Biofuel production and kinetics analysis for microwave pyrolysis of Douglas fir sawdust pellet

Journal of Analytical and Applied Pyrolysis 94 (2012) 163–169

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Biofuel production and kinetics analysis for microwave pyrolysis of Douglas fir sawdust pellet Shoujie Ren a , Hanwu Lei a,∗ , Lu Wang a , Quan Bu a , Shulin Chen a , Joan Wu a , James Julson b , Roger Ruan c a

Bioproducts, Sciences and Engineering Laboratory, Department of Biological Systems Engineering, Washington State University, Richland, WA 99354-1671, USA Department of Agricultural and Biological Engineering, South Dakota State University, Brookings, SD 57006, USA c Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN 55108, USA b

a r t i c l e

i n f o

Article history: Received 23 September 2011 Accepted 8 December 2011 Available online 16 December 2011 Keywords: Douglas fir sawdust pellet Biofuels Kinetics Microwave pyrolysis

a b s t r a c t Microwave pyrolysis of Douglas fir sawdust pellet was investigated to determine the effects of reaction temperature and time on the yields of bio-oil, syngas, and charcoal using a central composite design (CCD) and response surface analysis. The research results indicated that thermo-chemical conversion reactions can take place rapidly in large-sized biomass pellet by using microwave pyrolysis. The yields of bio-oil and syngas were increased with the reaction temperature and time. The highest yield of biooils was 57.8% (dry biomass basis) obtained at 471 ◦ C and 15 min. GC/MS analysis indicated that the bio-oils were mainly composed of phenols, guaiacols, furans, ketones/aldehydes, and organic acids. The yield of specific chemicals such as furans and phenolic compounds were highly related to the reaction temperature. The syngas contained high value chemicals, such as carbon monoxide, methane, and short chain hydrocarbons. A third-order reaction mechanism fits well the microwave pyrolysis of Douglas fir pellet with activation energy of 33.5 kJ/mol and a frequency factor of 3.03 s−1 . © 2011 Elsevier B.V. All rights reserved.

1. Introduction The amount of fossil oil reservation is limited as it is not renewable. The increasing demand and reducing amount of fossil oils motivates scientists and researchers to look for alternative energy sources. Biomass is one of important and large amount renewable sources. Unlike the fossil oil, biomass such as crop residues, wood, and energy grasses, are planted and collected annually that can provide a continuous energy supply. Biomass is considered carbon neutral as it helps to reduce the greenhouse gas emission [1]. Biomass pyrolysis is a thermo-chemical process that conducted at 400–600 ◦ C. During pyrolysis biomass is heated and decomposed in the absence of oxygen to produce biofuels, charcoal, and other chemicals [2]. Traditional pyrolysis processes such as fixed and fluidized bed reactors, use heating provided by heated surface, sands, and hot gas [3–5]. Microwave pyrolysis is one of the novel thermo-chemical technologies by heating biomass with microwave irradiation. The major advantage of the microwave heating process over conventional heating methods is the nature of internal fast and uniform heating by microwave irradiation [7,11]. At present microwave pyrolysis is successfully applied to processing plant

∗ Corresponding author. Tel.: +1 509 372 7628; fax: +1 509 372 7690. E-mail address: [email protected] (H. Lei). 0165-2370/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.jaap.2011.12.004

residues, wood, and sewage sludge to produce bio-oil, gas, and charcoal [6–16]. The particle size of biomass feed material, as an important parameter in determining the efficacy of pyrolysis, significantly affects pyrolysis oil and charcoal yields [17]. In conventional pyrolysis system like fluidized bed, very fine feedstock is used to obtain high heating rates and liquid yield because large-sized particles are difficult to agitate and process [17–19]. In the fluidized bed pyrolysis system, large size particles tend to settle to the bottom of the bed where heat transfer and speed of thermal processing are reduced. This has a negative effect on the efficiency of production of bio-oils, which is increased when the particle size is reduced. But in microwave pyrolysis system, previous research results indicate that thermochemical conversion reactions can take place rapidly in relatively large-sized biomass materials [12]. Compared to the conventional fast pyrolysis, microwave pyrolysis of biomass produced bio-oils with low yields. In biomass fast pyrolysis using conventional heating reactors such as fluidized bed, the bio-oil yield was up to 60–70 wt% [3,5]. However, in microwave assisted pyrolysis of biomass the bio-oil yield was generally lower than 30 wt% [10,12,14]. In some reports the microwave absorption materials or catalysts were added to increase the heating rate and bio-oil production during microwave pyrolysis [14,20–22]. The biooil yield can be increased to about 40 wt%, but it is still much lower than that from fluidized bed pyrolysis. It indicates that the high bio-oil yield production is a big challenge in microwave pyrolysis.

