Higher value of A indicates simple complex. The empirical first-order pre-exponential factor range may vary from 104 to 1018 s-1 (Turmanova et al., 2008). Variation in pre-exponential values with conversion is due to the complex composition of biomass sample and complex reactions take place during decomposition. Fig. S(2) and S(3) shows the compensation effects between the activation energy and pre-exponential factor at different heating
10
rates. It was observed that the value of pre-exponential factor increases with increase in heating rate which may be due to increase in collision intensity at high heating rate. The A values of castor residue were almost equal to Para grass (Ahmad et al., 2017) and higher than RPW, rice bran, rice straw and Chicken manure (Maia and de Morais, 2016; Xu and Chen, 2013). This behavior showed the complex nature of castor residue and the components present in biomass follows multi-step degradation reaction chemistry. 3.5 Thermodynamic Parameters Equations (17), (18), (19) were used to calculate thermodynamic parameters and corresponding results are shown in Table 2. Enthalpy is the thermodynamic property which represents the total heat content of a system. For pyrolysis, enthalpy means the total energy consumed by the biomass for its conversion to various products like oil, gas, and char (Daugaard and Brown, 2003). The change in enthalpy with respect to the conversion is also shown in Fig. 4. It was observed that the little change in the enthalpy and activation energy (~5-6 kJ/mol) at each conversion point is due to the energy difference between the activated complex and the reagent. Less energy difference boosts the formation of activated complex (Vlaev et al., 2007). The closeness of ∆H values vs. Eɑ values states that product formation may be done by providing an amount of 5 kJ/mol of additional energy (Mehmood et al., 2017). It was noticed that the enthalpy variation for castor residue was 162.15 and 160.91 kJ/mol using FWO and KAS respectively while for RPW (red pepper waste) (Maia and de Morais, 2016), Rice Bran, Rice Straw, Chicken Manure, Dairy Manure (Xu and Chen, 2013) and Para grass (Ahmad et al., 2017) was 23.37-142.21, 111.03,162.23, 170.29, 153.10 and 173.66 kJ/mol respectively. “Figure 4 here’’ Gibbs free energy is also known as Free Enthalpy means the total increase in energy of the system for the formation of the activated complex (Kim et al., 2010; Sheng et al., 2014; Turmanova et al., 2008). Fig. 5(a) and (b) represents the change of Gibbs free energy at different heating rates calculated by FWO and KAS method respectively. The ∆G value of castor residue was 150.62-154.33 and 150.59-154.65 kJ/mol calculated using FWO and KAS respectively. The change in Gibbs free energy for RPW(Maia and de Morais, 2016), Rice Bran, Rice Straw, Chicken Manure, Dairy
11
Manure (Xu and Chen, 2013) and Para grass (Ahmad et al., 2017) were 71.77-207.03, 167.17, 164.59, 175.29, 176.60 and 169-173 (KAS) 168-172 (FWO) kJ/mol respectively. The average ∆G value for castor residue (152.00 kJ/mole) was higher than the average ∆G value of RPW (139.40 kJ/mole). “Figure 5(a) here’’ “Figure 5(b) here’’ Fig. 6 (a) and (b) represents the positive and negative values of change of entropy calculated by FWO and KAS method respectively. It was observed that the castor residue has both negative (-108.02 J/mol) and positive values (102.82 J/mol). Negative values of ∆S shows the degree of disorder of products produced through bond dissociations were lower than initial reactants. The low ∆S means the material just passes through some physical and chemical changes, bringing it to state near to its thermodynamic equilibrium. In