Article pubs.acs.org/EF
Fast Pyrolysis in a Microfluidized Bed Reactor: Effect of Biomass Properties and Operating Conditions on Volatiles Composition as Analyzed by Online Single Photoionization Mass Spectrometry Liangyuan Jia,† Yann Le-Brech,† Binod Shrestha,† Matthias Bente-von Frowein,‡ Sven Ehlert,‡,§,∥ Guillain Mauviel,† Ralf Zimmermann,§,∥ and Anthony Dufour*,† †
LRGP, CNRS, University of Lorraine, ENSIC, 1 rue Grandville, 54000 Nancy, France PHOTONION GmbH, Hagenower Strasse 73, 19061 Schwerin, Germany § Joint Mass Spectrometry Centre, Chair of Analytical Chemistry, Institute of Chemistry, University of Rostock, 18059 Rostock, Germany ∥ Comprehensive Molecular Analytics (CMA), Helmholtz, Zentrum München, 85764 Neuherberg, Germany ‡
S Supporting Information *
ABSTRACT: The real-time analysis of volatiles (primary tar) produced during the fast pyrolysis of biomass in a microfluidized bed reactor (MFBR) is achieved by online single photoionization mass spectrometry (SPI-MS). The effect of biomass composition (Douglas fir, oak, and miscanthus), particle shape and size (cylinder, lamella, or powder), bed temperature, and fluidizing gas flow-rate on primary tar composition is studied. Principle component analysis is conducted on the major ions analyzed by SPI-MS to evidence the significant differences between conditions. The variance in obtained SPI-MS spectra reveals the important effect of biomass composition and temperature on volatiles composition. The effect of particle size on volatiles composition is clearly evidenced. Typical pyrolysis regimes are defined according to specific markers which are key chemical compounds to characterize biomass fast pyrolysis. SPI-MS combined with a MFBR is an interesting tool to unravel the effects of biomass composition and of heat and mass transfers on biomass fast pyrolysis processes. 450−475 °C to achieve maximum yield of bio-oil and minimum content of water.11 A similar work accomplished by Mourant et al. confirmed the importance of temperature on the yields and properties of bio-oil from fast pyrolysis of bark.12 The effect of temperature on the primary and secondary lignin products was also investigated by pine wood pyrolysis in a fluidized-bed.13 Another study on fast pyrolysis of mallee wood has found that a maximum in the yield of lignin-derived oligomers could be obtained between 450 and 500 °C.14 Particle geometry also greatly affects the pyrolysis processes due to its direct influence on mass and heat transfers.15,21 Shen et al. pyrolyzed mallee wood in a fluidized-bed and found that the yield of ligninderived oligomers decreases as the biomass particle size increases.16 Two reactions regimes related to the effect of particle geometry on fast pyrolysis of beech wood were also found and confirmed by Westerhof et al.17,18 Other studies relating to combined effects of pyrolysis temperature, particle size, residence time, and sand particle size on the yield and quality of bio-oil from fast pyrolysis have also been reported.6,19,20,22 Analytical instruments, such as thermogravimetric analysis (TGA), gas chromatography (GC), Fourier transform infrared spectroscopy (FT-IR), and nuclear magnetic resonance (NMR), have been widely applied to study biomass pyrolysis