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Kinetics analysis is important to understand the mechanism of decomposition and chemical reactions of biomass pyrolysis. Reaction kinetics of biomass pyrolysis is complicated as biomass consists of three main components, hemicelluloses, cellulose and lignin. These three components are decomposed at different temperatures and rates. The hemicelluloses and cellulose can be decomposed relatively fast in low temperatures of 200–350 ◦ C while lignin can be decomposed slowly in a large range of temperatures from 280 to 500 ◦ C [5]. Some wood biomass pyrolysis kinetics models were developed to investigate the decomposition mechanism. These kinetic analyses were usually conducted using small particle size and light weight samples. Most wood biomass decomposition is the first order reaction with high activity energy [26–28]. In larger particle size samples, kinetics models are different [29–31]. The decomposition reaction of large sized samples involves the secondary reaction which should be taken into account in the kinetic model development. Douglas fir is one of the widespread and abundant species in western North America. It is a soft wood and belongs to the coniferous family. The Douglas fir is an important commercial wood; it can be used for structural timbers, lumber, and furniture, which generate large amounts of sawdust and wood residues every year. Wood pellets offer a renewable energy source for power generation and residential heating. Densification of wood residues into pellets has been practiced since several decades ago [32]. In North America there were estimated 800,000 wood pellet stoves in use with a total of about 1,500,000 tons of annual wood pellet consumption in 2008 [33]. Although microwave pyrolysis of wood pellets has been previously reported [34], data on the pyrolysis process optimization and characteristics of products such as bio-oil and syngas, has not been reported. The objective of this study was to investigate microwave pyrolysis of Douglas fir sawdust pellets, to determine the effects of pyrolytic conditions on yields of the bio-oil, syngas, and charcoal, and to establish models to predict the product yields. The compositions of bio-oil and syngas were characterized by GC/MS and GC, respectively. The reaction kinetics of wood pellet microwave pyrolysis was investigated. 2. Materials and methods 2.1. Materials

Table 1 Summary of experimental design and yield results based on biomass with 7% of moisture content. Run#

DF1 DF2 DF3 DF4 DF5 DF6 DF7 DF8 DF9 DF10 DF11 DF12 DF13

Code value

Yield (wt%)

Reaction temperature x1

Reaction time x2

Bio-oil

Syngas

Charcoal

−1 1 −1 1 −1.414 1.414 0 0 0 0 0 0 0

−1 −1 1 1 0 0 −1.414 1.414 0 0 0 0 0

35.0 52.2 38.6 53.8 31.4 53.9 45.2 49.6 49.8 50.2 49.9 48.9 49.0

9.8 13.3 10.6 14.5 7.9 15.0 11.8 12.9 12.9 13.1 12.2 11.9 12.0

55.2 34.4 50.8 31.8 60.7 31.2 42.9 37.6 37.3 36.7 37.9 39.4 39.0

2.3. Experiment design Central composite experimental design (CCD) was used in the optimization of volatile (bio-oil and syngas) and charcoal production [35]. Reaction temperature (X1 , ◦ C) and reaction residence time (X2 , min) were chosen as the independent variables and are shown in Table 1. Reaction residence time was recorded after the desired temperature was reached. Volatile yield (Yi , %) was the dependent output variable. For statistical calculations, the variables Xi were coded as xi according to Eq. 2: xi =

Xi − X0 X

(2)

where xi is dimensionless, Xi is the real value of an independent variable, X0 is real value of the independent variable at the center point, and X is step change. A 22 -factorial CCD, with 4 axial points (˛ = 1.414) and 5 replications at the center points (n0 = 5) leading to a total number of 13 experiments, was employed (Table 1) for the optimization of the conditions of pyrolysis process. The second-degree polynomials (Eq. (3)) were calculated with the statistical package (SAS Institute Inc., USA) to estimate the response of the dependent variable.

