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Optimization of bio-oil production using response surface methodology and formation of polycyclic aromatic hydrocarbons (PAHs) at elevated pressures
Fuel Processing Technology 142 (2016) 279–286
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Fuel Processing Technology journal homepage: www.elsevier.com/locate/fuproc
Research article
Optimization of bio-oil production using response surface methodology and formation of polycyclic aromatic hydrocarbons (PAHs) at elevated pressures Funda Ates a,⁎, Nihal Erginel b a b
Faculty of Engineering, Department of Chemical Engineering, Anadolu University, Eskisehir, Turkey Faculty of Engineering, Department of Industrial Engineering, Anadolu University, Eskisehir, Turkey
a r t i c l e
i n f o
Article history: Received 10 July 2015 Received in revised form 28 September 2015 Accepted 19 October 2015 Available online xxxx Keywords: Pressure Pyrolysis Response surface methodology (RSM) Polycyclic aromatic hydrocarbons (PAHs)
a b s t r a c t This paper aims at the optimization of bio-oil yield obtained from poplar sawdust pyrolysis. A response surface methodology was carried out to optimize the experimental conditions. The factors investigated were temperature, pressure and heating rate. Five levels, which were low level, upper level, center point and two axillar points, were considered for each of the factors. Statistical analysis shows that these factors significantly affect bio-oil yield. According to the model, bio-oil yield is maximized when the following conditions are utilized; a pyrolysis temperature of 528.44 °C, pressure of 1 bar, and a heating rate of 750 °C/min. Bio-oil yield decreased with increased pressure, and the maximum bio-oil yield obtained was 30.45%. The physical properties of char and chemical compositions of the produced bio-oil were then characterized. These included SEM (Scanning Electron Microscope) and GC/MS (Gas chromatography/mass spectrometry) characterization. The formation of polycyclic aromatic hydrocarbons (PAHs) from the pyrolysis of poplar sawdust was observed, taking into account the influence of pressure. Pressurized pyrolysis of poplar sawdust generated a tar range of 2–4 ring PAHs. PAHs were the dominant products at 21 and 41 bars. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Biomass can be converted to useful products by two major technologies: biochemical and thermochemical. The most frequently used processes in biochemical technology are fermentation and anaerobic digestion. Fermentation is used to produce alcohol fuels, while methane gas is produced by anaerobic digestion. Among thermochemical conversion processes, such as combustion, gasification, liquefaction or pyrolysis, a liquid product is produced only by liquefaction and pyrolysis. Solid and gaseous products, as well as liquid products, can be produced in pyrolysis compared to liquefaction. Liquefaction produces only small amounts of solid residue and gas, both considered by-products of the process. Percentage distribution and composition of pyrolysis products mainly depend on pyrolysis temperature, heating rate, particle size, catalyst, residence time, type of biomass used, and pressure [1–4]. One of the most significant parameters in pyrolysis is temperature, because it affects the amount and composition of the volatile component. High heating rates have the ability to produce a high yield of liquid product. Rapid heating provides efficient heat and mass transfer rates. Pressure affects the mass transfer of releasing ⁎ Corresponding author. E-mail address: [email protected] (F. Ates).
http://dx.doi.org/10.1016/j.fuproc.2015.10.026 0378-3820/© 2015 Elsevier B.V. All rights reserved.
volatiles [5]. Residence time is also a critical parameter for pyrolysis, because short residence times prevent secondary reactions. If the residence time is sufficiently high, the resulting primary products will stay longer in the reaction atmosphere. Therefore, these primary products enter reactions, such as cracking and repolymerization, to form secondary and tertiary products. However, which of these secondary reactions will be dominant depends on the reaction parameters and conditions. The major chemical composition of bio-oil is described as phenols, carbonyl compounds, carboxylic acids, sugars, aliphatics, aromatics, alcohols, furfurals and furans. Evans and Milne classify pyrolysis products as primary, secondary, and tertiary [6,7]. Primary products can be characterized by cellulose-derived products, such as levoglucosan, hydroxyacetaldehyde and furfurals, hemicellulosederived products, and lignin-derived methoxyphenols. At the secondary pyrolysis reactions stage, the primary pyrolysis products occur from decomposition of raw material reactions and may undergo additional cracking reactions to form more volatile products, or they may undergo repolymerization reactions to form high molecular size products. Secondary products can be characterized as phenols, and olefins. These components have been determined by a number of studies in the literature [8,9]. Polycyclic aromatic hydrocarbons (PAHs) are classified as tertiary products, such as naphthalene, acenaphthylene, anthracene/phenanthrene, and pyrene. The most effective reaction
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Table 1 Proximate and ultimate analysis of biomass sample. Proximate analysis (wt.%)
Moisture Volatile matter Fixed carbon Ash C H N S Oa
Ultimate analysis (wt.%)
a
7.7 74.8 13.8 3.7 49.8 6.3 0.5 0.4 42.9
By difference.
conditions that trigger secondary reactions are temperature, pressure and residence time. PAHs are a large group of organic compounds that have two or more aromatic rings. As pollutants, PAHs are of concern because certain compounds have been identified as carcinogenic, mutagenic, and teratogenic. Besides, PAH-containing oils are added to the rubber, typically together with fillers, to achieve the desired elasticity. They are used in some brittle synthetic products such as PVC to make soft and flexible. Also they are used in car tires. They are inexpensive and make the products purchasable. Besides, we use PAH containing products such as tool and bicycle handles, some shoes, or sports items in daily life. There have been numerous studies on the influence of pyrolysis parameters on pyrolysis product yields in the literature. Although, some researchers have evaluated the optimization of pyrolysis conditions using response surface methodology [2,3,10–12], elevated pressure, heating rate and temperature have not yet been evaluated together for bio-oil yield using response surface methodology. The Response Surface Method (RSM) is a useful statistical experimental design and analysis tool. The RSM is used to design experiments in which factors and levels are determined and also in which the number and order of experiments are defined. The order of experiments should be random to disperse the effect of environmental noise factors. After handling the response of the experiments, the results are obtained by analyzing the response according to the RSM. A mathematical model is set via RSM by considering both linear and nonlinear relationships between independent variables, namely factors and response. If interactions affect response, the interaction term can be modeled in a mathematical model in the RSM. In addition, the RSM allows for optimization of the response. A response surface graph and a contours plot help visualize the shape of a response surface [13]. Bio-oil can be produced from a variety agricultural waste, forest waste, industrial waste and co-products and energy crops. Poplar sawdust is a main forest waste. For instance, bio-oil is produced from forest waste, such as sawdust, bark or shavings in Europe and North America [9]. The poplar likes wetlands, and is a tree that grows throughout Turkey. Nowadays, poplar wood is widely-used in the paper and inexpensive furniture timber industries. In this context, the aim of the present work is to optimize the influence of temperature, pressure and heating rate on the yield of the bio-oil product. The RSM was selected for the construction of nonlinear mathematical functions that contain not only linear relationships, but also quadratic forms and interactions of factors. In addition, changes in the resulting bio-oil composition with elevated pressure are also determined.