1. INTRODUCTION The pyrolysis of biomass is considered as a promising process to efficiently produce transportation fuels and chemicals. The formation of volatiles which yield bio-oil after condensation takes place over the temperature range of 200−600 °C.1 According to the heat flux brought from the reactor to the biomass particles, the pyrolysis process can be divided into slow pyrolysis or fast pyrolysis.2 Fast pyrolysis promotes the formation of liquid bio-oil if the residence time of volatiles in the hot zone (∼500 °C) is lower than 2 s.3 In this process, biomass composition as well as heat and mass transfers are key parameters for bio-oil yield and composition.4 Numerous studies have investigated fast pyrolysis of biomass over the past few decades, and various reactors have been developed, such as fluidized-bed, single/twin screw, ablative, or rotating cone reactors.3−5 Fluidized-bed reactors are very suitable for fast pyrolysis as they are characterized by a relatively simple construction, a uniform hot sand temperature, and a high heat transfer coefficient from the sand to biomass.4,6 Recently the so-called microfluidized bed reactor (MFBR) has been developed to study the kinetics of the thermal decomposition of various solid materials and especially biomass pyrolysis due to its many advantages.7−10 The fast pyrolysis of biomass in fluidized bed reactors is significantly influenced by many factors, such as particle size and shape, hot sand temperature, gas-phase residence time, etc.6,11−20 Garcia-Perez et al. studied the fast pyrolysis of mallee wood and stated that the temperature should be well controlled in a small range of © 2015 American Chemical Society
Received: August 7, 2015 Revised: October 12, 2015 Published: October 14, 2015 7364
DOI: 10.1021/acs.energyfuels.5b01803 Energy Fuels 2015, 29, 7364−7374
Article
Energy & Fuels
Figure 1. Picture and scheme of microfluidized bed combined with a single photoionization mass spectrometer. The inset figure illustrates the method for biomass particles production. Two different injection rods are used for powder injection (left) or for bigger particles injection (right). Specific design of the furnace with a quartz window allows the visualization of the fluidized bed reactor in real-time. More details on the design are provided in Supporting Information.
products.4,23 Mass spectrometry (MS) combined with various pyrolysis reactors is also frequently utilized to analyze the volatiles from biomass pyrolysis.24 For example, GC-MS is frequently used for the off-line analysis of bio-oil.4 Pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) has been widely used for biomass analysis.25 Pyrolysis-molecular beam mass spectrometry (Py-MBMS) has also been shown to be specially suited for real-time sampling of high-temperature pyrolysis vapors of biomass.26−28 Recently, ultrahigh-resolution mass spectrometry such as Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR) has been successfully used for comprehensive analysis of bio-oil.29−33 However, more and more studies demonstrated that soft photoionization method can improve the mass spectrometric analysis of biomass volatiles, because most of them are very fragile and the lower ionization energy can reduce fragmentation of pyrolysis products and efficiently simplify the final mass spectra.5,34−38 The MFBR equipped with electron-impact (EI) mass spectrometry has been developed for the online analysis of permanent gas,9,39−41 but it has not yet been used for online analysis of pyrolysis tar (at the vapor phase). In this work, a homemade MFBR is used for fast pyrolysis of biomass under accurate hydrodynamic, mass, and heat transfers conditions, and this reactor is combined with single photoionization timeof-flight mass spectrometry (SPI-TOF-MS) for online analysis of volatiles (primary tar). The combination of our soft ionization technique with the MFBR is a novel and powerful method to study biomass fast pyrolysis. The effect of biomass composition, particle shape, and operating conditions on the composition of volatiles is studied by this method. A better
understanding of these parameters’ effects will contribute to the optimization of pyrolysis processes.
