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Pyrolysis of brewer’s spent grain: Kinetic study and products identification
Industrial Crops & Products 121 (2018) 388–395
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Industrial Crops & Products journal homepage: www.elsevier.com/locate/indcrop
Pyrolysis of brewer’s spent grain: Kinetic study and products identification a
b
c
a
Lidja D.M.S. Borel , Taísa S. Lira , Jânio A. Ribeiro , Carlos H. Ataíde , Marcos A.S. Barrozo a b c
a,⁎
T
Federal University of Uberlândia, School of Chemical Engineering, Brazil Federal University of Espírito Santo, Dep. Eng. Technol., Brazil Federal University of Mato Grosso, Institute of Engineering, Brazil
A R T I C LE I N FO
A B S T R A C T
Keywords: Brewer’s spent grain Thermogravimetric analysis Biomass Pyrolysis
In this study, the physicochemical properties, the thermal degradation behavior and the products generated from pyrolysis of brewer's spent grain (BSG) were investigated to evaluate the potential of this agro-industrial residue for bio-oil production via pyrolysis. Thermogravimetric analyses were performed in a nitrogen atmosphere. The kinetic parameters were estimated by isoconversional methods and by independent parallel reactions model (IPR). The results showed that the BSG has a good potential for bio-oil production owing to its high volatile matter content and the high heating value. The kinetic behavior was successfully modeled by the IPR model. High added-value compounds were identified from analytical pyrolysis, which indicates that BSG can be a source of important raw materials for the chemical industry.
1. Introduction The use of agro-industrial waste for energy production is an interesting possibility in the context of global efforts to maximize value addition of these residues, while reducing negative impact of industrial processes (Varma and Mondal, 2017). Brewer’s spent grain (BSG) is a major by-product generated from the brewing industry; it represents 85% of the total waste generated in this industry; 20 kg per 100 L of beer produced (Mahmood et al., 2013, Mussatto, 2014; Buffington, 2014; Ohra-Aho et al., 2016). This material comprises barley grain husks that are obtained as solid residue after the production of wort (Carvalho et al., 2015b). Approximately 39 million tons of beer are produced annually, with China, USA, Brazil, Russia and Germany being the largest producers (Lynch et al., 2016). The scientific community has made various proposals for BSG reuse. As a source of health-promoting nutrients, it has been evaluated by Reis et al. (2014) through arabinoxylans derived from BSG and by Guo et al. (2014) through BSG-enriched biscuits. These authors reported that the products obtained provide protection for cardiovascular diseases, cancer and other degenerative diseases. As adsorbent material, Vanreppelen et al. (2014) studied activated carbon derived from BSG for phenol absorption in the water treatment; Kordialik-Bogacka (2014) studied BSG as support for Saccharomyces pastorianus cells for the removal of lead ions. Ravindran et al. (2018) performed enzymatic hydrolysis of BSG to produce value added products. Besides, there are still studies of BSG use as additive in the production of building bricks; production of ethanol, lactic acid, enzymes and xylitol; among others
⁎
Corresponding author. E-mail addresses: [email protected], [email protected] (M.A.S. Barrozo).
https://doi.org/10.1016/j.indcrop.2018.05.051 Received 30 January 2018; Received in revised form 30 April 2018; Accepted 20 May 2018 0926-6690/ © 2018 Elsevier B.V. All rights reserved.
(Aliyu and Bala, 2011). Another alternative of BSG use, with possibly higher profitability, is the thermochemical conversion of this waste into biofuel or valuable chemical commodities by pyrolysis process. Mahmood et al. (2013) studied the intermediate pyrolysis and catalytic steam reforming (Ni/ Al2O3) of Brewers spent grain using a bench scale batch fixed bed reactor at 450 °C. These authors reported an increase of gaseous yield, mainly H2 and CO, with heating value between 10.8–25.2 MJ/m3. Poerschmann et al. (2014) proposed the application hydrothermal carbonization of BSG to produce biocoal. BSG is a lignocellulosic fibrous material, which composition is influenced by the species of barley, the malting process, proportion and types of adjuncts used, as well as the processes of milling, mashing and clarification. These variables can also influence the kinetic pyrolysis parameters (Aliyu and Bala, 2011; Xiros and Christakopoulos, 2012). To ensure the viability of the reuse of BSG by a thermochemical conversion process, it is imperative to consider aspects of the raw material, process and product (Kim and Agblevor, 2014; Sohni et al., 2018). Therefore, the BSG characterization is essential for predicting its behavior upon conversion to fuel or chemicals, as well as for selecting the most appropriate pyrolysis technique. Moreover, knowing the kinetic parameters is essential for proper description of the thermal conversion processes, in order to improve the design of reactors. For this, the thermogravimetric data (TGA) can be treated through different approaches (Domínguez et al., 2008; Gao et al., 2013; Odetoye et al., 2013; Titiloye et al., 2013). The isoconversional methods are very useful and interesting tool, since they provide consistent results for
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hour in a moisture-free sample was performed to estimate the extractives content of BSG. The lignin content was determined according to modified TAPPI standard T222 om-22 (2002c). The extractive and moisture free sample was hydrolyzed using sulfuric acid in two steps: first at 283–288 K and 72% (w/w) for 24 h, and after under heating and reflux for 4 h with 4% (w/w). Hemicellulose and α-cellulose constitute the holocellulose content, which was measured using glacial acetic acid and sodium hypochlorite at 348 ± 2 K. The α-cellulose was determined by treating the holocellulose sample with potassium hydroxide solutions of 5 and 24% (w/ w). The hemicellulose content was calculated subtracting the α-cellulose content from the holocellulose (Andrade et al., 2016).
activation energy estimation (Lira et al., 2010; Santos et al., 2010; Alvarenga et al., 2012; Santos et al., 2012c; Lopes et al., 2016). However, the independent parallel reaction kinetic model (IPR model) is a more robust technique to describe the kinetic behavior. This model provides detailed kinetic information for each subcomponent of the biomass (Santos et al., 2012b; Carvalho et al., 2015b). The composition of the bio-oil can be obtained via analytical pyrolysis and thus to evaluate the feasibility of its application (Greenhalf et al., 2012; Carvalho et al., 2015a). The influence of different operating conditions can be investigated by this technique and thus develop strategies to increase the bio-oil yield and the quality of the product obtained, by favoring the formation of more attractive compounds (Lu et al., 2011; Murillo et al., 2014; Santana et al., 2018). Some works of the literature have studied the thermochemical conversion of waste of the brewing industry. However, specifically on pyrolysis, there are still challenges to be overcome to make the process be cost effective. Thus, additional investigations are needed to a greater understanding on some important aspects of the BSG pyrolysis, such as the relationship between the pyrolysis products and the operating conditions, a reliable kinetic prediction and a complete characterization of this waste. Thus, this paper presents a complete thermochemical characterization of brewer’s spent grain composed by proximate and ultimate analysis, compositional analysis, X-ray fluorescence spectrometry analysis, infrared spectra, analytical pyrolysis and thermogravimetric analyses. The effects of the heating rate and the reaction temperature on the degradation behavior and on the pyrolytic products obtained were evaluated. This information may be an important contribution for the further studies in the area. Furthermore, the kinetic parameters of the devolatilization were determined through two approaches: by isoconversional methods and by the independent parallel reactions (IPR) model using thermogravimetric analyses data.
2.2.4. X-ray fluorescence spectrometry analysis The inorganic matter in BSG was measured by X-ray fluorescence spectrometry in a pre-calibrated equipment (S8 Tiger, Bruker). The samples were prepared in the form of pressed pellets of 34 mm diameter, using 4.5 g of biomass ( < 170 mesh). Semi-quantitative analysis was performed using the Quant-Express calibration package. The analyses were performed in triplicate and the mean results were reported. 2.2.5. Fourier transform infrared spectroscopy (FTIR) The FTIR spectra of BSG were obtained using a spectrophotometer (Shimadzu, IR Prestige-21). The analyses were performed with pellets of BSG and KBr (1:100 w/w) in the range of 4000–400 cm−1 with a resolution of 4 cm−1and a total of 32 scans. 2.2.6. Calorific value The higher heating value (HHV) of BSG was quantified using an oxygen bomb calorimeter (IKAC2000). The measurements were performed in triplicate according to ASTM D2015.
2. Materials and methods 2.3. Thermogravimetric analysis (TGA) 2.1. Materials A thermogravimetric analyzer (Shimadzu, DTG-60H) was used for monitoring the mass loss (TG) and the differential weight loss (DTG) profiles. The thermogravimetric tests of the samples (8 mg) were performed from 298 to 1173 K at heating rates of 5, 10, 20, 30, 40 and 50 K/min, using nitrogen as purge gas at a flow rate of 50 mL/min.