Fig. 1. Pressurized pyrolysis set-up.
2. Materials and methods 2.1. Biomass and TG analysis In the experimental study, poplar sawdust was used as a biomass sample in a fixed-bed reactor. Prior to the experiments, the biomass was dried, ground in a high speed rotary cutting mill to give particle size fractions of 0.425–1.25 mm. Table 1 shows the main characteristics of the pyrolyzed biomass. Ultimate analyses were performed on sawdust to determine its elemental composition. A Carlo Erba (EA 1108) elemental analyzer was used to determine the weight fractions of carbon, hydrogen, sulfur and nitrogen, with the weight fraction of oxygen being calculated by difference. A thermogravimetric analysis was carried out using a Linseis Thermowaage L81 thermo-gravimetric analyzer, coupled with a differential thermal analyzer (DTA), with high purity nitrogen as a carrier gas at a flow rate of 50 mL/min. About 25 mg material was placed in an alumina crucible and heated from room temperature to 1000 °C at 10 °C/min. 2.2. Response surface methodology (RSM) Response Surface Methodology (RSM) is a technique for modeling and analyzing the relationship between independent variables and response (yield), both as linear or nonlinear forms to determine an
Table 2 Factors and levels in experiments. Factors
Axillar (−2)
Low level (−1)
Center point (0)
Upper level (+1)
Axillar (+2)
Temperature (°C) Pressure (bar) Heating rate (°C/min)
400 1 150
450 11 300
500 21 450
550 31 600
600 41 750
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Fig. 2. DTG and TG curves of poplar sawdust.
optimum response. The linear and quadratic model with interactions can be seen in the following equation [13]:
y ¼ β0 þ
k X i¼1
β i xi þ
k X
βii x2i þ
XX
i¼1
βij xi x j þ ε
ib j
where y expresses response or yield, xis represent independent variables, β0 indicates the intercept constant, βis show the coefficients of linear terms, βiis represent the coefficients of quadratic terms, βijs show the coefficients of interaction terms, ε indicates experimental error and k represents the number of independent variables. Central Composite Design (CCD) in RSM is the most popular class of design used for fitting a second order model, especially in the chemical process [13]. In this study, three factors were considered in experiments with two levels, two axillar points with distance two (α = ±2), and six central points. In these experiments, handled factors and their levels have been given in Table 2. Twenty experiments were conducted in random order and the bio-oil yield was handled with the reactor.
the desired pressure within the reactor. When the desired temperature is reached, the reactor system is closed down for 5 min. After completion of the reaction, the valve is opened slowly and volatile products are completely discharged from the reactor. The volatile products passed through three traps, which were placed in an ice-bath. Condensable products were cooled and condensed by mean of ice-cooled traps and recovered with DCM (dichloromethane) washing. The aqueous phase was separated (condensed and non-condensed) from organic phase with a separating funnel. The solvent was removed in a rotary evaporator and residual was weighed as bio-oil. The solid product (char) remaining in the reactor was weighed. The gas yield was calculated by taking the difference. A detailed description of the reactor and pyrolysis experiments can be found elsewhere [5]. The feedstock was pyrolyzed between pressures of 1–41 bars and between temperatures of 400–600 °C, at a heating rate of between 150 and 750 °C/min. All the yields were calculated on a dry and ash-free basis, also each experiment was repeated for three times at each experimental condition and reproducibility of the experimental data was calculated to be within ±2%.
2.3. Experimental pyrolysis set-up 2.4. Product analyses A schematic diagram of the unit is represented in Fig. 1. The process set up involves steel wool in a thin tubular reactor for the placement of 3 g of sample raw material, a thermocouple inserted into the reactor from the top, fixing flanges at the top and bottom of the reactor for sealing with a valve placed at the lower end. Pressure was provided by utilizing nitrogen gas. The valve was kept closed in order to provide
Analyses have been carried out at a constant level of heating rate (750 °C/min) and pyrolysis temperature (500 °C) to analyze the influence of pressure on bio-oil composition. The pressure levels of 1, 21 and 41 bars were selected for the analysis of bio-oil components. A Hewlett-Packard HP 7890 gas chromatograph coupled to a HP 5975 Table 4 ANOVA table.
Table 3 Estimated regression coefficients for yield using data coded units. Term
Coef
SE coef
T
p-Value
Constant Temperature Pressure Heating rate Temperature ∗ temperature S = 0.9399
27.2985 1.1250 −0.9875 0.4250 −0.9794 R-Sq = 83.0%
0.2549 0.2350 0.2350 0.2350 0.1802 R-Sq(adj) = 78.5%
107.108 4.788 −4.203 1.809 −5.435
0.000 0.000 0.001 0.091 0.000
Source
DF
Seq SS
Adj SS
Adj MS
F
p-Value
Regression Linear Square Residual error Lack-of-fit Pure error Total
4 3 1 15 10 5 19
64.8340 38.7425 26.0915 13.2515 10.2381 3.0133 78.0855
64.8340 38.7425 26.0915 13.2515 10.2381 3.0133
16.2085 12.9142 26.0915 0.8834 1.0238 0.6027
18.35 14.62 29.53
0.000 0.000 0.000
1.70
0.291
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quadruple detector (GC/MS) was used for bio-oil analysis. A detailed description of this method can be found elsewhere [5]. The physical features of chars were recorded using a Zeiss EVO 50 Scanning Electron Microscope. Samples were mounted on an aluminum stub using carbon bands coated with a thin layer of gold–palladium in an argon atmosphere using an Agar Sputter Coater. 3. Results and discussion 3.1. Biomass analyses Typically, two or three peaks appear in the thermogravimetric analyses of lignocellulosic materials. These peaks can be assigned to each of the biomass components, such as hemicellulose, cellulose and lignin [14, 15]. From the DTG pyrolysis profile, as seen in Fig. 2, the first peak showing at 103 °C for poplar sawdust was obviously responsible for the moisture content in the raw material. The flat line observed after this peak indicates that most of the water was removed [16]. It can be seen that maximum thermal degradation occurs at 331 °C. The peak temperature of poplar sawdust is determined to be as much as Miscanthus straw (331 °C) and cotton stalk (334 °C) [17], but it is somewhat lower than other biomasses, such as sugarcane bagasse (355 °C) [17], wheat straw (372 °C), switch grass (392 °C), beech wood (382 °C) [18] and hornbeam sawdust (348 °C) [19]. The main thermal degradation reactions form and the TG curve sharply drops from this point. Afterwards, slight devolatilization continues and the TG curve is relatively flat. The total weight loss according to TGA is 76% at 600 °C.