Douglas fir sawdust pellets were purchased from Bear Mountain Forest Products Inc. (USA). The pellets were made from 100% natural Douglas fir wood sawdust with a heating value of 19.4 MJ/kg and a water content of 7 wt%. The pellets had an average diameter of 6 mm and an average length of 10 mm.

where Yi is predicted response, X1 and X2 , are independent variables, b0 is the offset term, b1 and b2 are linear effects, b11 and b22 are squared effects, and b21 are interaction terms.

2.2. Microwave apparatus

2.4. GC/MS analysis for bio-oil

A Sineo MAS-II batch microwave oven (Shanghai, China) with a rated power of 1000 W was used at the 700 W power setting. 400 g Douglas fir pellets were placed in a 1-l quartz flask inside the microwave oven. The details of experimental setting can be found in previous report [12]. The reaction temperature of biomass was monitored by an infrared sensor through a closed end quartz tube which is penetrated to the central of the reaction flask. During pyrolysis the heavier volatiles were condensed into liquids as biooils and the lighter volatiles escaped as syngases at the end of the condensers where they were either burned or collected for analysis. Char was left in the quartz flask. The weight of syngas product was calculated using following equation:

Chemical compositions of the bio-oil were determined using an Agilent 7890A GC/MS with a DB-5 capillary column. The GC was programmed at 45 ◦ C for 3 min and then increased at 10 ◦ C/min to 300 ◦ C and finally held isothermal for 10 min. The injector temperature was 300 ◦ C and the injection size was 1 ␮L. The flow rate of the carrier gas (helium) was 0.6 mL/min. The ion source temperature was 230 ◦ C for the mass selective detector. The compounds were identified by comparing the spectral data with the NIST Mass Spectral library.

weight of biogas = initial wood pellet mass − bio-oil mass − biochar mass

(1)

Yi = b0 + b1 X1 + b2 X2 + b11 X12 + b21 X2 X1 + b22 X22

(3)

2.5. GC analysis for syngas The chemical compositions of syngas were determined by a Carle 400 gas chromatography (GC) system with a thermal conductivity detector (TCD).

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2.6. Douglas fir pellet pyrolysis kinetics A kinetic scheme to model thermal decomposition of biomass can be schematized as: Douglas fir pellet → bio-oil + syngas + charcoal

(4)

where the reaction rate is a function of the remaining raw material and follows an Arrhenius law dependent on temperature [36]. The rate of decomposition can be expressed by the following equation:



 E

d˛ = A exp − RT dt

(1 − ˛)n

(5)

where A is frequency or pre-exponential factor of the pyrolysis process (s−1 ), E is apparent activation energy (J/mol), T is temperature (K), R is universal gas constant, 8.3145 (J/mol K), n is the order of reaction, t is time (s), and the fractional reaction ˛ is defined in terms of the change in mass of Douglas fir pellet samples: ˛=

X0 −X X0 −Xf

(6)

In order to determine the values of kinetic parameters, the Coats–Redfern method was used to solve Eq. (5). 2.6.1. Coats–Redfern method For a constant heating rate ˇ (ˇ = dT/dt), the following expression can be obtained from Eq. (5): A d˛ = e−E/RT (1 − ˛)n dT ˇ

(7)

Re-arranging and integrating Eq. (7) leads to:



˛

d˛ (1 − ˛)

0

n

=

A ˇ



T

e−E/RT dT

(8)

0

Integrating both sides gives:



ART 2 −E/RT 1 − (1 − ˛)1−n = e 1−n ˇE

1−

2RT E

 (9)

Converting Eq. (9) into a logarithmic expression we have:



ln

1 1 − (1 − ˛)1−n 1−n T2



= ln

 AR ˇE

−

2RT E



−

E 1 · R T

(10)

Assuming 1 − (2RT/E) ≈ 1, Eq. (10) becomes:



ln

1 1 − (1 − ˛)1−n 1−n T2



= ln

AR E 1 − · , R T ˇE

n= / 1

(11)

If n = 1, Eq. (10) becomes:

ln

 − ln(1 − ˛)  T2

= ln

AR E 1 − · , R T ˇE

n=1

(12)

Thus, a plot of ln((1/T2 )((1 − (1 − ˛)1−n )/(1 − n)) versus (1/T) when n = / 1 or ln((− ln(1 − ˛))/T2 ) versus (1/T) when n = 1 results in a straight line with slope = −E/R and intercept = ln(AR/ˇE). 3. Results and discussion 3.1. Response surface analysis The detailed experimental design and observed results are shown in Table 1. Thirteen experiments were performed using different combinations of the variables as per the CCD. The suitable levels for these parameters were also determined using statistical CCD. Previous research indicated that the most important physical factors that affected bio-oil and syngas production from corn stover microwave pyrolysis were the reaction time and reaction