The BSG used in this study was obtained from a brewing process that provided 100% malted barley (without addition of other cereal adjuncts). The material was supplied by a microbrewery of Uberlândia, Minas Gerais State, Brazil, and it was classified by sieving after drying (oven method at 378 ± 3 K for 24 h). The average sieve diameter of dried BSG was 3.23 mm. The samples were ground so that they passed through a 100 mesh screen to perform the chemical characterization.
2.3.1. Kinetic study Isoconversional methods and the independent parallel reactions (IPR) model were used to estimate the kinetic parameters of the devolatilization of BSG.
2.2. Characterization of the BSG
2.3.1.1. Isoconversional methods. The rate of reaction can be expressed from product of two independent terms, according to the following equation:
2.2.1. Ultimate analysis Chemical composition of BSG in terms of carbon (C), hydrogen (H), nitrogen (N), oxygen (O) and sulfur (S) was determined using a Perkin Elmer 2400 CHNS/O elemental analyzer, operating at 1198 K in an atmosphere of pure oxygen. The oxygen content was calculated by difference also considering the ash content according to Eq. (1): %O = 100 − %C − %H − %S − %Ash
dX = K (T )⋅f (X ) dt
(2)
Pyrolytic conversion was calculated according to Eq. (3): (1)
X= 2.2.2. Proximate analysis The moisture, volatiles and ash contents were measured according to the ASTM standard (E1756-01, E872-82 and E1755-01). The fixed carbon was determined by difference. The analyses were performed in triplicate and the mean results were reported.
m o − mt mo − m∞
(3)
where mo is the initial mass of sample; m∞ is the final mass and mt is an instantaneous mass. The thermal dependence term K(T) can be described by an Arrhenius relationship. Considering the non-isothermal conditions, in which the heating rate of the process is β = dT/dt, Eq. (2) becomes Eq. (4):
2.2.3. Compositional analysis The extractives, hemicellulose, cellulose and lignin contents were determined according to the procedure proposed by Andrade et al. (2016). Soxhlet extraction with acetone as solvent using 6 refluxes per
dX k 0 -Ea = eRT dT f(X) β The integral form of Eq. (3) results in: 389
(4)
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Table 1 Physicochemical properties of BSG. Ultimate analysis (% wt) Proximate analysis (% wt) Chemical composition (% wt) HHVa (MJ/kg) a
C 47.2 ± 1.3 Moisture 3.97 ± 0.00 Extractives 5.26 ± 0.06 21.6 ± 2.8
H 7.2 ± 0.1 Volatile matter 83.30 ± 0.29 Lignin 29.37 ± 4.03
N 3.6 ± 0.4 Ash 3.22 ± 0.03 Cellulose 15.14 ± 0.03
S 1.1 ± 0.1 Fixed carbon 9.51 ± 0.31 Hemicellulose 50.23 ± 0.03
O 37.6 ± 1.7
HHV is the higher heating value.
Table 2 Element and oxides content in the BSG samples (% w/w ± standard deviation). Element
Composition contents (wt.%)
Oxides
Composition contents (wt.%)
P Si K Ca Mg Fe S Zn Mn Cu Cl Br
0.75 0.74 0.56 0.39 0.15 0.14 0.76 0.07 0.02 0.02 0.12 0.02
P2O5 SiO2 K2O CaO MgO Fe2O3 SO3 ZnO MnO CuO – –
1.74 1.96 0.68 0.98 0.43 0.19 1.91 0.09 0.08 0.02
∫0
g(X)=
X
± ± ± ± ± ± ± ± ± ± ± ±
0.02 0.01 0.01 0.01 0.01 0.01 0.02 0.00 0.00 0.00 0.01 0.00
dX k 0 = f(X) β
∫T
T
-Ea
eRT dT=
0
± ± ± ± ± ± ± ± ± ±
0.01 0.64 0.00 0.74 0.33 0.01 0.05 0.01 0.10 0.00
k 0Ea Ea ⎞ p⎛ βR ⎝ RT ⎠
(5)
Fig. 1. FTIR spectra of BSG.
where ko represents the pre-exponential factor, R represents the ideal gas constant, Ea represents the activation energy and T represents the absolute temperature of the sample. Eq. (5) can be solved by numerical methods or approximations. In this study we used the methods of Ozawa and Kissinger according to Eq. (6) and Eq. (7), respectively. These methods follow the same physicochemical and mathematical assumptions and differ according to approximation for the polynomial p(E/RT) in Eq. (5).
ln β = −1.0518[Ea RT ] + [ln(k 0 Ea R) − ln g (X ) − 5.3305]
(6)
β E k R ln ⎛⎜ 2 ⎟⎞ = −⎛ a ⎞ + ⎡ln ⎛ 0 ⎞ − ln g (x ) ⎤ ⎢ ⎥ RT T ⎦ ⎝ max ⎠ ⎣ ⎝ T ⎠ ⎝ max ⎠
(7)
⎜
dmcalc = −(mo − m) dt
2.3.1.2. Independent parallel reactions (IPR) model. The Independent Parallel Reactions (IPR) approach considers that each subcomponent is degraded individually, thus ensuring a potentially simultaneous decomposition. Thus, the rate of conversion for each component is:
N
O. F .DTG =
∑ j=1
dXi dt
(10)
obs
⎛ ⎛ dm ⎞ ⎜ dt ⎠j ⎝⎝
calc 2
dm ⎞ ⎞ −⎛ ⎟ ⎝ dt ⎠ j ⎠
(11)
where subscript j refers to the data points used, N represents the number of experimental data of each run and (dm/dt)obs is the experimentally observed value and (dm/dt)calc is the value calculated with a given set of parameters (Fernandes et al., 2009).
(8)
where Xi, k0i, Eai, and ni represent, respectively, the conversion, preexponential factor, activation energy, and apparent order of reaction of each component. The global reaction rate is the linear combination of the rates of the partial reactions, considering the mass fraction of each component (ci):
2.4. Analytical pyrolysis The fast pyrolysis of BSG was performed in a CDS Pyroprobe® 5200 pyrolyzer at 723, 823, 923 and 1023 K, with heating rate of 20 K/ms. Helium (99.999 purity) was used as inert gas. The volatile products were analyzed by gas chromatography and mass spectrometry (Shimadzu GC/MS-QP2010 Plus). The gas used in the analyses was helium (99.999 purity) at a split ratio of 100:1, using a Rtx-1701 GC column. Data processing was performed using the NIST05 library (Cardoso and Ataide, 2013).
nc
dX dX = − ∑ ci i dt dt i=1
i=1
ci
First-order reactions kinetics were assumed for extractives, cellulose and hemicellulose. The pyrolysis of lignin cannot be modeled by firstorder kinetics. Various studies in the literature report that the pyrolysis of lignin is better described by third-order reaction kinetics (Santos et al., 2012a; Alvarenga et al., 2016). An algorithm based on differential evolution method was implemented in Mathlab R2013a to estimate the kinetic parameters (Lobato et al., 2008, Arruda et al., 2009; Santos et al., 2012b). The objective function to be minimized is the sum of the squared residuals according to the following equation:
⎟
dXi E = koi exp ⎛− ai ⎞ (1 − Xi )ni dt ⎝ RT ⎠
nc
∑
(9)
where nc represents the number total of components. Four components were considered for this biomass (BSG): extractives, cellulose, hemicellulose, and lignin. Thus, the mass loss with time is calculated using the following relationship: 390
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Fig. 3. Linear regression using (a) Ozawa (b) Kissinger methods for pyrolysis reaction of BSG.
Fig. 2. Experimental (a) TG and (b) DTG curves of BSG as function of reaction temperature at the different heating rates.
The inorganic matter in BSG was determined by X-ray fluorescence spectrometry analysis and the results are presented in Table 2. It can be seen, that minerals present in greater quantities in this residue are: phosphorus, silicon, potassium and calcium. The results of FTIR spectroscopy for the BSG are presented in Fig. 1. It was possible to identify the functional groups, and from the intensity value of the absorption band, the most abundant chemical bonds could also be identified, such as: hydroxyl in water, alcohol and phenols (3428 cm−1), CeH group in asymmetric and symmetric aliphatic (2930–2860 cm−1), CeN or a CeC triple bond (2400–2200 cm−1), carbonyl in aldehydes or unconjugated ketone (1732 cm−1), OeH from the water molecules absorbed and conjugated C]O with a benzene ring in lignin or cellulose (1647 cm−1), C]C in aromatics related to the lignin (1533 cm−1), C−H bending in aliphatic compounds or CeH asymmetric deformation of aromatic skeletal in lignin (1454 cm−1), CeH vibration in cellulose (1251 cm−1), CeO stretching and hydroxyl bending in primary, secondary and tertiary alcohols, esters and ethers (950–1200 cm−1), CeH deformation in cellulose (856 cm−1), AreOH functional group in phenols (706 cm−1) and CeOeC group in ethers (480 cm−1) (Pandey and Pitman, 2003; Popescu et al., 2007). The results were consistent with reported data in literature for other similar biomasses (Andrade et al., 2016; Ma et al., 2016).