3.2. Optimization of pressure, temperature, and heating rate on bio-oil yield using response surface methodology The results were analyzed with RSM using MINITAB 14.12.0 software. The use of partitioning to formally test for no differences in treatment means requires that certain assumptions need to be satisfied. Specifically, these assumptions are that the observations are adequately described by the model and that errors are normally and independently distributed with a mean of zero and a constant, but unknown, variance σ 2. If these assumptions are valid, the analysis of the variance procedure is an exact test of the hypothesis of no difference in treatment means [13]. According to the analyzing on residuals, three assumptions are valid at this study. The effective factors and their coefficients of the second-order regression model, for maximum bio-oil yield obtained from pressurized pyrolysis of poplar sawdust, are given in Table 3. In addition, a mathematical model is given in Eq. (1). Also the ANOVA table, shown in Table 4, indicates that the second order regression model is appropriate for the yield. Models with p-value of less than 0.10 are defined as significant fits. The second-order regression model is:
^ ¼ −81:094 þ 0:4143x1 −0:0988x2 þ 0:0028x3 −0:000392x21 y
ð1Þ
where, x1 represents temperature, x2 shows pressure, x3 indicates ^ is the percentage yield of bioheating rate independent variables, and y oil. According to the results, the mathematical model consists of effective terms that are temperature, pressure, heating rate and temperature2. The interaction terms, and square terms of pressure and heating rate are not significant on yield. As a result, these terms were extracted from the model. The R2(adj) of the mathematical model in Table 3 refers to the coefficient of determination and gives the amount of variability in the data explained by the mathematical model. In this mathematical model, R2(adj) is equal to 78.5% and this value is acceptable.
Fig. 3. Surface plot of bio-oil yield and pressure and temperature (a), bio-oil yield and heating rate and pressure (b), and bio-oil yield and heating rate and temperature (c).
There is a quadratic relationship between bio-oil yield and temperature. A three dimensional response surface plot of yield versus pressure and temperature can be seen in Fig. 3a. The linear relationship between bio-oil yield, heating rate and pressure can be seen in Fig. 3b. In addition, the surface plot of bio-oil yield versus heating rate and temperature is given in Fig. 3c. Because of the nonlinear mathematical model, further calculations were conducted to determine whether the stationary point is at a minimum or maximum value for temperature. ^ dy ¼ 0:4143−2ð0:000392Þx1 ¼ 0 dx1 x1 ¼ 528:44
ð2Þ
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^ dy ¼ −0:000784 b 0: dx21
ð3Þ
The stationary point of x1 =528.44 (°C) was defined as a maximum value for temperature (Eqs. (2) and (3)). For maximum bio-oil yield, pressure should be 1 bar, and heating rate should be 750 °C/min. In this case, the maximum bio-oil yield is 30.45%. Increasing pressure led to a decrease of bio-oil yield. A pressure gradient between the inside of the raw materials and the external environment is evident, together with the increase in pressure [4]. Therefore, volatiles forming with increasing temperatures are imprisoned in residual char. A decrease in bio-oil yield with increasing pressure has been observed in other studies in the literature [5,20]. Furthermore, formed
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primary products can be cracked by secondary fragmentation and/or converted to heavier components by combining with an increase in residence time. As a result, it can be said that the yield of gas product increases, while the yield of liquid product decreases. Besides, if residence time is long enough, the liquid product consists of heavy hydrocarbons. 3.3. Bio-oil/tar analysis The GC/MS analysis of bio-oil/tars obtained at different pressures and at a pyrolysis temperature of 500 °C is given in Fig. 4. Table 5 shows the detailed component analysis of bio-oil/tars by GC/MS, including retention time (min), compound name, and peak area. Also, the compounds in Table 5 are classified under main pyrolysis compounds and they are presented in Fig. 5. Considering Fig. 5, it can be seen that
Fig. 4. GC/MS chromatograms of the pyrolysis oils/tars at different pressures.
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Table 5 Relative proportions (area %) of compounds in bio-oils obtained at different pressures and at a pyrolysis temperature of 500 °C. Area (%) and (peak number) Retention time
Compound name
1 bar
3.84 9.06 9.48 10.41 11.18 11.83 12.5 13.91 14.55 14.82 15.17 15.72 17.21 17.57 17.92 18.3 18.37 18.53 19.62 19.69 19.93 20.18 20.88 20.99 22.04 23.04 23.93 24.11 24.87 25.13 25.24 25.73 26.83 27.14 27.94 28.74 29.49 29.52 29.68 31.82 32.24 33.15 33.74 34.99 36.31 44.74
Acetic acid, methyl ester Phenol 2,4-Imidazolidinedione, 3-methyl1,2-Cyclopentanedione, 3-methylPhenol, 2-methylPhenol, 3-methylPhenol, 2-methoxyPhenol, 2,4-dimethyl Phenol, 3-ethylNaphthalene Phenol, 2-methoxy-4-methyl1,2-Benzenediol 1,2-Benzenediol, 3-methoxyBenzeneethanol, 2-methoxyNaphthalene, 1-methylPyrazine, 2-methoxy-6-methylNaphthalene, 2-methyl2-Methoxy-4-vinylphenol Phenol, 2,6-dimethoxyEugenol Phenol, 2-methoxy-4-propylBiphenyl Benzaldehyde, 4-hydroxy-3-methoxyPhenol, 2-methoxy-4-(1-propenyl)2 H-Pyran-2,4(3 H)-dione Ethanone, 1-(4-hydroxy-3-methoxyph enyl)2,3,5- Trimethoxytoluene Homovanillyl alcohol 2,6-Dimethyl-3-(methoxymethyl)-p-benzoquinone Phenol, 2-methoxy-4-propyl9 H-Fluorene Phenol, 2,6-dimethoxy-4-(2-propenyl)5-(3′-Methyliden-2′-oxa-butyliden) -3,3-dimethyl-cyclohexanone Benzaldehyde, 4-hydroxy-3,5-dimethoxyPhenol, 2,6-dimethoxy-4-(2-propenyl)4-Hydroxy-2-methoxycinnamaldehyde Phenanthrene 2-Pentanone, 1-(2,4,6-trihydroxyphenyl) Anthracene Anthracene, 1-methyl4 H-Cyclopentaphenanthrene Hexadecanoic acid 3,5-Dimethoxy-4-hydroxycinnamalde Fluoranthene 9,12-Octadecadienoic acidAndrost-5,16-diene-3.beta.-ol
3.38 (1) 18.07 (2) 1.16 (3) 2.09 (4)
phenol and its derivatives and the carbonyl compounds consist of bio-oil obtained at 1 bar. Small amounts of fatty acids and acid esters were also found. Some oxygenated aromatic products, such as 1,2-
Fig. 5. Main component groups of bio-oil/tars at different pressures.