165

temperature [12]. In this research, these two parameters have significant effects on microwave pyrolysis of Douglas fir pellets. Using the results of the experiments obtained the following second–order polynomial equations for the bio-oil yield (Eq. (13)), syngas yield (Eq. (14)), and charcoal yield (Eq. (15)) as a function of reaction temperature (X1 , ◦ C) and reaction time (X2 , min): Y = −250.01 + 1.27X1 + 1.59X2 − 0.0014X12 − 0.043X22

(13)

Y = −36.29 + 0.19X1 + 0.086X2 − 0.0019X12

(14)

Y = −385.04 − 1.45X1 − 1.67X2 + 0.0016X12 + 0.044X22

(15)

The model terms X12 (P-value = 0.079, 0.36) were insignificant (Pvalues > 0.05) when Eq. (3) was used to fit the data for bio-oil and charcoal. The model term X12 (P-value = 0.78) and X22 (Pvalue = 0.97) were not significant (P-value > 0.05) when Eq. (3) was used to fit the data for syngas. Eq. (3) was reduced by using backward statistical analysis, and Eqs. (13)–(15) were obtained with its significant terms (P-value < 0.0001). The correlation coefficients of determination, R2 was 1.00, 0.95, and 0.99 respectively for bio-oil, syngas, and charcoal, implying that the reduced quadratic regression models can be used to explain the pyrolysis reaction, and the biofuel yield variations were attributed to the independent variables of reaction time, reaction temperature, and their squared effects. Hence, these models can adequately represent the experimental data and can be used to predict the production yields for biomass microwave pyrolysis processes. The volatile (bio-oil and syngas) and bio-oil yields increased with increasing reaction temperature and time. The volatile yields were found to range from 39.3 to 68.8 wt% depending on pyrolysis conditions, while the yield of bio-oils was from 33.8 to 57.8 wt% based on dry biomass. The syngas yield ranged from 7.9 to 15.0 wt% and increased with the reaction temperature. The charcoal yield varied from 31.2 to 60.7 wt%. Fig. 1 represents the response contour and surface plots for the pyrolysis conditions of product yields. The water contents of bio-oils were determined by Mettler Toledo V30 volumetric Karl–Fisher Titrator. The water contents of bio-oils ranged from 36.8 to 52.9%, 17.2 to 24.7 wt% based on dry biomass. Liquid chemicals in bio-oils ranged from 16.1 to 34.4 wt% based on dry biomass. The highest yield of liquid chemicals in biooil was observed at the pyrolysis condition of 450 ◦ C and 20 min. The yield distributions of water, liquid chemicals, syngas and charcoal are shown in Fig. 2. Biomass microwave pyrolysis produced low yield bio-oil in previous reports. 22.6 wt% bio-oil yield was obtained from rice straw microwave pyrolysis at temperature of 407 ◦ C with power input of 300 W [23]. 7.9–9.2 wt% bio-oil yield on dry basis was obtained from coffee hulls microwave pyrolysis at the temperature ranged from 500 ◦ C to 1000 ◦ C with the reaction time of 15 min [8]. 31.5 wt% bio-oil yield was obtained from wood block microwave pyrolysis with the power consumption of 1.11 kWh kg−1 and reaction time of 11 min [10]. To increase the liquid yield of microwave pyrolysis, microwave absorption was added in the microwave pyrolysis. About 25 wt% bio-oil yield was obtained from oil palm biomass with char absorber microwave pyrolysis with the power input of 450 W and reaction time of 25 min [14]. About 34 wt% bio-oil yield was obtained from wood sawdust with ionic liquid microwave pyrolysis [22]. But in fluidized bed about 60–70% bio-oil yield on dry basis was obtained [3,5]. Compared to the fluidized bed, microwave pyrolysis produces much lower liquid yield. In this research the highest bio-oil was 57.8 wt% based on dry biomass obtained at the optimization conditions with the reaction temperature of 471 ◦ C and reaction time of 15 min. This result indicates that Douglas fir pellet microwave pyrolysis can produce the high yield bio-oil close to conventional pyrolysis in optimum conditions [3,5,24,25,37].

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Fig. 3. Chemical composition distribution of bio-oil from microwave pyrolysis.