this state, material shows little reactivity and takes more time to form activated complex. On the other hand, high ∆S means reactivity will be high and less time is consumed to form activated complex. “Figure 6(a) here’’ “Figure 6(b) here’’ “Table 2 here’’ Conclusions Castor residue has high volatile content and high heating value (14.43 MJ/kg). Sulphur content was not detected in castor residue. There is a little variation in the apparent activation energy (Eɑ) calculated by FWO (167.10 kJ/mole) and KAS (165.86 kJ/mole) methods. Pre-exponential factor (A) results varies from 10 8-1018 and 107-1018 for FWO and KAS methods respectively. The average ∆G value of castor residue (152 kJ/mole) shows more available energy to be considered as a raw material for bioenergy production. It is observed that the castor residue has significant potential to be used as a feedstock for bioenergy/biofuels production. Acknowledgement
12
The authors gratefully acknowledge the Director, CSIR-Indian Institute of Petroleum (IIP) and Director, National Institute of Technology, Jalandhar for constant endorse in all ways. RK thanks the TPA group of Bio-Fuels Division at CSIR-Indian Institute of Petroleum (IIP) for providing analytical support. RK acknowledges MHRD, Govt of India for rendering fellowship and NIT Jalandhar for their financial support for carrying out this work. References [1] Agrawal, R.K., Sivasubramanian, M.S., 1987. Integral approximations for nonisothermal kinetics. AIChE J. 33, 1212–1214. doi:10.1002/aic.690330716 [2] Ahmad, M.S., Mehmood, M.A., Al Ayed, O.S., Ye, G., Luo, H., Ibrahim, M., Rashid, U., Arbi Nehdi, I., Qadir, G., 2017. Kinetic analyses and pyrolytic behavior of Para grass (Urochloa mutica) for its bioenergy potential. Bioresour. Technol. 224, 708–713. doi:10.1016/j.biortech.2016.10.090 [3] Akahira, T., Sunose, T., 1971. Method of determining activation deterioration constant of electrical insulating materials. Res. Rep. Chiba Inst. Technol. (Sci. Technol.) 16, 22–31. [4] Aldobouni, I.A., Fadhil, A.B., Saied, I.K., 2015. Conversion of de-oiled castor seed cake into bio-oil and carbon adsorbents. Energ. Source Part A 37, 26172624. doi:10.1080/15567036.2012.733482 [5] Balogun, A.O., Lasode, O.A., McDonald, A.G., 2014. Devolatilisation kinetics and pyrolytic analyses of Tectona grandis (teak). Bioresour. Technol. 156, 57– 62. doi:10.1016/j.biortech.2014.01.007 [6] Bateni, H., Karimi, K., Zamani, A., Benakashani, F., 2014. Castor plant for biodiesel, biogas, and ethanol production with a biorefinery processing perspective. Appl. Energy 136, 14–22. doi:10.1016/j.apenergy.2014.09.005 [7] Braga, R.M., Melo, D.M., Aquino, F.M., Freitas, J.C., Melo, M.A., Barros, J.M., Fontes, M.S., 2014. Characterization and comparative study of pyrolysis kinetics of the rice husk and the elephant grass. J. Therm. Anal. Calorim. 115, 1915-1920. [8] Çepelioǧullar, Ö., Pütün, A.E., 2013. Thermal and kinetic behaviors of biomass and plastic wastes in co-pyrolysis. Energy Convers. Manag. 75, 263–270.
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Figure Captions Fig. 1(a) Thermogravimetric curves (b) Derivative Thermogravimetric curves (c) Extent of conversion curves for the devolatilization process of castor residue at different heating rates. Fig. 2. Linear plot for determining activation energy of castor residue calculated by (a) FWO (b) KAS method. Fig. 3. Activation Energy as a function of conversion. Fig. 4. Change in Enthalpy as a function of conversion. Fig. 5. Change in Gibbs Energy as a function of conversion calculated by (a) FWO (b) KAS method. Fig.6. Change in Entropy as a function of conversion calculated by (a) FWO (b) KAS method.