2.77 (5)
3.67 (6) 0.82 (7) 1.57 (8) 2.18 (9)
21 bar 8.47 (1)
41 bar 3.2 (1)
4.43 (2) 5.86 (3) 1.46 (4) 3.81 (5) 2.94 (6) 3.56 (7) 1.2 (8)
1.59 (9) 1.77 (10)
1.02 (2)
1.52 (10) 1.64 (11) 1.96 (11) 11.4 (12) 1.9 (13) 0.64 (14) 2.59 (15) 1 (16) 11.49 (17) 1.66 (18) 3 (19) 1.72 (20) 2.25 (21) 0.57 (22) 3.52 (23) 1.47 (24) 4.2 (25) 4.21 (26) 4.63 (27)
3.15 (12) 1.18 (13) 0.27 (14) 0.95 (15)
3.11 (3)
3.58 (16)
1.46 (4)
2.65 (17)
1.84 (5)
2.64 (18) 2.07 (19)
5.59 (6)
8.86 (20)
17.89 (7)
3.65 (28) 1.87 (21) 0.67 (22) 1.06 (29) 3.06 (30)
0.71 (23)
3.49 (8) 1.45 (9) 1.1 (10) 0.54 (11)
4.4 (24)
10.56 (12)
0.33 (31) 1.73 (32)
benzenediol, 1,2-benzenediol,3-methoxy-, benzeneethanol and benzoquinone were also formed. Cracking reactions are dominant at low residence times in pressurized pyrolysis. Radicals are formed as a result of the cracking reactions. They play a vital role in pyrolysis reactions. An increase of radicals, via ring crosslinking reactions, results in condensation of aromatics. If residence time is high enough, radicals can undergo a series of reactions with alkenes and aromatics to form larger ring structures or/and mono aromatic compounds connect to each other to form PAHs [8]. The relative proportion of PAHs in bio-oils was seen to increase with pressure. Phenol is an example of a benzene compound with just one substituent [23]. It is hydroxylated benzene. Under atmospheric conditions, phenols are relatively stable at 700 °C, but at 900 °C they are significantly decomposed [24]. In this study, at moderate temperatures, phenol and its derivatives were decreased and PAHs increased with increasing pressure. The condensed phenolic and aromatic units are connected to each other and form multi-ring PAHs with increased pressure and residence time. The ring size of PAHs was also shown to increase with pressure. The percentage of 2-ring PAHs (naphthalene and its derivatives) diminished and the percentage of 3-ring (9H-Fluorene, phenanthrene, anthracene and their derivatives) and 4-ring (Fluoranthene) PAHs increased with
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increasing pressure. At increased pressures (21 bars), 2-ring naphthalene and its derivatives were the only major PAH component. 3-ringed PAHs were not observed at pressures of less than 41 bars. As pressure and residence times increase, larger PAHs, such as 9 H-fluorene, phenanthrene, anthracene and their derivatives and Fluoranthene were detected. Primary oxygenated compounds were produced during pyrolysis at moderate temperatures and under 1 bar pressure. The primary
285
oxygenated oils obtained at moderate temperature (500 °C) changed to polycyclic aromatic and deoxygenated tar with increased pressure. A high temperature at atmospheric pressure is the most important factor in the formation of PAHs. Under atmospheric pyrolysis conditions, the formation of PAHs occurs at over 700 °C [6,21]. These compounds can either be found in only small amounts or cannot be determined in bio-oils at pyrolysis temperatures between 400 and 600 °C. Some studies in the literature show that when the temperature is increased from 500 °C to 900 °C PAHs increases, except for naphthalene and its derivatives, because naphthalene and its derivatives decrease when the temperature is increased from 800 °C to 900 °C [22]. But in this study it was found to produce significant amounts of PAH components at moderate temperatures when using high pressures. The composition of tar may also change as a function of residence time. Research by Ateş et al., shows that when residence time is one minute, then only cracking reactions are dominant [5]. Although they used pressure of between 1 and 10 bars to conduct their work, almost no PAH formation was observed. But in this study residence time was 5 min. The longer the residence time, the larger the fraction of PAH that is produced. The results are consistent with McGrath et al. [1]. Their results show that the yield of PAHs increases with temperature. In addition, the yield of PAHs increases as the residence time increases.
3.4. Char analysis Scanning electron microscopy (SEM) was used to evaluate the surface physical morphology of the chars. Fig. 6 shows the SEM images of the chars. Char morphology was greatly influenced by pressure. It can be seen that there are several developed pores on char obtained at 1 bar pressure. The raw material losses volatile components, so open pores occurred on char at 1 bar pressure pyrolysis. Swelling, exploding swelling pores and the formation of larger pores were specific for 21 bars pressure chars. It is not possible to observe pores on the surface of chars obtained at 41 bars pressure. Due to a possible pressure effect during pyrolysis, fragmentation and breakage into small pieces are specific for chars obtained at high pressure (41 bars).
4. Conclusion CCD in RSM contributes to the optimization of pyrolysis parameters under experimental conditions by setting both linear and second order mathematical models. According to the results of the analyses, maximum bio-oil yield of 30.45% was obtained at a heating rate of 750 °C/min, a pyrolysis temperature of 528.44 °C and 1 bar pressure. When the pressure was increased from atmospheric to 41 bars the yield decreased. From the results it can be concluded that the PAHs from the pyrolysis products were influenced by the process conditions. High pressures and/or long residence times are required to form PAHs. High pressure was found to trigger the formation of two, three, four-ringed aromatic hydrocarbons. In addition, after pyrolysis at a pressurized atmosphere, the tars produced had markedly less oxygenated compounds. Pyrolysis components, such as PAHs, previously obtained in other studies at atmospheric pressure and high temperatures, were obtained at moderate temperatures and high pressures in this current study. A decrease in pore number on the surface of char was observed at 21 bars, compared to 1 bar pressure char. At 41 bars, with the breakage of char into small pieces, no pore was observed.
Acknowledgments
Fig. 6. SEM micrographs of char obtained at different pressures.