2. MATERIALS AND METHODS 2.1. Characterization of Biomass Samples. Miscanthus, a “bamboo” type grass (Miscanthus × Giganteus), was harvested in Lorraine (France). Douglas fir (softwood) and oak (hardwood) were harvested in the Haut-Beaujolais area (southeast France). These biomasses have been carefully characterized. Their composition (ash content and composition, carbohydrate and lignin content, etc.) is presented in detail in Tables S.1 and S.2 (see Supporting Information). The preparation of wood particles is presented in the inset of Figure 1. All samples with different shapes and sizes were produced from the same piece of wood (Douglas fir and oak). As shown in Figure 1, cylinder and lamella particles were milled to have their length (L) in the direction of the fibers. A powder sieved between 40 and 100 μm meshes was also produced from the same woods (Douglas fir and oak) and from miscanthus. Miscanthus pellets (but no lamella) were also prepared from the same Miscanthus powder pressed into the shape of cylinder by using a hydraulic press (P-16, Beckman-RIIC Ltd., UK) under 3 tons pressure for 30 s. 2.2. Design and Operation of the Reactor for Fast Pyrolysis Experiments. A schematic diagram of the experimental setup is shown in Figure 1. The devolatilization of wood particles was carried out in a preheated microfluidized bed reactor (MFBR) with an inner diameter of 20 mm and a height of 15 cm (for the outlet of gas). The design of the MFBR follows the recommendations of Xu et al., and a detailed hydrodynamic study has been presented by these authors in ref 8. A sintered plate of 5 mm in thickness, made of 150 μm silica sand particles, was used as MFBR’s gas distributor. The inert bed material was composed of silica sand particles with 150−300 μm particle size to ensure a suitable fluidization regime (see ref 8). The entire MFBR was positioned in a homemade electrical furnace, which has a quartz window to make the fluidization process easily visible during pyrolysis. Pure nitrogen (99.99%) was introduced by two gas 7365
DOI: 10.1021/acs.energyfuels.5b01803 Energy Fuels 2015, 29, 7364−7374
Article
Energy & Fuels lines into the reactor. One served as the fluidizing gas (from bottom) whose flow rate was varied to investigate its effect on the pyrolysis process. The other with constant flow rate of 40 mL/min (measured at 20 °C, atmospheric pressure) was used as the sweep gas (from above) for the injection system. Both flow rates were monitored by mass flowmeters. All samples in any shape or size could be handled in our specially designed injection rods (see inset picture in Figure 1), and then introduced into the MFBR. The top of reactor could be opened to accept samples before injection and sealed by the stainless steel rod and a carrier gas flow. All temperatures were controlled with temperature controllers and measured by K-type thermocouples. The temperature profiles in MFBR are provided in Supporting Information. They show the very good homogeneity in the fluidized zone and a temperature profile in the gas-phase zone. This temperature profile may lead to some secondary reactions depending on the gas-phase residence time as will be discussed in the Results section. The gas residence time in the hot zone of MFBR (10 cm with a temperature higher than 400 °C, leading to a volume of about 30 mL, see Supporting Information) and for a flow rate of fluidizing gas of 670 mL/min (measured at 20 °C, atmospheric pressure) is about 1 s at 500 °C. During the experiment, the particles and powder were injected into the preheated MFBR (set at the targeted temperature) in less than 1 s. The position of the particles in the fluidized zone is displayed in Supporting Information. 2.3. Sampling of Volatiles and Analysis by SPI-TOFMS. The outlet of the MFBR was connected to the transfer-line of SPI mass spectrometer with a heated tee adapter (300 °C). Excess gas was released into the laboratory’s vents from second outlet of the adapter. The evolved gas, seeded in carrier gas, was sampled by a quartz capillary line (3−4 mL/min) for SPI-TOFMS characterization. The transfer-line without any filtering materials was heated to a temperature of 250 °C to avoid the quartz capillary line (internal diameter 200 μm × 5 m length) being blocked by condensed volatiles. At the outlet of the heated capillary line, the volatiles were directly injected in the ionization zone of the SPI-MS. The SPI-MS measurements were conducted with a reflectron time-of-flight mass spectrometer (TOF-MS) equipped with dual ion source for EI and SPI (PhotoTOF, Photonion GmbH, Germany, a custom-device developed for CNRS-Nancy). An electron beam pumped argon-excimer vacuum ultraviolet (VUV) lamp system (EBEL, modified E-Lux 126, Optimare, Germany) with a photon energy of 9.8 eV (126 nm) was used for SPI.42 As the EBEL lamp works electrodeless, the spectral properties of the VUV emission stay constant over the operation time of the lamp. The TOF-MS covers the mass range of m/z 10−2000 with a mass resolution of 2000 and mass accuracy of 100 ppm. Data were acquired from the mass spectrometer with Acqiris AP240 (Agilent Technologies) average cards and displayed by a special software (Photonion GmbH, Germany). 2.4. Experimental Conditions Studied in This Work. Table 1 presents the experimental conditions studied in this work. The effects of biomass composition (oak, Douglas fir, miscanthus), particle shape