3. Results and discussion 3.1. Characterization of BSG Table 1 shows the results of the measurements of the physicochemical properties of the BSG. The results of chemical analysis of BSG are consistent with values reported in the literature for this residue of the brewing industry (Celaya et al., 2015; Mahmood et al., 2013; Vanreppelen et al., 2014). The BSG showed high H/C ratio (0.15), and an O/C ratio of 0.80. Thus, according to the Van Krevelen diagram (H/C versus O/C), BSG has good thermal properties compared with other waste biomass materials, such as: eucalyptus, H/C = 0.12 and O/ C = 1.26 (Chen et al., 2015); soybean hulls, H/C = 0.15 and O/ C = 1.35 (Oliveira et al., 2015) and rice hulls H/C = 0.13 and O/ C = 0.94 (Alvarez et al., 2014). This agrees with the high heating value found, which was higher than hazelnut husk (18.5 MJ/kg) (Ceylan and Topçu, 2014) and pine wood (17.34 MJ/kg) (Mishra et al., 2015). The BSG also has high volatile content (83.30%), similar to eucalyptus residue (Amutio et al., 2015) and cassava stem (Pattiya, 2011). Furthermore, BSG showed high hemicellulose content compared to other major subcomponents, which offers significant potential for interesting pyrolysis products, as well as to produce more gas and less tar. 391
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respectively. The lignin degradation it is highlighted by a shoulder at higher temperatures. At temperatures above 850 K passive pyrolysis or carbonization occurs (Stage 3), and the weight loss occurred smoothly (Chen et al., 2015; Ma et al., 2016; Rueda-Ordóñez and Tannous, 2015).
Table 3 Mass fraction and kinetic parameters of IPR model for the pyrolysis of BSG. β [K/ min]
Component
Mass fraction
k0 [s−1]
Ea [kJ/ mol]
Deviationa (%)
5
Extractives Hemicellulose Cellulose Lignin Extractives Hemicellulose Cellulose Lignin Extractives Hemicellulose Cellulose Lignin Extractives Hemicellulose Cellulose Lignin Extractives Hemicellulose Cellulose Lignin Extractives Hemicellulose Cellulose Lignin
0.0575 0.506 0.136 0.284 0.0575 0.508 0.136 0.320 0.0575 0.500 0.136 0.314 0.0575 0.504 0.136 0.317 0.0575 0.488 0.136 0.323 0.0575 0.506 0.136 0.323
1.98∙1019 1.08∙104 6.90∙1016 4.75∙106 3.86∙1018 4.72∙104 2.25∙1017 1.20∙107 8.41∙1017 2.55∙105 1.22∙1018 2.61∙106 1.12∙1018 3.18∙105 8.86∙1017 3.48∙106 8.54∙1016 3.19∙106 1.52∙1019 2.65∙105 1.37∙1017 2.04∙106 9.00∙1018 4.27∙105
196.14 71.01 224.13 117.93 191.34 75.88 230.90 120.55 186.37 81.30 238.49 109.87 187.68 81.01 236.04 109.78 178.25 90.95 251.15 94.07 179.41 87.90 246.56 95.25
3.93
10
20
30
40
50
a
3.2.1. Isoconversional approach Fig. 3 shows the linear regressions for the Ozawa (a) and Kissinger (b) methods. The results of Ozawa's method show that the average value of the activation energy in the conversion range of 0.1–0.2 (corresponding to the range 458–553 K) was 104.7 kJ/mol. In this temperature range begins the depolymerization of the biomass subcomponents, mainly hemicellulose, whose degradation requires low energy amount. In the range of 0.3–0.6 (equivalent to 511–636 K), the activation energy increases from 131 to 164 kJ/mol. This increase (25%) is because in this range begins cellulose degradation, which has a more complex structure and, therefore, requires more energy for its degradation. In the range of 0.6–0.8 (595–692 K), the maximum activation energy is observed (181.6 kJ/mol), which is associated with decomposition of cellulose, and first step of lignin decomposition. For conversion higher than 0.8 (T > 692 K) the degradation was almost complete and the activation energy decreases to 139.7 kJ/mol, which corresponds to the degradation of residual lignin and the formation of char (Rueda-Ordóñez and Tannous, 2015; Collazzo et al., 2017). The average value of the activation energy obtained by Ozawa’s method was Ea = 147.7 kJ/mol (R2 = 0.9670). The Kissinger method leads to a value of Ea = 140.4 kJ/mol (R2 = 0.9964). Therefore, the values of activation energy obtained from these two isoconversional methods are in agreement.
3.43
3.53
3.45
3.73
3.61
Deviation was defined asFITDTG (%) = 100 (O. F .DTG ) N max( (dm dt )obs j ).
3.2. Kinetic study
3.2.2. Independent parallel reactions (IPR) model The IPR model was used in this study to describe the pyrolysis of BSG, assuming four parallel reactions in which, extractives, hemicellulose and cellulose are described as first order reactions and lignin as a third-order reaction. The results of the estimated kinetic parameters for the pyrolysis of BSG using IPR model are shown in Table 3. The literature shows that for lignocellulosic biomass the activation energy varies from 80 to 150 kJ/ mol for the hemicellulose, 80–286 kJ/mol for cellulose and from 10 to 180 kJ/mol for lignin (Alvarenga et al., 2016; Xavier et al., 2016). Thus, the results obtained for each component in this study (Table 3) are
The differential thermogravimetric (DTG) curves are shown in Fig. 2. It can be seen that the DTG profiles of BSG had a similar behavior at heating range from 5 to 50 K/min. Thermal degradation of BSG can be divided into three stages. In stage 1, from 301 to 428 K, the moisture and lighter volatiles are removed without chemical reaction. In the stage 2, called active pyrolysis or devolatilization, the main components of the biomass are degraded. Initially, the thermal decomposition of extractives occurs being characterized by a “shoulder” in DTG curve. Then two peaks in the DTG curve indicate the degradation of hemicellulose and cellulose,
Fig. 4. DTG curves − experimental and simulated (by IPR model) for the heating rate of 30 K/min. 392
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estimate the mass fractions of each pseudo-components of this residue of the brewing industry. 3.3. Analytical pyrolysis Analytical pyrolysis was used to verify the potential of BSG as a source of biomass for the biofuel production. The main products present in the vapor produced by the micropyrolyzer were identified. The pyrolytic vapors are complex mixtures of organic compounds whose distribution can be affected by pyrolysis conditions. The identified compounds were classified in groups of oxygenated, heteroaromatic, hydrocarbon, nitrogenated compounds and others (amines, amides, etc) detected in minor amounts. Fig. 5 shows the influence of temperature on the presence of the group of compounds in the pyrolytic vapors. Among the identified products there is a predominance of holocellulose-derived compounds such as 2-propanone, acetic acid and furfural over lignin-derived compounds such as phenolic derivatives and benzene. There was a reduction in the amount of oxygen compounds in the vapors composition while the number of hydrocarbons increased with increasing temperature. This may be related to the fact that the deoxygenation is favored during decomposition at higher temperatures (Andrade et al., 2018). Table 4 shows the main compounds identified from the fast pyrolysis of BSG at 723, 823, 923 and 1023 K. The major compounds identified in the pyrolysis of BSG, at the temperature range used in this work were: 1-methoxy-2-propyl acetate, acetic acid, acetic anhydride, furfural and toluene. The 1-methoxy-2propyl acetate is used in the production of paints, coatings, cleaners, electronics manufacturing, silk-screen printing inks and metal finishers. Acetic acid is a carboxylic acid used as a raw material for the production of ethyl vinyl which is used to produce polyethylene terephthalate (PET), among others (Smets et al., 2014; Carvalho et al., 2015b). The acetic anhydride is applied in the production of cellulose acetate, explosives and aspirin (García et al., 2016). The furfural is also an
Fig. 5. Product distribution from pyrolysis of BSG at different reaction temperatures.