This study was financially supported by the Anadolu University Research Fund (Project No: 1201F003).
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Fuel Processing Technology journal homepage: www.elsevier.com/locate/fuproc
Research article
Optimization of bio-oil production using response surface methodology and formation of polycyclic aromatic hydrocarbons (PAHs) at elevated pressures Funda Ates a,⁎, Nihal Erginel b a b
Faculty of Engineering, Department of Chemical Engineering, Anadolu University, Eskisehir, Turkey Faculty of Engineering, Department of Industrial Engineering, Anadolu University, Eskisehir, Turkey
a r t i c l e
i n f o
Article history: Received 10 July 2015 Received in revised form 28 September 2015 Accepted 19 October 2015 Available online xxxx Keywords: Pressure Pyrolysis Response surface methodology (RSM) Polycyclic aromatic hydrocarbons (PAHs)
a b s t r a c t This paper aims at the optimization of bio-oil yield obtained from poplar sawdust pyrolysis. A response surface methodology was carried out to optimize the experimental conditions. The factors investigated were temperature, pressure and heating rate. Five levels, which were low level, upper level, center point and two axillar points, were considered for each of the factors. Statistical analysis shows that these factors significantly affect bio-oil yield. According to the model, bio-oil yield is maximized when the following conditions are utilized; a pyrolysis temperature of 528.44 °C, pressure of 1 bar, and a heating rate of 750 °C/min. Bio-oil yield decreased with increased pressure, and the maximum bio-oil yield obtained was 30.45%. The physical properties of char and chemical compositions of the produced bio-oil were then characterized. These included SEM (Scanning Electron Microscope) and GC/MS (Gas chromatography/mass spectrometry) characterization. The formation of polycyclic aromatic hydrocarbons (PAHs) from the pyrolysis of poplar sawdust was observed, taking into account the influence of pressure. Pressurized pyrolysis of poplar sawdust generated a tar range of 2–4 ring PAHs. PAHs were the dominant products at 21 and 41 bars. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Biomass can be converted to useful products by two major technologies: biochemical and thermochemical. The most frequently used processes in biochemical technology are fermentation and anaerobic digestion. Fermentation is used to produce alcohol fuels, while methane gas is produced by anaerobic digestion. Among thermochemical conversion processes, such as combustion, gasification, liquefaction or pyrolysis, a liquid product is produced only by liquefaction and pyrolysis. Solid and gaseous products, as well as liquid products, can be produced in pyrolysis compared to liquefaction. Liquefaction produces only small amounts of solid residue and gas, both considered by-products of the process. Percentage distribution and composition of pyrolysis products mainly depend on pyrolysis temperature, heating rate, particle size, catalyst, residence time, type of biomass used, and pressure [1–4]. One of the most significant parameters in pyrolysis is temperature, because it affects the amount and composition of the volatile component. High heating rates have the ability to produce a high yield of liquid product. Rapid heating provides efficient heat and mass transfer rates. Pressure affects the mass transfer of releasing ⁎ Corresponding author. E-mail address: [email protected] (F. Ates).
http://dx.doi.org/10.1016/j.fuproc.2015.10.026 0378-3820/© 2015 Elsevier B.V. All rights reserved.
volatiles [5]. Residence time is also a critical parameter for pyrolysis, because short residence times prevent secondary reactions. If the residence time is sufficiently high, the resulting primary products will stay longer in the reaction atmosphere. Therefore, these primary products enter reactions, such as cracking and repolymerization, to form secondary and tertiary products. However, which of these secondary reactions will be dominant depends on the reaction parameters and conditions. The major chemical composition of bio-oil is described as phenols, carbonyl compounds, carboxylic acids, sugars, aliphatics, aromatics, alcohols, furfurals and furans. Evans and Milne classify pyrolysis products as primary, secondary, and tertiary [6,7]. Primary products can be characterized by cellulose-derived products, such as levoglucosan, hydroxyacetaldehyde and furfurals, hemicellulosederived products, and lignin-derived methoxyphenols. At the secondary pyrolysis reactions stage, the primary pyrolysis products occur from decomposition of raw material reactions and may undergo additional cracking reactions to form more volatile products, or they may undergo repolymerization reactions to form high molecular size products. Secondary products can be characterized as phenols, and olefins. These components have been determined by a number of studies in the literature [8,9]. Polycyclic aromatic hydrocarbons (PAHs) are classified as tertiary products, such as naphthalene, acenaphthylene, anthracene/phenanthrene, and pyrene. The most effective reaction
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Table 1 Proximate and ultimate analysis of biomass sample. Proximate analysis (wt.%)
Moisture Volatile matter Fixed carbon Ash C H N S Oa
Ultimate analysis (wt.%)
a
7.7 74.8 13.8 3.7 49.8 6.3 0.5 0.4 42.9
By difference.
conditions that trigger secondary reactions are temperature, pressure and residence time. PAHs are a large group of organic compounds that have two or more aromatic rings. As pollutants, PAHs are of concern because certain compounds have been identified as carcinogenic, mutagenic, and teratogenic. Besides, PAH-containing oils are added to the rubber, typically together with fillers, to achieve the desired elasticity. They are used in some brittle synthetic products such as PVC to make soft and flexible. Also they are used in car tires. They are inexpensive and make the products purchasable. Besides, we use PAH containing products such as tool and bicycle handles, some shoes, or sports items in daily life. There have been numerous studies on the influence of pyrolysis parameters on pyrolysis product yields in the literature. Although, some researchers have evaluated the optimization of pyrolysis conditions using response surface methodology [2,3,10–12], elevated pressure, heating rate and temperature have not yet been evaluated together for bio-oil yield using response surface methodology. The Response Surface Method (RSM) is a useful statistical experimental design and analysis tool. The RSM is used to design experiments in which factors and levels are determined and also in which the number and order of experiments are defined. The order of experiments should be random to disperse the effect of environmental noise factors. After handling the response of the experiments, the results are obtained by analyzing the response according to the RSM. A mathematical model is set via RSM by considering both linear and nonlinear relationships between independent variables, namely factors and response. If interactions affect response, the interaction term can be modeled in a mathematical model in the RSM. In addition, the RSM allows for optimization of the response. A response surface graph and a contours plot help visualize the shape of a response surface [13]. Bio-oil can be produced from a variety agricultural waste, forest waste, industrial waste and co-products and energy crops. Poplar sawdust is a main forest waste. For instance, bio-oil is produced from forest waste, such as sawdust, bark or shavings in Europe and North America [9]. The poplar likes wetlands, and is a tree that grows throughout Turkey. Nowadays, poplar wood is widely-used in the paper and inexpensive furniture timber industries. In this context, the aim of the present work is to optimize the influence of temperature, pressure and heating rate on the yield of the bio-oil product. The RSM was selected for the construction of nonlinear mathematical functions that contain not only linear relationships, but also quadratic forms and interactions of factors. In addition, changes in the resulting bio-oil composition with elevated pressure are also determined.