and size (cylinder, lamella, powder, and length of cylinder), temperature of the MFBR (400 and 500 °C, temperature of the fluidized sand), and flow of fluidizing gas are investigated. In the following text, we always refer to the temperature of the fluidized sand (400 or 500 °C) and not to the temperature of “pyrolysis reactions”, which cannot be measured directly in our experimental conditions and corresponds to a large temperature range. Char yields for cylinders experiments are provided in Supporting Information. 2.5. Statistical Analysis by the Principal Component Analysis Method. In order to clearly present the influence of varying experimental conditions on pyrolysis products, principal component analysis (PCA) was conducted. The SPI-MS spectra contain dozens of peaks, and it is difficult to make a distinction solely based on observation. PCA has been shown to be a powerful statistical tool to analyze the infrared and mass spectra of biomass pyrolysis.5,43−47 This method allows visualizing all the information contained in a set of data and also extracting the significant differences between conditions as opposed to noise or meaningless variation contained in the data. PCA transforms the original ordinate system. The new ordinates are called principal components. The origin of the new coordinate system is located in the center of the data points. The first PC (PC1) refers to the highest variance (most significant effect), the second PC (PC2) to the second highest variance, and so on. In PCA plots, the points labeled with numbers correspond to m/z observed for various ions analyzed by SPI-MS. All raw mass spectra have been treated with the MSC/EMSC method to average the signal intensities of 38 key peaks for each experimental condition before application of PCA, using the Unscrambler (CAMO software AS, Version 10.3, Oslo, Norway). The PCA in this work presents the difference in product distribution obtained for the various biomass species, temperatures, shapes, and gas flow rates.
3. RESULTS AND DISCUSSION Here we present first the assignment of the molecular structure of the main m/z ions detected by SPI-MS. Second, the main markers of the three biomasses are compared based on PCA. Third, the effect of particle shape, pyrolysis temperature, and fluidization velocity is studied for each biomass. 3.1. Characterization and Classification of Primary Products from the Three Biomasses. The mass spectra (m/ z 40−350) of primary products from Douglas fir, oak, and miscanthus pyrolysis were obtained by SPI-MS and were time averaged to yield a representative spectrum for each condition (see Figures 2−4). The most important pyrolysis products are listed in Table 2. As shown in Table 2, most peaks observed in SPI mass spectra of Douglas fir, oak, and miscanthus correspond to the same compounds, which stem from thermal degradation of carbohydrates (cellulose and hemicelluloses) and lignin. Most m/z peaks were tentatively assigned based on our off-line analysis by GC*GC/MS and by comparison with MS spectra from the literature, while a few other peaks still need further work to be assigned. The detailed assignments of these m/z peaks are discussed for the three macromolecules (hemicelluloses, cellulose, then lignin) in the following text. (1) Hemicelluloses present in the biomasses produce two main specific markers: 3-hydroxy-2-penteno-1,5-lactone (m/z 114) and ethyl-1-propenyl ether (m/z 86). Actually, a little m/z 114 is also produced from cellulose, but its main contribution comes from xylan, which is the main component of hemicelluloses. Our previous study also demonstrates that m/ z 86 is a typical fragment of m/z 114.36 Therefore, m/z 114 could be chosen as a marker of hemicelluloses. (2) Cellulose products contain light oxygenated compounds (m/z 60, 70, 74), cyclopentanone (m/z 98, 112), pyran derivatives (m/z 144, 162), and furan derivatives (m/z 82, 96, 98, 110, 112, 126, 128, and 142). Please note that m/z 110 (5-
Table 1. Experimental Conditions with Their Abbreviations parameters
varying conditions
biomass type particle shape and size
oak (O), Douglas fir (D), and miscanthus (M) powder (40−100 μm, P); thin lamella (0.5 × 12 mm, L); cylinder (6 × 12 mm length, C1), and (6 × 20 mm length, C2) Fontainebleau sand (150−300 μm)
fluidization sand flow rate of fluidizing gas temperature of fluidized sand
Uf1 = 670 mL/min (B); Uf 2 = 300 mL/min (M); Uf 3 = 200 mL/min (S) T1 = 400 °C and T2 = 500 °C
7366
DOI: 10.1021/acs.energyfuels.5b01803 Energy Fuels 2015, 29, 7364−7374
Article
Energy & Fuels
Figure 2. Representative SPI mass spectra from the pyrolysis of Douglas fir with different shapes (400 °C, Uf1): (a) powder, 40−100 μm, 50 mg; (b) thin lamella 0.5 × 12 mm; (c) cylinder 6 × 12 mm; (d) cylinder 6 × 20 mm.