3.2. GC/MS analysis for bio-oil

Fig. 1. Response surface and contour line of bio-oil yields (a), syngas yield (b), and charcoal yield (c) as a function of reaction time and reaction temperature.

Product yields, wt% on biomass

100 90 80 70 60 50 40 30 20 10 0 DF1

DF2

DF3 Charcoal

DF4 Syngas

DF6

DF7

Liquid Chemicals

DF5

Water

DF8

Fig. 2. Product yield distribution from microwave pyrolysis.

DF9

To further understand the chemical reactions in microwave pyrolysis, we carried out GC/MS analysis to determine the composition of bio-oils. The main ingredients of bio-oils were guaiacols, phenols, furans, ketones/aldehydes, and organic acids (Fig. 3). The guaiacols accounted for the largest amounts in the bio-oil which represented 49.0–72.7% in area. The guaiacols were mainly made up of 2-methoxy-4-methylphenol, 2-methoxyphenol, 4ethyl-2-methoxy-phenol and phenol, 2-methoxy-4-(1-propenyl)-, (E)- which represented 14.0–19.8%, 5.3–12.0%, 5.0–12.8% and 5.5–14.2% of the bio-oil in area, respectively. The phenols in the bio-oils ranged from 3.6 to 11.0% in area. The phenols were mainly made up of 1,2-benzenediol, phenol, 2-methyl- and phenol which represented 1.9–5.0%, 0.1–1.4% and 0.2–0.9% in area, respectively. The furans in the bio-oils ranged from 10.1–17.7% in area. The furans were primarily composed of furfural, tetrahydro-2,5dimethoxy-furan, ␤-methoxy-(S)-2-furanethanol and, 5-methyl2-furancarboxaldehyde. Furfural represented 2.8–6.6% of the bio-oil in area. The organic acids in the bio-oil ranged 0.3–6.2% in area. Levoglucosan sugars had very low yield except in run# DF7 which was processed in the condition of 400 ◦ C and 7.9 min. The reason of this is that the levoglucosan can be decomposed to gas and volatiles at high temperature and long reaction residence time [38]. Douglas fir is mainly composed of three components, hemicelluloses, cellulose and lignin with the compositions of 21%, 44% and 32%, respectively [39]. The reaction mechanism and characteristics of bio-oil for three components decomposition were widely investigated in previous research [40–49,54]. Hemicelluloses can be decomposed to acetic acid and furfural [40–43] and cellulose can be decomposed to ketones, aldehydes, and furans [44,45]. The yields of chemicals derived from hemicelluloses and cellulose decomposition are increased with the increase of reaction temperature and time [44]. Our results are in good agreement with the results from previous reports. The total yield of organic acid, ketones, aldehydes, and furans were increase from 17.5 to 30.9% in area with the temperature and reaction time increasing. The maximum yield was obtained at the temperature 400 ◦ C and reaction time 22 min. Phenolic compounds mainly from lignin decomposition are wide useful chemicals in pharmacy, synthesis and food industry [47,50,51]. Therefore, some researchers focus on in lignin pyrolysis to produce phenolic compounds [46–49,52]. In this research we produced very

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Table 2 Optimum conditions and maximum yield of specific chemicals in furans and phenolics. Category

Compound name

Reaction temperature ( ◦ C)

Reaction time (min)

Yields (% in area)

Furans

Furfural 2-Furancarboxaldehyde, 5-methyl2-Furanethanol, ␤-methoxy-(S)Furan, tetrahydro-2,5-dimethoxyTotal

329 350 400 470

15 20 22 15

6.56 3.64 3.46 3.27 16.93

Phenolic chemicals

Phenol, 2-methoxy-3-(2-propenyl)Phenol, 2-methoxy-4-(1-propenyl)Phenol, 2-methoxy-4-(1-propenyl)-, (E)Phenol, 4-ethyl-2-methoxyPhenol, 2-methoxy-4-propylPhenol, 2-methoxy-4-methylPhenol, 2-methoxy2-Methoxy-4-vinylphenol 1,2-Benzenediol Total