consistent with reported data in literature for lignocellulosic biomass materials. Fig. 4 presents the experimental and simulated (by model IPR) DTG curves for rate of 30 K/min, as example. The other heating rates had the same behavior. It can be seen that the curve simulated by the model IPR is in a good agreement with the experimental curve, with a deviation lower than 3.93%. Thus confirming the good quality of the prediction of the pyrolysis kinetic behavior of the BSG by the IPR model. It is also worth noting that the mass fractions estimated by the model IPR (Table 3) are close to the values obtained experimentally (Table 1). The deviations were lower than 10% and they are within the ranges described in the literature for this material, which are: extractives, 4.7–5.8; hemicellulose, 23.41–48.78; cellulose, 12.29–24.68 and lignin, 7.12–27.8 (Vanreppelen et al., 2014; Mahmood et al., 2013). This result shows that the IPR model was also adequate to
Table 4 Main compounds identified in analytical pyrolysis of BSG at different temperatures. RTa (min)
5.7 6.4 7.1 8.5 9.7 11.2 11.5 16.3 17.6 18.4 19.3 20.6 21.7 22.2 23.7 24.2 25.3 26.9 28.1 28.7 29.1 30.5 .30.8 31.4 32.5 36.4 45.3 a
Name
Acetic anhydride 2-methyl-Furan 2,3-Butanedione 3-methyl-Butanal, Acetic acid 1-hydroxy-2-Propanone Toluene Pyrrole 3,3′-oxybis-Propanenitrile 1-Methoxy-2-propyl acetate Furfural 1-Decene 2-Furanmethanol 1-(acetyloxy)-2-Propanone Limonene 2-Cyclopentene-1,4-dione 6-Oxa-bicyclo[3,1,0]hexan-3-one 5-methyl-2-Furancarboxaldehyde Butyrolactone 2(5H)-Furanone Hexanoic acid 2-Butoxyethyl acetate Benzeneacetaldehyde 1-Dodecene Phenol Dodecanal 2-Methoxy-4-vinylphenol
Formula
MW
C4H6O3 C5H6O C4H6O2 C5H10O C2H4O2 C3H6O2 C7H8 C4H5N C6H8N2O C6H12O3 C5H4O2 C10H20 C5H6O2 C5H8O3 C10H16 C5H4O2 C5H6O2 C6H6O2 C4H6O2 C4H4O2 C6H12O2 C8H16O3 C9H10O C12H24 C6H6O C12H24O C9H10O2
102.1 82.1 86.1 86.1 116.1 74.1 92.1 67.1 124.1 132.2 96.1 140.3 98.1 116.1 136.2 96.1 98.1 110.1 86.1 84.1 116.2 160.2 134.2 168.3 94.1 184.3 150.2
RT is the Retention time. 393
%Area 723 K
823 K
923 K
1023 K
2.39 2.18 2.96 2.47 19.22 3.57 0.71 2.31 2.11 10.01 9.85 – 3.02 3.46 – 1.33 1.8 1.79 0.54 1.66 – 0.85 0.8 – – 0.5 1.39
11.79 – 3.32 1.3 13.7 1.68 1.15 2.32 1.36 31.16 7.15 – 1.04 1.5 1.57 1.12 0.57 1.01 0.49 1.23 .0.45 2.58 0.36 – – 1.18 –
– 4.44 5.81 1.55 15.82 1.79 5.31 2.06 1.66 12.09 8.79 0.83 – 1.01 0.97 – – – – – 0.58. 2.41 0.67 0.67 0.88 – –
– 4.93 – 0.7 9.02 – 11.02 3.34 – 4.86 5.41 1.95 – – – – – 1.1 – – – 0.63 1.3 2.06 – –
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important raw material in the chemical industry, such as in the manufacture of pharmaceuticals, food, additives, resins and others (Lu et al., 2011). Toluene is also widely used in various industrial processes, such as in the production of paints, varnishes, adhesives and fuel.
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Saccharomyces pastorianus immobilized on brewer's spent grain in continuous system for lead ion biosorption. Int. Biodeterior. Biodegrad. 96, 191–197. Lira, T.S., Santos, K.G., Murata, V.V., Gianesella, M., Barrozo, M.A., 2010. The use of nonlinearity measures in the estimation of kinetic parameters of sugarcane bagasse pyrolysis. Chem. Eng. Technol. 33 (10), 1699–1705. Lobato, F.S., Steffen Jr, V., Arruda, E.B., Barrozo, M.A.S., 2008. Estimation of drying parameters in rotary dryers using differential evolution. Journal of Physics: Conference Series, vol. 135. IOP Publishing, pp. 1. Lopes, F.C.R., Tannous, K., Rueda-Ordóñez, Y.J., 2016. Combustion reaction kinetics of guarana seed residue applying isoconversional methods and consecutive reaction scheme. Bioresour. Technol. 219, 392–402. Lu, Q., Yang, X.C., Dong, C.Q., Zhang, Z.F., Zhang, X.M., Zhu, X.F., 2011. Influence of pyrolysis temperature and time on the cellulose fast pyrolysis products: analytical PyGC/MS study. J. Anal. 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Mussatto, S.I., 2014. Brewer's spent grain: a valuable feedstock for industrial applications. J. Sci. Food Agric. 94 (7), 1264–1275. Odetoye, T.E., Onifade, K.R., AbuBakar, M.S., Titiloye, J.O., 2013. Thermochemical characterisation of Parinari polyandra Benth fruit shell. Ind. Crops Prod. 44, 62–66. Ohra-Aho, T., Niemi, P., Aura, A.M., Orlandi, M., Poutanen, K., Buchert, J., Tamminen, T., 2016. Structure of brewer’s spent grain lignin and its interactions with gut microbiota in vitro. J. Agric. Food Chem. 64 (4), 812–820. Oliveira, T.J.P., Cardoso, C.R., Ataíde, C.H., 2015. Fast pyrolysis of soybean hulls: analysis of bio-oil produced in a fluidized bed reactor and of vapor obtained in analytical pyrolysis. J. Therm. Anal. Calorim. 120 (1), 427–438. Pandey, K.K., Pitman, A.J., 2003. FTIR studies of the changes in wood chemistry following decay by brown-rot and white-rot fungi. Int. Biodeterior. Biodegrad. 52 (3), 151–160. Pattiya, A., 2011. Bio-oil production via fast pyrolysis of biomass residues from cassava plants in a fluidised-bed reactor. Bioresour. Technol. 102 (2), 1959. Poerschmann, J., Weiner, B., Wedwitschka, H., Baskyr, I., Koehler, R., Kopinke, F.D., 2014. Characterization of biocoals and dissolved organic matter phases obtained upon hydrothermal carbonization of brewer’s spent grain. Bioresour. Technol. 164, 162–169. Popescu, C.M., Popescu, M.C., Singurel, G., Vasile, C., Argyropoulos, D.S., Willfor, S., 2007. Spectral characterization of eucalyptus wood. Appl. Spectrosc. 61 (11), 1168–1177. Ravindran, R., Jaiswal, S., Abu-Ghannam, N., Jaiswal, A.K., 2018. A comparative analysis of pretreatment strategies on the properties and hydrolysis of brewers’ spent grain. Bioresour. Technol. 248, 272–279. Reis, S.F., Gullón, B., Gullón, P., Ferreira, S., Maia, C.J., Alonso, J.L., Domingues, F.C., Abu-Ghannam, N., 2014. Evaluation of the prebiotic potential of arabinoxylans from brewer’s spent grain. Appl. Microbiol. Biotechnol. 98 (22), 9365–9373. Rueda-Ordóñez, Y.J., Tannous, K., 2015. Isoconversional kinetic study of the thermal decomposition of sugarcane straw for thermal conversion processes. Bioresour. Technol. 196, 136–144. Santana, J.A., Carvalho, W.S., Ataíde, C.H., 2018. Catalytic effect of ZSM-5 zeolite and HY-340 niobic acid on the pyrolysis of industrial kraft lignins. Ind. Crops Prod. 111, 126–132. Santos, K.G., Lira, T.S., Murata, V.V., Gianesella, M., Barrozo, M.A., 2010. Pyrolysis of sugarcane bagasse: a consecutive reactions kinetic model from TGA experiments. Mater. Sci. Forum 660, 593–598 (Trans Tech Publications). Santos, K.G., Lira, T.S., Gianesella, M., Lobato, F.S., Murata, V.V., Barrozo, M.A.S., 2012a. Bagasse pyrolysis: a comparative study of kinetic models. Chem. Eng. Commun. 199, 109–121. Santos, K.G., Lobato, F.S., Lira, T.S., Murata, V.V., Barrozo, M.A.S., 2012b. Sensitivity analysis applied to independent parallel reaction model for pyrolysis of bagasse. Chem. Eng. 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4. Conclusions The results of this study showed that the brewer's spent grain (BSG), which is the most abundant waste of the brewing industry, has a good potential for bio-oil production owing to its high volatile matter content and the high heating value (HHV). Devolatilization kinetics of BSG was successfully modeled by the IPR model. The parameters estimated and the kinetic behavior were consistent with the experimental measurements. High added-value compounds e.g. 1-methoxy-2-propyl acetate, furfural and toluene were obtained from fast pyrolysis of BSG in the temperature range investigated, which indicates that BSG can be a source for production of chemicals. Acknowledgements The authors acknowledge CNPq (National Council for Scientific and Technological Development), CAPES (Federal Agency for the Support and Improvement of Higher Education) andFAPEMIG (Minas Gerais State Research Foundation) for the financial aid. We also thank to Microbrewery Überbräu Ltda. for providing the samples. References Aliyu, S., Bala, M., 2011. Brewer’s spent grain: a review of its potentials and applications. Afr. J. Biotechnol. 