Fig. 1. Pressurized pyrolysis set-up.
2. Materials and methods 2.1. Biomass and TG analysis In the experimental study, poplar sawdust was used as a biomass sample in a fixed-bed reactor. Prior to the experiments, the biomass was dried, ground in a high speed rotary cutting mill to give particle size fractions of 0.425–1.25 mm. Table 1 shows the main characteristics of the pyrolyzed biomass. Ultimate analyses were performed on sawdust to determine its elemental composition. A Carlo Erba (EA 1108) elemental analyzer was used to determine the weight fractions of carbon, hydrogen, sulfur and nitrogen, with the weight fraction of oxygen being calculated by difference. A thermogravimetric analysis was carried out using a Linseis Thermowaage L81 thermo-gravimetric analyzer, coupled with a differential thermal analyzer (DTA), with high purity nitrogen as a carrier gas at a flow rate of 50 mL/min. About 25 mg material was placed in an alumina crucible and heated from room temperature to 1000 °C at 10 °C/min. 2.2. Response surface methodology (RSM) Response Surface Methodology (RSM) is a technique for modeling and analyzing the relationship between independent variables and response (yield), both as linear or nonlinear forms to determine an
Table 2 Factors and levels in experiments. Factors
Axillar (−2)
Low level (−1)
Center point (0)
Upper level (+1)
Axillar (+2)
Temperature (°C) Pressure (bar) Heating rate (°C/min)
400 1 150
450 11 300
500 21 450
550 31 600
600 41 750
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Fig. 2. DTG and TG curves of poplar sawdust.
optimum response. The linear and quadratic model with interactions can be seen in the following equation [13]:
y ¼ β0 þ
k X i¼1
β i xi þ
k X
βii x2i þ
XX
i¼1
βij xi x j þ ε
ib j
where y expresses response or yield, xis represent independent variables, β0 indicates the intercept constant, βis show the coefficients of linear terms, βiis represent the coefficients of quadratic terms, βijs show the coefficients of interaction terms, ε indicates experimental error and k represents the number of independent variables. Central Composite Design (CCD) in RSM is the most popular class of design used for fitting a second order model, especially in the chemical process [13]. In this study, three factors were considered in experiments with two levels, two axillar points with distance two (α = ±2), and six central points. In these experiments, handled factors and their levels have been given in Table 2. Twenty experiments were conducted in random order and the bio-oil yield was handled with the reactor.
the desired pressure within the reactor. When the desired temperature is reached, the reactor system is closed down for 5 min. After completion of the reaction, the valve is opened slowly and volatile products are completely discharged from the reactor. The volatile products passed through three traps, which were placed in an ice-bath. Condensable products were cooled and condensed by mean of ice-cooled traps and recovered with DCM (dichloromethane) washing. The aqueous phase was separated (condensed and non-condensed) from organic phase with a separating funnel. The solvent was removed in a rotary evaporator and residual was weighed as bio-oil. The solid product (char) remaining in the reactor was weighed. The gas yield was calculated by taking the difference. A detailed description of the reactor and pyrolysis experiments can be found elsewhere [5]. The feedstock was pyrolyzed between pressures of 1–41 bars and between temperatures of 400–600 °C, at a heating rate of between 150 and 750 °C/min. All the yields were calculated on a dry and ash-free basis, also each experiment was repeated for three times at each experimental condition and reproducibility of the experimental data was calculated to be within ±2%.
2.3. Experimental pyrolysis set-up 2.4. Product analyses A schematic diagram of the unit is represented in Fig. 1. The process set up involves steel wool in a thin tubular reactor for the placement of 3 g of sample raw material, a thermocouple inserted into the reactor from the top, fixing flanges at the top and bottom of the reactor for sealing with a valve placed at the lower end. Pressure was provided by utilizing nitrogen gas. The valve was kept closed in order to provide
Analyses have been carried out at a constant level of heating rate (750 °C/min) and pyrolysis temperature (500 °C) to analyze the influence of pressure on bio-oil composition. The pressure levels of 1, 21 and 41 bars were selected for the analysis of bio-oil components. A Hewlett-Packard HP 7890 gas chromatograph coupled to a HP 5975 Table 4 ANOVA table.
Table 3 Estimated regression coefficients for yield using data coded units. Term
Coef
SE coef
T
p-Value
Constant Temperature Pressure Heating rate Temperature ∗ temperature S = 0.9399
27.2985 1.1250 −0.9875 0.4250 −0.9794 R-Sq = 83.0%
0.2549 0.2350 0.2350 0.2350 0.1802 R-Sq(adj) = 78.5%
107.108 4.788 −4.203 1.809 −5.435
0.000 0.000 0.001 0.091 0.000
Source
DF
Seq SS
Adj SS
Adj MS
F
p-Value
Regression Linear Square Residual error Lack-of-fit Pure error Total
4 3 1 15 10 5 19
64.8340 38.7425 26.0915 13.2515 10.2381 3.0133 78.0855
64.8340 38.7425 26.0915 13.2515 10.2381 3.0133
16.2085 12.9142 26.0915 0.8834 1.0238 0.6027
18.35 14.62 29.53
0.000 0.000 0.000
1.70
0.291
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quadruple detector (GC/MS) was used for bio-oil analysis. A detailed description of this method can be found elsewhere [5]. The physical features of chars were recorded using a Zeiss EVO 50 Scanning Electron Microscope. Samples were mounted on an aluminum stub using carbon bands coated with a thin layer of gold–palladium in an argon atmosphere using an Agar Sputter Coater. 3. Results and discussion 3.1. Biomass analyses Typically, two or three peaks appear in the thermogravimetric analyses of lignocellulosic materials. These peaks can be assigned to each of the biomass components, such as hemicellulose, cellulose and lignin [14, 15]. From the DTG pyrolysis profile, as seen in Fig. 2, the first peak showing at 103 °C for poplar sawdust was obviously responsible for the moisture content in the raw material. The flat line observed after this peak indicates that most of the water was removed [16]. It can be seen that maximum thermal degradation occurs at 331 °C. The peak temperature of poplar sawdust is determined to be as much as Miscanthus straw (331 °C) and cotton stalk (334 °C) [17], but it is somewhat lower than other biomasses, such as sugarcane bagasse (355 °C) [17], wheat straw (372 °C), switch grass (392 °C), beech wood (382 °C) [18] and hornbeam sawdust (348 °C) [19]. The main thermal degradation reactions form and the TG curve sharply drops from this point. Afterwards, slight devolatilization continues and the TG curve is relatively flat. The total weight loss according to TGA is 76% at 600 °C.