329 329 350 350 400 400 450 471 471

15 15 10 20 15 15 10 15 15

4.47 3.34 14.17 12.79 3.47 19.83 11.98 5.41 5.03 80.49

high yield of phenolic compounds, from 60 to 78% in area in which guaiacols contributed about 49 to 72% in area. The relatively high yields of phenolic compounds were obtained at temperatures of 350 ◦ C and 450 ◦ C with reaction time of 10 min. The chemical ingredients of furans and phenolic compounds were further analyzed as they were large amount chemicals in bio-oil which represented up to 62.6–84.3% in area. In furans the large amount chemicals were furfural and 2-furancarboxaldehyde, 5-methyl- which decreased with the increase of reaction temperature and increased with the increase of reaction time. The amounts of other two main furans, ␤-methoxy-(S)-2-furanethanol and tetrahydro-2,5-dimethoxy-furan, increased with the reaction temperature and time. It was found that the yield of guaiacols first increased and then decrease with the increase of reaction time at the same temperature while the yield of phenols were not significantly changed. The guaiacols were mainly made up of eight specific chemicals, phenol, 2-methoxy-, phenol, 2-methoxy-4-methyl-, phenol, 4-ethyl-2-methoxy-, phenol, 2-methoxy-4-(1-propenyl), (E)-2-methoxy-4-vinylphenol, phenol, 2-methoxy-4-propyl-, phenol, 2-methoxy-3-(2-propenyl)-, and phenol, 2-methoxy-4-(1propenyl)-. The first four chemicals had high percentage ranged from 5% to 20% in area, and the last four chemicals had the percentage ranged from 1% to 5% in area. The yield of 2-methoxy-phenol, 2-methoxy-4-vinylphenol, and 2-methoxy-4-propyl-phenol, were very stable in different reaction temperature. The yield of 4ethyl-2-methoxy-phenol, 2-methoxy-3-(2-propenyl)-phenol, and 2-methoxy-4-(1-propenyl)-phenol, decreased with the increasing reaction temperature. However, the yield of 2-methoxy-4-methylphenol, increased with the increasing reaction temperature in this research. The yield of 2-methoxy-4-methyl-phenol was also related to the reaction time. At temperature 400 ◦ C, the yield significantly increased from 7.9 to 15 min and then significantly decreased from 15 min to 22 min. The maximum yield of 19.8% in area was obtained at condition of 400 ◦ C and 15 min. Furthermore, it was found that the yield of 1,2-benzenediol increased with the increase of reaction temperature and time. This result indicated that the second reaction occurred in which the guaiacols were converted to 1,2-benzenediol which is in a good agreement with the previous reports [38,53]. The optimum conditions and maximum yield for main furans and phenolic compounds are shown in Table 2. These results indicated that the selectivity of specific compounds can be improved through controlling the reaction temperature and time. The proposed reaction pathway of Douglas fir pellet microwave pyrolysis is shown in Fig. 4. We proposed that hemicellulose and cellulose decomposition mainly include two steps. The first step is that hemicelluloses and cellulose are depolymerized and dehydrated to furfural and 2-furancarboxaldehyde at low temperature

ranged from 329 to 350 ◦ C. The second step is that C O linkage is broken and recombinated to ␤-methoxy-(S)-2-furanethanol and tetrahydro-2,5-dimethoxy-furan at high reaction temperature ranged from 400 to 471 ◦ C. Compared to hemicelluloses and cellulose, lignin decomposition involving depolymerization, dehydration, cracking and hydrogenation is much complex. At low temperatures from 329 to 350 ◦ C, lignin is primarily depolymerized and dehydrated to produce propenyl-guaiacols. The propenylguaiacols are further hydrogenated to propyl-guaiacols at the temperature 350–400 ◦ C. Cracking of lignin and guaiacols occurred at temperatures from 350 to 471 ◦ C and the positions of C C bond broken are highly related to the temperature. The cracking of C␤ C␥ bond occurs at 350 ◦ C, followed by the cracking of C␣ C␤ bound at 400 ◦ C and C4 C␣ bond at 450 ◦ C. The cleavage of C OCH3 occurs at the temperature 471 ◦ C. 3.3. GC analysis for syngas Syngas was one of the main products of Douglas fir pellet pyrolysis. The yield of syngas ranged from 7.9 to 15.0 wt%. Knowing the compositions of the syngas will help better understand the reaction of microwave pyrolysis and explore its potential utilization. The uncondensed gas was mainly composed of CO, CH4 , CO2 , and short-chain hydrocarbons. The amounts of these chemicals in the gas varied with reaction conditions. Carbon monoxide is the largest amount of the chemicals in the syngases from the Douglas fir pellet pyrolysis. The highest content of carbon monoxide was around 64% (v/v) of the total amount of gas at the conditions of 329 ◦ C and 15 min. The content of carbon dioxide was about 25% (v/v). The contents of methane and short chain hydrocarbons were relatively low, which contributed to about 1.5–7.7% (v/v) and 0.4–3.5% (v/v) of the syngases, respectively. There was small amount of hydrogen detected in the gas products of Douglas fir pellet. The reason is that the hydrogen might be involved in the secondary reaction such as hydrogenation during pyrolysis. The syngas had up to 70% (v/v) of usable gas components that can be burned or utilized as a syngas. Therefore, the gas products from microwave pyrolysis of Douglas fir pellets have high values for potential utilizations. 3.4. Kinetic evaluation Douglas fir sawdust is a complex biomass solid which is mainly composed of hemicelluloses, cellulose and lignin [5,39]. During the microwave pyrolysis, Douglas fir sawdust pellet decomposed and released volatiles with complex reactions. Products of microwave pyrolysis of Douglas fir pellet were obtained in three fractions, bio-oil, gas and bio-char which proportions depended on the process conditions. Parameters like temperature or residence time