10 (3), 324–331. Alvarenga, L.M., Xavier, T.P., Barrozo, M.A.S., Bacelos, M.S., Lira, T.S., 2012. Analysis of reaction kinetics of carton packaging pyrolysis. Procedia Eng. 42, 113–122. Alvarenga, L.M., Xavier, T.P., Barrozo, M.A.S., Bacelos, M.S., Lira, T.S., 2016. Determination of activation energy of pyrolysis of carton packaging wastes and its pure components using thermogravimetry. Waste Manage. 53, 68–75. Alvarez, J., Lopez, G., Amutio, M., Bilbao, J., Olazar, M., 2014. Bio-oil production from rice husk fast pyrolysis in a conical spouted bed reactor. Fuel 128, 162–169. Amutio, M., Lopez, G., Alvarez, J., Olazar, M., Bilbao, J., 2015. Fast pyrolysis of eucalyptus waste in a conical spouted bed reactor. Bioresour. Technol. 194, 225–232. Andrade, L.A., Barrozo, M.A.S., Vieira, L.G.M., 2016. Thermo-chemical behavior and product formation during pyrolysis of mango seed shell. Ind. Crops Prod. 85, 174–180. Andrade, L.A., Batista, F.R.X., Lira, T.S., Barrozo, M.A.S., Vieira, L.G.M., 2018. Characterization and product formation during the catalytic and non-catalytic pyrolysis of the green microalgae Chlamydomonas reinhardtii. Renew. Energy 119, 731–740. Arruda, E.B., Façanha, J.M.F., Pires, L.N., Assis, A.J., Barrozo, M.A.S., 2009. Conventional and modified rotary dryer: comparison of performance in fertilizer drying. Chem. Eng. Proc. 48, 1414–1418. Buffington, J., 2014. The economic potential of brewer’s spent grain (BSG) as a biomass feedstock. Adv. Chem.Eng. Sci. 2014. Cardoso, C.R., Ataide, C.H., 2013. Analytical pyrolysis of tobacco residue: effect of temperature and inorganic additives. J. Anal. Appl. Pyrolysis 99, 49–57. Carvalho, W.S., Cunha, I.F., Pereira, M.S., Ataíde, C.H., 2015a. Thermal decomposition profile and product selectivity of analytical pyrolysis of sweet sorghum bagasse: effect of addition of inorganic salts. Ind. Crops Prod. 74, 372–380. Carvalho, W.S., Oliveira, T.J., Cardoso, C.R., Ataíde, C.H., 2015b. Thermogravimetric analysis and analytical pyrolysis of a variety of lignocellulosic sorghum. Chem. Eng. Res. Des. 95, 337–345. Celaya, A.M., Lade, A.T., Goldfarb, J.L., 2015. Co-combustion of brewer's spent grains and Illinois No. 6 coal: impact of blend ratio on pyrolysis and oxidation behavior. Fuel Process. Technol. 129, 39–51. Ceylan, S., Topçu, Y., 2014. Pyrolysis kinetics of hazelnut husk using thermogravimetric analysis. Bioresour. Technol. 156, 182–188. Chen, Z., Hu, M., Zhu, X., Guo, D., Liu, S., Hu, Z., Xiao, B., Wang, J., Laghari, M., 2015. Characteristics and kinetic study on pyrolysis of five lignocellulosic biomass via thermogravimetric analysis. Bioresour. Technol. 192, 441–450. Collazzo, G.C., Broetto, C.C., Perondi, D., Junges, J., Dettmer, A., Dornelles Filho, A.A., Godinho, M., 2017. A detailed non-isothermal kinetic study of elephant grass pyrolysis from different models. Appl. Therm. Eng. 110, 1200–1211. Domínguez, J.C., Oliet, M., Alonso, M.V., Gilarranz, M.A., Rodríguez, F., 2008. Thermal stability and pyrolysis kinetics of organosolv lignins obtained from Eucalyptus globulus. Ind. Crops Prod. 27 (2), 150–156. Fernandes, N.J., Ataide, C.H., Barrozo, M.A.S., 2009. Modeling and experimental study of hydrodynamic and drying characteristics of an industrial rotary dryer. Braz. J. Chem. Eng. 26, 331–341.
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adsorption properties. Waste Manage. Res. 32 (7), 634–645. Varma, A.K., Mondal, P., 2017. Pyrolysis of sugarcane bagasse in semi batch reactor: effects of process parameters on product yields and characterization of products. Ind. Crops Prod. 95, 704–717. Xavier, T.P., Lira, T.S., Schettino Jr., M.A., Barrozo, M.A.S., 2016. A study of pyrolysis of Macadamia Nut Shell: parametric sensitivity analysis of the IPR model. Braz. J. Chem. Eng. 33 (1), 115–122. Xiros, C., Christakopoulos, P., 2012. Biotechnological potential of brewers spent grain and its recent applications. Waste Biomass Valorization 3 (2), 213–232.
Smets, K., Schreurs, S., Carleer, R., Yperman, J., 2014. Valorization of raspberry seed cake by flash and slow pyrolysis: product yield and characterization of the liquid and solid fraction. J. Anal. Appl. Pyrolysis 107, 289–297. Sohni, S., Norulaini, N.N., Hashim, R., Khan, S.B., Fadhullah, W., Omar, A.M., 2018. Physicochemical characterization of Malaysian crop and agro-industrial biomass residues as renewable energy resources. Ind. Crops Prod. 111, 642–650. Titiloye, J.O., Bakar, M.S.A., Odetoye, T.E., 2013. Thermochemical characterisation of agricultural wastes from West Africa. Ind. Crops Prod. 47, 199–203. Vanreppelen, K., Vanderheyden, S., Kuppens, T., Schreurs, S., Yperman, J., Carleer, R., 2014. Activated carbon from pyrolysis of brewer’s spent grain: production and
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Contents lists available at ScienceDirect
Industrial Crops & Products journal homepage: www.elsevier.com/locate/indcrop
Pyrolysis of brewer’s spent grain: Kinetic study and products identification a
b
c
a
Lidja D.M.S. Borel , Taísa S. Lira , Jânio A. Ribeiro , Carlos H. Ataíde , Marcos A.S. Barrozo a b c
a,⁎
T
Federal University of Uberlândia, School of Chemical Engineering, Brazil Federal University of Espírito Santo, Dep. Eng. Technol., Brazil Federal University of Mato Grosso, Institute of Engineering, Brazil
A R T I C LE I N FO
A B S T R A C T
Keywords: Brewer’s spent grain Thermogravimetric analysis Biomass Pyrolysis
In this study, the physicochemical properties, the thermal degradation behavior and the products generated from pyrolysis of brewer's spent grain (BSG) were investigated to evaluate the potential of this agro-industrial residue for bio-oil production via pyrolysis. Thermogravimetric analyses were performed in a nitrogen atmosphere. The kinetic parameters were estimated by isoconversional methods and by independent parallel reactions model (IPR). The results showed that the BSG has a good potential for bio-oil production owing to its high volatile matter content and the high heating value. The kinetic behavior was successfully modeled by the IPR model. High added-value compounds were identified from analytical pyrolysis, which indicates that BSG can be a source of important raw materials for the chemical industry.
1. Introduction The use of agro-industrial waste for energy production is an interesting possibility in the context of global efforts to maximize value addition of these residues, while reducing negative impact of industrial processes (Varma and Mondal, 2017). Brewer’s spent grain (BSG) is a major by-product generated from the brewing industry; it represents 85% of the total waste generated in this industry; 20 kg per 100 L of beer produced (Mahmood et al., 2013, Mussatto, 2014; Buffington, 2014; Ohra-Aho et al., 2016). This material comprises barley grain husks that are obtained as solid residue after the production of wort (Carvalho et al., 2015b). Approximately 39 million tons of beer are produced annually, with China, USA, Brazil, Russia and Germany being the largest producers (Lynch et al., 2016). The scientific community has made various proposals for BSG reuse. As a source of health-promoting nutrients, it has been evaluated by Reis et al. (2014) through arabinoxylans derived from BSG and by Guo et al. (2014) through BSG-enriched biscuits. These authors reported that the products obtained provide protection for cardiovascular diseases, cancer and other degenerative diseases. As adsorbent material, Vanreppelen et al. (2014) studied activated carbon derived from BSG for phenol absorption in the water treatment; Kordialik-Bogacka (2014) studied BSG as support for Saccharomyces pastorianus cells for the removal of lead ions. Ravindran et al. (2018) performed enzymatic hydrolysis of BSG to produce value added products. Besides, there are still studies of BSG use as additive in the production of building bricks; production of ethanol, lactic acid, enzymes and xylitol; among others
⁎
Corresponding author. E-mail addresses: [email protected], [email protected] (M.A.S. Barrozo).
https://doi.org/10.1016/j.indcrop.2018.05.051 Received 30 January 2018; Received in revised form 30 April 2018; Accepted 20 May 2018 0926-6690/ © 2018 Elsevier B.V. All rights reserved.