3.2. Optimization of pressure, temperature, and heating rate on bio-oil yield using response surface methodology The results were analyzed with RSM using MINITAB 14.12.0 software. The use of partitioning to formally test for no differences in treatment means requires that certain assumptions need to be satisfied. Specifically, these assumptions are that the observations are adequately described by the model and that errors are normally and independently distributed with a mean of zero and a constant, but unknown, variance σ 2. If these assumptions are valid, the analysis of the variance procedure is an exact test of the hypothesis of no difference in treatment means [13]. According to the analyzing on residuals, three assumptions are valid at this study. The effective factors and their coefficients of the second-order regression model, for maximum bio-oil yield obtained from pressurized pyrolysis of poplar sawdust, are given in Table 3. In addition, a mathematical model is given in Eq. (1). Also the ANOVA table, shown in Table 4, indicates that the second order regression model is appropriate for the yield. Models with p-value of less than 0.10 are defined as significant fits. The second-order regression model is:
^ ¼ −81:094 þ 0:4143x1 −0:0988x2 þ 0:0028x3 −0:000392x21 y
ð1Þ
where, x1 represents temperature, x2 shows pressure, x3 indicates ^ is the percentage yield of bioheating rate independent variables, and y oil. According to the results, the mathematical model consists of effective terms that are temperature, pressure, heating rate and temperature2. The interaction terms, and square terms of pressure and heating rate are not significant on yield. As a result, these terms were extracted from the model. The R2(adj) of the mathematical model in Table 3 refers to the coefficient of determination and gives the amount of variability in the data explained by the mathematical model. In this mathematical model, R2(adj) is equal to 78.5% and this value is acceptable.
Fig. 3. Surface plot of bio-oil yield and pressure and temperature (a), bio-oil yield and heating rate and pressure (b), and bio-oil yield and heating rate and temperature (c).
There is a quadratic relationship between bio-oil yield and temperature. A three dimensional response surface plot of yield versus pressure and temperature can be seen in Fig. 3a. The linear relationship between bio-oil yield, heating rate and pressure can be seen in Fig. 3b. In addition, the surface plot of bio-oil yield versus heating rate and temperature is given in Fig. 3c. Because of the nonlinear mathematical model, further calculations were conducted to determine whether the stationary point is at a minimum or maximum value for temperature. ^ dy ¼ 0:4143−2ð0:000392Þx1 ¼ 0 dx1 x1 ¼ 528:44
ð2Þ
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^ dy ¼ −0:000784 b 0: dx21
ð3Þ
The stationary point of x1 =528.44 (°C) was defined as a maximum value for temperature (Eqs. (2) and (3)). For maximum bio-oil yield, pressure should be 1 bar, and heating rate should be 750 °C/min. In this case, the maximum bio-oil yield is 30.45%. Increasing pressure led to a decrease of bio-oil yield. A pressure gradient between the inside of the raw materials and the external environment is evident, together with the increase in pressure [4]. Therefore, volatiles forming with increasing temperatures are imprisoned in residual char. A decrease in bio-oil yield with increasing pressure has been observed in other studies in the literature [5,20]. Furthermore, formed
283
primary products can be cracked by secondary fragmentation and/or converted to heavier components by combining with an increase in residence time. As a result, it can be said that the yield of gas product increases, while the yield of liquid product decreases. Besides, if residence time is long enough, the liquid product consists of heavy hydrocarbons. 3.3. Bio-oil/tar analysis The GC/MS analysis of bio-oil/tars obtained at different pressures and at a pyrolysis temperature of 500 °C is given in Fig. 4. Table 5 shows the detailed component analysis of bio-oil/tars by GC/MS, including retention time (min), compound name, and peak area. Also, the compounds in Table 5 are classified under main pyrolysis compounds and they are presented in Fig. 5. Considering Fig. 5, it can be seen that
Fig. 4. GC/MS chromatograms of the pyrolysis oils/tars at different pressures.
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Table 5 Relative proportions (area %) of compounds in bio-oils obtained at different pressures and at a pyrolysis temperature of 500 °C. Area (%) and (peak number) Retention time
Compound name
1 bar
3.84 9.06 9.48 10.41 11.18 11.83 12.5 13.91 14.55 14.82 15.17 15.72 17.21 17.57 17.92 18.3 18.37 18.53 19.62 19.69 19.93 20.18 20.88 20.99 22.04 23.04 23.93 24.11 24.87 25.13 25.24 25.73 26.83 27.14 27.94 28.74 29.49 29.52 29.68 31.82 32.24 33.15 33.74 34.99 36.31 44.74
Acetic acid, methyl ester Phenol 2,4-Imidazolidinedione, 3-methyl1,2-Cyclopentanedione, 3-methylPhenol, 2-methylPhenol, 3-methylPhenol, 2-methoxyPhenol, 2,4-dimethyl Phenol, 3-ethylNaphthalene Phenol, 2-methoxy-4-methyl1,2-Benzenediol 1,2-Benzenediol, 3-methoxyBenzeneethanol, 2-methoxyNaphthalene, 1-methylPyrazine, 2-methoxy-6-methylNaphthalene, 2-methyl2-Methoxy-4-vinylphenol Phenol, 2,6-dimethoxyEugenol Phenol, 2-methoxy-4-propylBiphenyl Benzaldehyde, 4-hydroxy-3-methoxyPhenol, 2-methoxy-4-(1-propenyl)2 H-Pyran-2,4(3 H)-dione Ethanone, 1-(4-hydroxy-3-methoxyph enyl)2,3,5- Trimethoxytoluene Homovanillyl alcohol 2,6-Dimethyl-3-(methoxymethyl)-p-benzoquinone Phenol, 2-methoxy-4-propyl9 H-Fluorene Phenol, 2,6-dimethoxy-4-(2-propenyl)5-(3′-Methyliden-2′-oxa-butyliden) -3,3-dimethyl-cyclohexanone Benzaldehyde, 4-hydroxy-3,5-dimethoxyPhenol, 2,6-dimethoxy-4-(2-propenyl)4-Hydroxy-2-methoxycinnamaldehyde Phenanthrene 2-Pentanone, 1-(2,4,6-trihydroxyphenyl) Anthracene Anthracene, 1-methyl4 H-Cyclopentaphenanthrene Hexadecanoic acid 3,5-Dimethoxy-4-hydroxycinnamalde Fluoranthene 9,12-Octadecadienoic acidAndrost-5,16-diene-3.beta.-ol
3.38 (1) 18.07 (2) 1.16 (3) 2.09 (4)
phenol and its derivatives and the carbonyl compounds consist of bio-oil obtained at 1 bar. Small amounts of fatty acids and acid esters were also found. Some oxygenated aromatic products, such as 1,2-
Fig. 5. Main component groups of bio-oil/tars at different pressures.