18
Table 1 Elemental, Proximate, Component analysis of castor residue Elements
wt.%
wt.%
43.59
Proximate Analysis Moisture
Carbon Hydrogen
5.56
Ash
Nitrogen
4.69
Sulphur
ND
Oxygen*
46.16
Volatile 74.30 Matter Fixed 9.16 Carbon * by difference ND: Not Detected
HHV(MJ/kg) 14.43
11.14
Component Analysis Extractives
wt.% 16.40
5.40
Cellulose
38.42
Hemicellulose
22.40
Lignin
20.20
19
Table 2 Conversion points, Kinetics and corresponding thermodynamic parameters Conversion Activation Preexponential R2 ∆H* ∆G* ∆S* Points (α) Energy factor* (kJ/mol) (kJ/mol) (kJ/mol) (kJ/mol) (s-1) FWO method 0.2 127.81 7.28E+10 0.99 122.86 153.20 -51.01 0.3 143.57 1.98E+12 0.99 138.62 152.63 -23.54 0.4 214.33 4.85E+18 0.99 209.38 150.64 98.74 0.5 215.56 6.26E+18 0.99 210.61 150.62 100.86 0.6 206.24 9.09E+17 0.99 201.29 150.84 84.82 0.7 160.32 6.55E+13 0.99 155.37 152.08 5.53 0.8 101.87 3.06E+08 0.99 96.92 154.33 -96.51 Average 167.10 162.15 152.05 KAS method 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Average
126.17 142.14 216.02 216.70 206.78 157.83 95.35 165.85
5.17E+10 1.47E+12 6.88E+18 7.92E+18 1.02E+18 3.89E+13 7.68E+07
0.99 0.99 0.98 0.99 0.99 0.99 0.98
121.22 137.19 211.07 211.75 201.83 152.88 90.40 160.91
153.27 152.68 150.61 150.59 150.82 152.16 154.65 152.11
-53.87 -26.03 101.65 102.82 85.76 1.20 -108.01
*results calculated at 10°C/min.
20
Fig.1(a) 100
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
90 80
Weight loss (%)
70 60 50 40 30 20 10
1(a) 0 200
400
600
800
Temperature (°C)
Fig.1(b)
21
0.000 -0.002 -0.004
DTG (mg/sec)
-0.006 -0.008
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
-0.010 -0.012 -0.014 -0.016 -0.018
1(b) -0.020 200
400
600
800
Temperature (°C)
Fig.1(c)
22
1.0
1(c)
Conversion(α)
0.8
0.6
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
0.4
0.2
0.0 200
400
600
800
Temperature (°C)
Fig.2(a)
23
4.0
0.2 0.3 0.4 0.5 0.6 0.7 0.8
3.5
ln(β)
3.0
2.5
2.0
1.5
2(a) 1.2
1.4
1.6
1.8
2.0
2.2
-1
1/T (K )
Fig.2(b) -8.5
0.2 0.3 0.4 0.5 0.6 0.7 0.8
-9.0
2
ln(β/T )
-9.5
-10.0
-10.5
-11.0
-11.5
2(b) 1.4
1.6
1.8
2.0
2.2
-1
1/T (K )
Fig.3
24
250
Activation Energy (kJ/mol)
3
KAS FWO
200
150
100
50 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Conversion (α)
Fig.4
25
250
4
FWO KAS
200
∆H(kJ/mol)
150
100
50
0 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Conversion (α)
Fig.5(a)
26
5(a)
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
∆G(kJ/mol)
155
153
151
149 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Conversion(α)
Fig.5(b).
157
5(b)
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
156 155
∆G(kJ/mole)
154 153 152 151 150 149 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Conversion(α)
27
Fig.6(a). 100
6(a)
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
∆S(J/mole)
50
0 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Conversion (α) -50
-100
Fig.6(b).
100
5°C/min 10°C/min 15°C/min 20°C/min 30°C/min 40°C/min
5(b)
∆S(J/mole)
50
0 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Conversion(α) -50
-100
28
Highlights • • • •
The first study on pyrolysis kinetics of castor residue (leaves and stems). The thermal conversion of castor residue was characterized by TG-DTG. The thermodynamic parameters (∆H, ∆G, ∆S) were calculated. Castor residue has potential to be used as biofuel or bioenergy production.
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