(Aliyu and Bala, 2011). Another alternative of BSG use, with possibly higher profitability, is the thermochemical conversion of this waste into biofuel or valuable chemical commodities by pyrolysis process. Mahmood et al. (2013) studied the intermediate pyrolysis and catalytic steam reforming (Ni/ Al2O3) of Brewers spent grain using a bench scale batch fixed bed reactor at 450 °C. These authors reported an increase of gaseous yield, mainly H2 and CO, with heating value between 10.8–25.2 MJ/m3. Poerschmann et al. (2014) proposed the application hydrothermal carbonization of BSG to produce biocoal. BSG is a lignocellulosic fibrous material, which composition is influenced by the species of barley, the malting process, proportion and types of adjuncts used, as well as the processes of milling, mashing and clarification. These variables can also influence the kinetic pyrolysis parameters (Aliyu and Bala, 2011; Xiros and Christakopoulos, 2012). To ensure the viability of the reuse of BSG by a thermochemical conversion process, it is imperative to consider aspects of the raw material, process and product (Kim and Agblevor, 2014; Sohni et al., 2018). Therefore, the BSG characterization is essential for predicting its behavior upon conversion to fuel or chemicals, as well as for selecting the most appropriate pyrolysis technique. Moreover, knowing the kinetic parameters is essential for proper description of the thermal conversion processes, in order to improve the design of reactors. For this, the thermogravimetric data (TGA) can be treated through different approaches (Domínguez et al., 2008; Gao et al., 2013; Odetoye et al., 2013; Titiloye et al., 2013). The isoconversional methods are very useful and interesting tool, since they provide consistent results for
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hour in a moisture-free sample was performed to estimate the extractives content of BSG. The lignin content was determined according to modified TAPPI standard T222 om-22 (2002c). The extractive and moisture free sample was hydrolyzed using sulfuric acid in two steps: first at 283–288 K and 72% (w/w) for 24 h, and after under heating and reflux for 4 h with 4% (w/w). Hemicellulose and α-cellulose constitute the holocellulose content, which was measured using glacial acetic acid and sodium hypochlorite at 348 ± 2 K. The α-cellulose was determined by treating the holocellulose sample with potassium hydroxide solutions of 5 and 24% (w/ w). The hemicellulose content was calculated subtracting the α-cellulose content from the holocellulose (Andrade et al., 2016).
activation energy estimation (Lira et al., 2010; Santos et al., 2010; Alvarenga et al., 2012; Santos et al., 2012c; Lopes et al., 2016). However, the independent parallel reaction kinetic model (IPR model) is a more robust technique to describe the kinetic behavior. This model provides detailed kinetic information for each subcomponent of the biomass (Santos et al., 2012b; Carvalho et al., 2015b). The composition of the bio-oil can be obtained via analytical pyrolysis and thus to evaluate the feasibility of its application (Greenhalf et al., 2012; Carvalho et al., 2015a). The influence of different operating conditions can be investigated by this technique and thus develop strategies to increase the bio-oil yield and the quality of the product obtained, by favoring the formation of more attractive compounds (Lu et al., 2011; Murillo et al., 2014; Santana et al., 2018). Some works of the literature have studied the thermochemical conversion of waste of the brewing industry. However, specifically on pyrolysis, there are still challenges to be overcome to make the process be cost effective. Thus, additional investigations are needed to a greater understanding on some important aspects of the BSG pyrolysis, such as the relationship between the pyrolysis products and the operating conditions, a reliable kinetic prediction and a complete characterization of this waste. Thus, this paper presents a complete thermochemical characterization of brewer’s spent grain composed by proximate and ultimate analysis, compositional analysis, X-ray fluorescence spectrometry analysis, infrared spectra, analytical pyrolysis and thermogravimetric analyses. The effects of the heating rate and the reaction temperature on the degradation behavior and on the pyrolytic products obtained were evaluated. This information may be an important contribution for the further studies in the area. Furthermore, the kinetic parameters of the devolatilization were determined through two approaches: by isoconversional methods and by the independent parallel reactions (IPR) model using thermogravimetric analyses data.
2.2.4. X-ray fluorescence spectrometry analysis The inorganic matter in BSG was measured by X-ray fluorescence spectrometry in a pre-calibrated equipment (S8 Tiger, Bruker). The samples were prepared in the form of pressed pellets of 34 mm diameter, using 4.5 g of biomass ( < 170 mesh). Semi-quantitative analysis was performed using the Quant-Express calibration package. The analyses were performed in triplicate and the mean results were reported. 2.2.5. Fourier transform infrared spectroscopy (FTIR) The FTIR spectra of BSG were obtained using a spectrophotometer (Shimadzu, IR Prestige-21). The analyses were performed with pellets of BSG and KBr (1:100 w/w) in the range of 4000–400 cm−1 with a resolution of 4 cm−1and a total of 32 scans. 2.2.6. Calorific value The higher heating value (HHV) of BSG was quantified using an oxygen bomb calorimeter (IKAC2000). The measurements were performed in triplicate according to ASTM D2015.
2. Materials and methods 2.3. Thermogravimetric analysis (TGA) 2.1. Materials A thermogravimetric analyzer (Shimadzu, DTG-60H) was used for monitoring the mass loss (TG) and the differential weight loss (DTG) profiles. The thermogravimetric tests of the samples (8 mg) were performed from 298 to 1173 K at heating rates of 5, 10, 20, 30, 40 and 50 K/min, using nitrogen as purge gas at a flow rate of 50 mL/min.
The BSG used in this study was obtained from a brewing process that provided 100% malted barley (without addition of other cereal adjuncts). The material was supplied by a microbrewery of Uberlândia, Minas Gerais State, Brazil, and it was classified by sieving after drying (oven method at 378 ± 3 K for 24 h). The average sieve diameter of dried BSG was 3.23 mm. The samples were ground so that they passed through a 100 mesh screen to perform the chemical characterization.
2.3.1. Kinetic study Isoconversional methods and the independent parallel reactions (IPR) model were used to estimate the kinetic parameters of the devolatilization of BSG.
2.2. Characterization of the BSG
2.3.1.1. Isoconversional methods. The rate of reaction can be expressed from product of two independent terms, according to the following equation:
2.2.1. Ultimate analysis Chemical composition of BSG in terms of carbon (C), hydrogen (H), nitrogen (N), oxygen (O) and sulfur (S) was determined using a Perkin Elmer 2400 CHNS/O elemental analyzer, operating at 1198 K in an atmosphere of pure oxygen. The oxygen content was calculated by difference also considering the ash content according to Eq. (1): %O = 100 − %C − %H − %S − %Ash
dX = K (T )⋅f (X ) dt
(2)
Pyrolytic conversion was calculated according to Eq. (3): (1)
X= 2.2.2. Proximate analysis The moisture, volatiles and ash contents were measured according to the ASTM standard (E1756-01, E872-82 and E1755-01). The fixed carbon was determined by difference. The analyses were performed in triplicate and the mean results were reported.
m o − mt mo − m∞
(3)
where mo is the initial mass of sample; m∞ is the final mass and mt is an instantaneous mass. The thermal dependence term K(T) can be described by an Arrhenius relationship. Considering the non-isothermal conditions, in which the heating rate of the process is β = dT/dt, Eq. (2) becomes Eq. (4):
2.2.3. Compositional analysis The extractives, hemicellulose, cellulose and lignin contents were determined according to the procedure proposed by Andrade et al. (2016). Soxhlet extraction with acetone as solvent using 6 refluxes per
dX k 0 -Ea = eRT dT f(X) β The integral form of Eq. (3) results in: 389
(4)
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Table 1 Physicochemical properties of BSG. Ultimate analysis (% wt) Proximate analysis (% wt) Chemical composition (% wt) HHVa (MJ/kg) a
C 47.2 ± 1.3 Moisture 3.97 ± 0.00 Extractives 5.26 ± 0.06 21.6 ± 2.8
H 7.2 ± 0.1 Volatile matter 83.30 ± 0.29 Lignin 29.37 ± 4.03
N 3.6 ± 0.4 Ash 3.22 ± 0.03 Cellulose 15.14 ± 0.03
S 1.1 ± 0.1 Fixed carbon 9.51 ± 0.31 Hemicellulose 50.23 ± 0.03
O 37.6 ± 1.7
HHV is the higher heating value.