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Fig. 4. Proposed reaction pathway of Douglas fir pellet pyrolysis.

influence the products through the kinetics of the reaction and knowledge of the kinetics is a key factor to predicting product yields. The Coats–Fedfern method is the very common method for investigating reaction kinetics and determining the activity energy for biomass decomposition by thermal process [55–57]. From our experiment data, the kinetic parameters, including activation energy (E) and frequency factors (A), were estimated using Coats–Fedfern method and listed in Table 3. A third-order reaction mechanism fits well the microwave pyrolysis of Douglas fir pellet with R2 = 0.85. It indicates that the rate of decomposition is proportional to the cube of the mass of Douglas fir pellet by microwave irradiation. The starting rate of pellet decomposition is very fast in microwave pyrolysis. A constant heating rate was used with activation energy of 33.5 kJ/mol for Douglas fir pellet and a frequency factor of 3.03 s−1 . The activation energy in a third order-reaction model gives a good approximation of the temperature range where the reaction takes place at the constant heating rate of pryolysis process. The good fit of the pyrolysis path was carried out in accord with the temperature and time. In regard to the evolution of the total volatiles with temperature and heating rate, the model was able to describe properly the experimental data.

Table 3 Kinetic parameters for the microwave pyrolysis of Douglas fir sawdust pellet by Coats–Redfern method. Raw materials

Reaction order n

Activation energy E (kJ/mol)

Frequency factor A (s−1 )

R2

Douglas fir pellet

1 2 3

16.5 21.0 33.5

15.27 1.42 3.03

0.81 0.79 0.85

The kinetics analysis of biomass decomposition in large size biomass showed that the secondary reactions occurred [29–31]. Grieco et al. [29] reported that the secondary reactions occurred in wood pellet pyrolysis with the activation energy of 45 kJ/mol. Willer and Brunner [30] noted that the secondary reactions occurred in large size biomass pyrolysis and the activity energies of both wood and wood component pyrolysis were in the range of 31–67 kJ/kg. The secondary reaction also occurred in the microwave pyrolysis for Douglas fir pellet as guaiacols were cracked to phenols at the high temperature and long reaction time. The kinetic model developed in this study was a global model with the low activity energy of 33.5 kJ/kg which matches well to the previous reports.

4. Conclusions In this study, the microwave pyrolysis of Douglas fir sawdust pellet was investigated and the effects of reaction temperature and time on the yields of products (bio-oil, syngas, and charcoal) were determined using the central composite design (CCD) and response surface analysis. The fast pyrolysis of Douglas fir pellet was achieved by microwave heating with high bio-oil yields. The yields of bio-oils were 33.8–57.8 wt% based on dry biomass basis. The yields of co-products, syngas and charcoal, were 7.9–15.0 wt%, and 31.2–60.7 wt%, respectively. The bio-oil and syngas yields increased with the increase of reaction temperature and time. The highest yields of bio-oil and syngas were obtained at 471 ◦ C and 15 min. Second-order polynomial models were obtained to predict the yields of products with high accuracy. The bio-oil was mainly composed of aromatics phenols, guaiacols, furans, ketones/aldehydes, and organic acids. The phenols and guaiacols accounted for the largest amount of chemicals in the biooil which represented 59.7–78.6% in area depending on different

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