2.77 (5)
3.67 (6) 0.82 (7) 1.57 (8) 2.18 (9)
21 bar 8.47 (1)
41 bar 3.2 (1)
4.43 (2) 5.86 (3) 1.46 (4) 3.81 (5) 2.94 (6) 3.56 (7) 1.2 (8)
1.59 (9) 1.77 (10)
1.02 (2)
1.52 (10) 1.64 (11) 1.96 (11) 11.4 (12) 1.9 (13) 0.64 (14) 2.59 (15) 1 (16) 11.49 (17) 1.66 (18) 3 (19) 1.72 (20) 2.25 (21) 0.57 (22) 3.52 (23) 1.47 (24) 4.2 (25) 4.21 (26) 4.63 (27)
3.15 (12) 1.18 (13) 0.27 (14) 0.95 (15)
3.11 (3)
3.58 (16)
1.46 (4)
2.65 (17)
1.84 (5)
2.64 (18) 2.07 (19)
5.59 (6)
8.86 (20)
17.89 (7)
3.65 (28) 1.87 (21) 0.67 (22) 1.06 (29) 3.06 (30)
0.71 (23)
3.49 (8) 1.45 (9) 1.1 (10) 0.54 (11)
4.4 (24)
10.56 (12)
0.33 (31) 1.73 (32)
benzenediol, 1,2-benzenediol,3-methoxy-, benzeneethanol and benzoquinone were also formed. Cracking reactions are dominant at low residence times in pressurized pyrolysis. Radicals are formed as a result of the cracking reactions. They play a vital role in pyrolysis reactions. An increase of radicals, via ring crosslinking reactions, results in condensation of aromatics. If residence time is high enough, radicals can undergo a series of reactions with alkenes and aromatics to form larger ring structures or/and mono aromatic compounds connect to each other to form PAHs [8]. The relative proportion of PAHs in bio-oils was seen to increase with pressure. Phenol is an example of a benzene compound with just one substituent [23]. It is hydroxylated benzene. Under atmospheric conditions, phenols are relatively stable at 700 °C, but at 900 °C they are significantly decomposed [24]. In this study, at moderate temperatures, phenol and its derivatives were decreased and PAHs increased with increasing pressure. The condensed phenolic and aromatic units are connected to each other and form multi-ring PAHs with increased pressure and residence time. The ring size of PAHs was also shown to increase with pressure. The percentage of 2-ring PAHs (naphthalene and its derivatives) diminished and the percentage of 3-ring (9H-Fluorene, phenanthrene, anthracene and their derivatives) and 4-ring (Fluoranthene) PAHs increased with
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increasing pressure. At increased pressures (21 bars), 2-ring naphthalene and its derivatives were the only major PAH component. 3-ringed PAHs were not observed at pressures of less than 41 bars. As pressure and residence times increase, larger PAHs, such as 9 H-fluorene, phenanthrene, anthracene and their derivatives and Fluoranthene were detected. Primary oxygenated compounds were produced during pyrolysis at moderate temperatures and under 1 bar pressure. The primary
285
oxygenated oils obtained at moderate temperature (500 °C) changed to polycyclic aromatic and deoxygenated tar with increased pressure. A high temperature at atmospheric pressure is the most important factor in the formation of PAHs. Under atmospheric pyrolysis conditions, the formation of PAHs occurs at over 700 °C [6,21]. These compounds can either be found in only small amounts or cannot be determined in bio-oils at pyrolysis temperatures between 400 and 600 °C. Some studies in the literature show that when the temperature is increased from 500 °C to 900 °C PAHs increases, except for naphthalene and its derivatives, because naphthalene and its derivatives decrease when the temperature is increased from 800 °C to 900 °C [22]. But in this study it was found to produce significant amounts of PAH components at moderate temperatures when using high pressures. The composition of tar may also change as a function of residence time. Research by Ateş et al., shows that when residence time is one minute, then only cracking reactions are dominant [5]. Although they used pressure of between 1 and 10 bars to conduct their work, almost no PAH formation was observed. But in this study residence time was 5 min. The longer the residence time, the larger the fraction of PAH that is produced. The results are consistent with McGrath et al. [1]. Their results show that the yield of PAHs increases with temperature. In addition, the yield of PAHs increases as the residence time increases.
3.4. Char analysis Scanning electron microscopy (SEM) was used to evaluate the surface physical morphology of the chars. Fig. 6 shows the SEM images of the chars. Char morphology was greatly influenced by pressure. It can be seen that there are several developed pores on char obtained at 1 bar pressure. The raw material losses volatile components, so open pores occurred on char at 1 bar pressure pyrolysis. Swelling, exploding swelling pores and the formation of larger pores were specific for 21 bars pressure chars. It is not possible to observe pores on the surface of chars obtained at 41 bars pressure. Due to a possible pressure effect during pyrolysis, fragmentation and breakage into small pieces are specific for chars obtained at high pressure (41 bars).
4. Conclusion CCD in RSM contributes to the optimization of pyrolysis parameters under experimental conditions by setting both linear and second order mathematical models. According to the results of the analyses, maximum bio-oil yield of 30.45% was obtained at a heating rate of 750 °C/min, a pyrolysis temperature of 528.44 °C and 1 bar pressure. When the pressure was increased from atmospheric to 41 bars the yield decreased. From the results it can be concluded that the PAHs from the pyrolysis products were influenced by the process conditions. High pressures and/or long residence times are required to form PAHs. High pressure was found to trigger the formation of two, three, four-ringed aromatic hydrocarbons. In addition, after pyrolysis at a pressurized atmosphere, the tars produced had markedly less oxygenated compounds. Pyrolysis components, such as PAHs, previously obtained in other studies at atmospheric pressure and high temperatures, were obtained at moderate temperatures and high pressures in this current study. A decrease in pore number on the surface of char was observed at 21 bars, compared to 1 bar pressure char. At 41 bars, with the breakage of char into small pieces, no pore was observed.
Acknowledgments
Fig. 6. SEM micrographs of char obtained at different pressures.
This study was financially supported by the Anadolu University Research Fund (Project No: 1201F003).
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