Table 2 Element and oxides content in the BSG samples (% w/w ± standard deviation). Element
Composition contents (wt.%)
Oxides
Composition contents (wt.%)
P Si K Ca Mg Fe S Zn Mn Cu Cl Br
0.75 0.74 0.56 0.39 0.15 0.14 0.76 0.07 0.02 0.02 0.12 0.02
P2O5 SiO2 K2O CaO MgO Fe2O3 SO3 ZnO MnO CuO – –
1.74 1.96 0.68 0.98 0.43 0.19 1.91 0.09 0.08 0.02
∫0
g(X)=
X
± ± ± ± ± ± ± ± ± ± ± ±
0.02 0.01 0.01 0.01 0.01 0.01 0.02 0.00 0.00 0.00 0.01 0.00
dX k 0 = f(X) β
∫T
T
-Ea
eRT dT=
0
± ± ± ± ± ± ± ± ± ±
0.01 0.64 0.00 0.74 0.33 0.01 0.05 0.01 0.10 0.00
k 0Ea Ea ⎞ p⎛ βR ⎝ RT ⎠
(5)
Fig. 1. FTIR spectra of BSG.
where ko represents the pre-exponential factor, R represents the ideal gas constant, Ea represents the activation energy and T represents the absolute temperature of the sample. Eq. (5) can be solved by numerical methods or approximations. In this study we used the methods of Ozawa and Kissinger according to Eq. (6) and Eq. (7), respectively. These methods follow the same physicochemical and mathematical assumptions and differ according to approximation for the polynomial p(E/RT) in Eq. (5).
ln β = −1.0518[Ea RT ] + [ln(k 0 Ea R) − ln g (X ) − 5.3305]
(6)
β E k R ln ⎛⎜ 2 ⎟⎞ = −⎛ a ⎞ + ⎡ln ⎛ 0 ⎞ − ln g (x ) ⎤ ⎢ ⎥ RT T ⎦ ⎝ max ⎠ ⎣ ⎝ T ⎠ ⎝ max ⎠
(7)
⎜
dmcalc = −(mo − m) dt
2.3.1.2. Independent parallel reactions (IPR) model. The Independent Parallel Reactions (IPR) approach considers that each subcomponent is degraded individually, thus ensuring a potentially simultaneous decomposition. Thus, the rate of conversion for each component is:
N
O. F .DTG =
∑ j=1
dXi dt
(10)
obs
⎛ ⎛ dm ⎞ ⎜ dt ⎠j ⎝⎝
calc 2
dm ⎞ ⎞ −⎛ ⎟ ⎝ dt ⎠ j ⎠
(11)
where subscript j refers to the data points used, N represents the number of experimental data of each run and (dm/dt)obs is the experimentally observed value and (dm/dt)calc is the value calculated with a given set of parameters (Fernandes et al., 2009).
(8)
where Xi, k0i, Eai, and ni represent, respectively, the conversion, preexponential factor, activation energy, and apparent order of reaction of each component. The global reaction rate is the linear combination of the rates of the partial reactions, considering the mass fraction of each component (ci):
2.4. Analytical pyrolysis The fast pyrolysis of BSG was performed in a CDS Pyroprobe® 5200 pyrolyzer at 723, 823, 923 and 1023 K, with heating rate of 20 K/ms. Helium (99.999 purity) was used as inert gas. The volatile products were analyzed by gas chromatography and mass spectrometry (Shimadzu GC/MS-QP2010 Plus). The gas used in the analyses was helium (99.999 purity) at a split ratio of 100:1, using a Rtx-1701 GC column. Data processing was performed using the NIST05 library (Cardoso and Ataide, 2013).
nc
dX dX = − ∑ ci i dt dt i=1
i=1
ci
First-order reactions kinetics were assumed for extractives, cellulose and hemicellulose. The pyrolysis of lignin cannot be modeled by firstorder kinetics. Various studies in the literature report that the pyrolysis of lignin is better described by third-order reaction kinetics (Santos et al., 2012a; Alvarenga et al., 2016). An algorithm based on differential evolution method was implemented in Mathlab R2013a to estimate the kinetic parameters (Lobato et al., 2008, Arruda et al., 2009; Santos et al., 2012b). The objective function to be minimized is the sum of the squared residuals according to the following equation:
⎟
dXi E = koi exp ⎛− ai ⎞ (1 − Xi )ni dt ⎝ RT ⎠
nc
∑
(9)
where nc represents the number total of components. Four components were considered for this biomass (BSG): extractives, cellulose, hemicellulose, and lignin. Thus, the mass loss with time is calculated using the following relationship: 390
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Fig. 3. Linear regression using (a) Ozawa (b) Kissinger methods for pyrolysis reaction of BSG.
Fig. 2. Experimental (a) TG and (b) DTG curves of BSG as function of reaction temperature at the different heating rates.
The inorganic matter in BSG was determined by X-ray fluorescence spectrometry analysis and the results are presented in Table 2. It can be seen, that minerals present in greater quantities in this residue are: phosphorus, silicon, potassium and calcium. The results of FTIR spectroscopy for the BSG are presented in Fig. 1. It was possible to identify the functional groups, and from the intensity value of the absorption band, the most abundant chemical bonds could also be identified, such as: hydroxyl in water, alcohol and phenols (3428 cm−1), CeH group in asymmetric and symmetric aliphatic (2930–2860 cm−1), CeN or a CeC triple bond (2400–2200 cm−1), carbonyl in aldehydes or unconjugated ketone (1732 cm−1), OeH from the water molecules absorbed and conjugated C]O with a benzene ring in lignin or cellulose (1647 cm−1), C]C in aromatics related to the lignin (1533 cm−1), C−H bending in aliphatic compounds or CeH asymmetric deformation of aromatic skeletal in lignin (1454 cm−1), CeH vibration in cellulose (1251 cm−1), CeO stretching and hydroxyl bending in primary, secondary and tertiary alcohols, esters and ethers (950–1200 cm−1), CeH deformation in cellulose (856 cm−1), AreOH functional group in phenols (706 cm−1) and CeOeC group in ethers (480 cm−1) (Pandey and Pitman, 2003; Popescu et al., 2007). The results were consistent with reported data in literature for other similar biomasses (Andrade et al., 2016; Ma et al., 2016).
3. Results and discussion 3.1. Characterization of BSG Table 1 shows the results of the measurements of the physicochemical properties of the BSG. The results of chemical analysis of BSG are consistent with values reported in the literature for this residue of the brewing industry (Celaya et al., 2015; Mahmood et al., 2013; Vanreppelen et al., 2014). The BSG showed high H/C ratio (0.15), and an O/C ratio of 0.80. Thus, according to the Van Krevelen diagram (H/C versus O/C), BSG has good thermal properties compared with other waste biomass materials, such as: eucalyptus, H/C = 0.12 and O/ C = 1.26 (Chen et al., 2015); soybean hulls, H/C = 0.15 and O/ C = 1.35 (Oliveira et al., 2015) and rice hulls H/C = 0.13 and O/ C = 0.94 (Alvarez et al., 2014). This agrees with the high heating value found, which was higher than hazelnut husk (18.5 MJ/kg) (Ceylan and Topçu, 2014) and pine wood (17.34 MJ/kg) (Mishra et al., 2015). The BSG also has high volatile content (83.30%), similar to eucalyptus residue (Amutio et al., 2015) and cassava stem (Pattiya, 2011). Furthermore, BSG showed high hemicellulose content compared to other major subcomponents, which offers significant potential for interesting pyrolysis products, as well as to produce more gas and less tar. 391
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respectively. The lignin degradation it is highlighted by a shoulder at higher temperatures. At temperatures above 850 K passive pyrolysis or carbonization occurs (Stage 3), and the weight loss occurred smoothly (Chen et al., 2015; Ma et al., 2016; Rueda-Ordóñez and Tannous, 2015).
Table 3 Mass fraction and kinetic parameters of IPR model for the pyrolysis of BSG. β [K/ min]
Component
Mass fraction
k0 [s−1]
Ea [kJ/ mol]
Deviationa (%)
5
Extractives Hemicellulose Cellulose Lignin Extractives Hemicellulose Cellulose Lignin Extractives Hemicellulose Cellulose Lignin Extractives Hemicellulose Cellulose Lignin Extractives Hemicellulose Cellulose Lignin Extractives Hemicellulose Cellulose Lignin
0.0575 0.506 0.136 0.284 0.0575 0.508 0.136 0.320 0.0575 0.500 0.136 0.314 0.0575 0.504 0.136 0.317 0.0575 0.488 0.136 0.323 0.0575 0.506 0.136 0.323
1.98∙1019 1.08∙104 6.90∙1016 4.75∙106 3.86∙1018 4.72∙104 2.25∙1017 1.20∙107 8.41∙1017 2.55∙105 1.22∙1018 2.61∙106 1.12∙1018 3.18∙105 8.86∙1017 3.48∙106 8.54∙1016 3.19∙106 1.52∙1019 2.65∙105 1.37∙1017 2.04∙106 9.00∙1018 4.27∙105
196.14 71.01 224.13 117.93 191.34 75.88 230.90 120.55 186.37 81.30 238.49 109.87 187.68 81.01 236.04 109.78 178.25 90.95 251.15 94.07 179.41 87.90 246.56 95.25
3.93
10
20
30
40
50
a
3.2.1. Isoconversional approach Fig. 3 shows the linear regressions for the Ozawa (a) and Kissinger (b) methods. The results of Ozawa's method show that the average value of the activation energy in the conversion range of 0.1–0.2 (corresponding to the range 458–553 K) was 104.7 kJ/mol. In this temperature range begins the depolymerization of the biomass subcomponents, mainly hemicellulose, whose degradation requires low energy amount. In the range of 0.3–0.6 (equivalent to 511–636 K), the activation energy increases from 131 to 164 kJ/mol. This increase (25%) is because in this range begins cellulose degradation, which has a more complex structure and, therefore, requires more energy for its degradation. In the range of 0.6–0.8 (595–692 K), the maximum activation energy is observed (181.6 kJ/mol), which is associated with decomposition of cellulose, and first step of lignin decomposition. For conversion higher than 0.8 (T > 692 K) the degradation was almost complete and the activation energy decreases to 139.7 kJ/mol, which corresponds to the degradation of residual lignin and the formation of char (Rueda-Ordóñez and Tannous, 2015; Collazzo et al., 2017). The average value of the activation energy obtained by Ozawa’s method was Ea = 147.7 kJ/mol (R2 = 0.9670). The Kissinger method leads to a value of Ea = 140.4 kJ/mol (R2 = 0.9964). Therefore, the values of activation energy obtained from these two isoconversional methods are in agreement.
3.43
3.53
3.45
3.73
3.61
Deviation was defined asFITDTG (%) = 100 (O. F .DTG ) N max( (dm dt )obs j ).
3.2. Kinetic study
3.2.2. Independent parallel reactions (IPR) model The IPR model was used in this study to describe the pyrolysis of BSG, assuming four parallel reactions in which, extractives, hemicellulose and cellulose are described as first order reactions and lignin as a third-order reaction. The results of the estimated kinetic parameters for the pyrolysis of BSG using IPR model are shown in Table 3. The literature shows that for lignocellulosic biomass the activation energy varies from 80 to 150 kJ/ mol for the hemicellulose, 80–286 kJ/mol for cellulose and from 10 to 180 kJ/mol for lignin (Alvarenga et al., 2016; Xavier et al., 2016). Thus, the results obtained for each component in this study (Table 3) are
The differential thermogravimetric (DTG) curves are shown in Fig. 2. It can be seen that the DTG profiles of BSG had a similar behavior at heating range from 5 to 50 K/min. Thermal degradation of BSG can be divided into three stages. In stage 1, from 301 to 428 K, the moisture and lighter volatiles are removed without chemical reaction. In the stage 2, called active pyrolysis or devolatilization, the main components of the biomass are degraded. Initially, the thermal decomposition of extractives occurs being characterized by a “shoulder” in DTG curve. Then two peaks in the DTG curve indicate the degradation of hemicellulose and cellulose,
Fig. 4. DTG curves − experimental and simulated (by IPR model) for the heating rate of 30 K/min. 392
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estimate the mass fractions of each pseudo-components of this residue of the brewing industry. 3.3. Analytical pyrolysis Analytical pyrolysis was used to verify the potential of BSG as a source of biomass for the biofuel production. The main products present in the vapor produced by the micropyrolyzer were identified. The pyrolytic vapors are complex mixtures of organic compounds whose distribution can be affected by pyrolysis conditions. The identified compounds were classified in groups of oxygenated, heteroaromatic, hydrocarbon, nitrogenated compounds and others (amines, amides, etc) detected in minor amounts. Fig. 5 shows the influence of temperature on the presence of the group of compounds in the pyrolytic vapors. Among the identified products there is a predominance of holocellulose-derived compounds such as 2-propanone, acetic acid and furfural over lignin-derived compounds such as phenolic derivatives and benzene. There was a reduction in the amount of oxygen compounds in the vapors composition while the number of hydrocarbons increased with increasing temperature. This may be related to the fact that the deoxygenation is favored during decomposition at higher temperatures (Andrade et al., 2018). Table 4 shows the main compounds identified from the fast pyrolysis of BSG at 723, 823, 923 and 1023 K. The major compounds identified in the pyrolysis of BSG, at the temperature range used in this work were: 1-methoxy-2-propyl acetate, acetic acid, acetic anhydride, furfural and toluene. The 1-methoxy-2propyl acetate is used in the production of paints, coatings, cleaners, electronics manufacturing, silk-screen printing inks and metal finishers. Acetic acid is a carboxylic acid used as a raw material for the production of ethyl vinyl which is used to produce polyethylene terephthalate (PET), among others (Smets et al., 2014; Carvalho et al., 2015b). The acetic anhydride is applied in the production of cellulose acetate, explosives and aspirin (García et al., 2016). The furfural is also an
Fig. 5. Product distribution from pyrolysis of BSG at different reaction temperatures.
consistent with reported data in literature for lignocellulosic biomass materials. Fig. 4 presents the experimental and simulated (by model IPR) DTG curves for rate of 30 K/min, as example. The other heating rates had the same behavior. It can be seen that the curve simulated by the model IPR is in a good agreement with the experimental curve, with a deviation lower than 3.93%. Thus confirming the good quality of the prediction of the pyrolysis kinetic behavior of the BSG by the IPR model. It is also worth noting that the mass fractions estimated by the model IPR (Table 3) are close to the values obtained experimentally (Table 1). The deviations were lower than 10% and they are within the ranges described in the literature for this material, which are: extractives, 4.7–5.8; hemicellulose, 23.41–48.78; cellulose, 12.29–24.68 and lignin, 7.12–27.8 (Vanreppelen et al., 2014; Mahmood et al., 2013). This result shows that the IPR model was also adequate to
Table 4 Main compounds identified in analytical pyrolysis of BSG at different temperatures. RTa (min)
5.7 6.4 7.1 8.5 9.7 11.2 11.5 16.3 17.6 18.4 19.3 20.6 21.7 22.2 23.7 24.2 25.3 26.9 28.1 28.7 29.1 30.5 .30.8 31.4 32.5 36.4 45.3 a
Name
Acetic anhydride 2-methyl-Furan 2,3-Butanedione 3-methyl-Butanal, Acetic acid 1-hydroxy-2-Propanone Toluene Pyrrole 3,3′-oxybis-Propanenitrile 1-Methoxy-2-propyl acetate Furfural 1-Decene 2-Furanmethanol 1-(acetyloxy)-2-Propanone Limonene 2-Cyclopentene-1,4-dione 6-Oxa-bicyclo[3,1,0]hexan-3-one 5-methyl-2-Furancarboxaldehyde Butyrolactone 2(5H)-Furanone Hexanoic acid 2-Butoxyethyl acetate Benzeneacetaldehyde 1-Dodecene Phenol Dodecanal 2-Methoxy-4-vinylphenol
Formula
MW
C4H6O3 C5H6O C4H6O2 C5H10O C2H4O2 C3H6O2 C7H8 C4H5N C6H8N2O C6H12O3 C5H4O2 C10H20 C5H6O2 C5H8O3 C10H16 C5H4O2 C5H6O2 C6H6O2 C4H6O2 C4H4O2 C6H12O2 C8H16O3 C9H10O C12H24 C6H6O C12H24O C9H10O2
102.1 82.1 86.1 86.1 116.1 74.1 92.1 67.1 124.1 132.2 96.1 140.3 98.1 116.1 136.2 96.1 98.1 110.1 86.1 84.1 116.2 160.2 134.2 168.3 94.1 184.3 150.2
RT is the Retention time. 393
%Area 723 K
823 K
923 K
1023 K
2.39 2.18 2.96 2.47 19.22 3.57 0.71 2.31 2.11 10.01 9.85 – 3.02 3.46 – 1.33 1.8 1.79 0.54 1.66 – 0.85 0.8 – – 0.5 1.39
11.79 – 3.32 1.3 13.7 1.68 1.15 2.32 1.36 31.16 7.15 – 1.04 1.5 1.57 1.12 0.57 1.01 0.49 1.23 .0.45 2.58 0.36 – – 1.18 –
– 4.44 5.81 1.55 15.82 1.79 5.31 2.06 1.66 12.09 8.79 0.83 – 1.01 0.97 – – – – – 0.58. 2.41 0.67 0.67 0.88 – –
– 4.93 – 0.7 9.02 – 11.02 3.34 – 4.86 5.41 1.95 – – – – – 1.1 – – – 0.63 1.3 2.06 – –
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important raw material in the chemical industry, such as in the manufacture of pharmaceuticals, food, additives, resins and others (Lu et al., 2011). Toluene is also widely used in various industrial processes, such as in the production of paints, varnishes, adhesives and fuel.
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