methylfurfural) has been assigned as a main product from carbohydrates,36,48 but it also appeared in the REMPI mass spectra even though its signal was weak.5 This suggested that small but detectable amounts of catechol or other dihydroxybenzene isomers (m/z 110) from lignin could be produced since REMPI is very selective to the lignin-derived products. The peak at m/z 162 assigned to levoglucosan is often considered to be a characteristic product from cellulose degradation, but Fendt et al. also assigned this peak to methoxycinnamaldehyde from lignin degradation.5 The possibility of the latter cannot be ruled out for the following reason. Levoglucosan simultaneously produces a m/z 162 and fragment ions (m/z 144, etc.) even at our soft photoionization energy due to the low energy decomposition barrier from levoglucosan to 1,4:3,6-dianhydro-α-D-glucopyranose.34,36 However, a strong signal of m/z 162 and weak signal of m/z 144 were obtained by SPI-MS when powder miscanthus was pyrolyzed at 400 °C (see Figure 4). Moreover, the high inorganic content in miscanthus considerably inhibits the formation of levoglucosan (see Table S.2 in Supporting Information). This suggests that m/z 162 most probably corresponds to other compounds rather than levoglucosan for miscanthus. There is no obvious difference in time profiles between all cellulose markers (see Figure S.1 in Supporting Information), and therefore only m/z 126 has been plotted in Figure 5a as a significant marker for cellulose. It can be assigned to 5-(hydroxymethyl)-2-furaldehyde (5HMFU) for Douglas fir and oak pyrolysis. m/z 126 may rather be
levoglucosenone for miscanthus pyrolysis because 5HMFU was not detected by GC/MS. (3) Lignin products are mainly composed of guaiacol- (G, m/z 124, 138, 150 and 166), syringol- (S, m/z 140, 154 168, 180, 182, 194, 196, 208 and 210), and phenol derivatives (H, m/z 94, 108, 110, 120, 122 and 148). The different structure of miscanthus, oak and Douglas fir can be clearly observed in SPI mass spectra (see Figures 2−4). Higher signal intensities of syringol derivatives are a typical feature associated with hardwood, while peaks at m/z 120 (4-vinylphenol) are a characteristic marker for miscanthus. Gaston et al. reported that m/z 124 arises from carbohydrates when oak was pyrolyzed at 500 °C,45 but we have detected (by GC-MS) guaiacol for oak pyrolysis. The peak at m/z 180 could correspond to two different compounds, namely, 4-vinylsyringol and coniferyl alcohol. The former is a pyrolysis product from oak and miscanthus, while the latter is a product from Douglas fir. Figure 5a displays the time profiles evolution of the main characteristic markers for hemicelluloses, cellulose, and lignin. These markers are significant of all other markers previously discussed and presented in Supporting Information. The degradation of hemicelluloses and lignin begins at almost the same time, followed by cellulose (for the pyrolysis of cylinder Douglas fir). This finding is consistent with previous works.36,37 Lignin-derived products could be further classified into two groups of markers named “lignin-1” and “lignin-2” based on their different formation rates. Figure 5b displays a simple 7367
DOI: 10.1021/acs.energyfuels.5b01803 Energy Fuels 2015, 29, 7364−7374
Article
Energy & Fuels
Figure 3. Representative SPI mass spectra from the pyrolysis of oak with different shapes (at 400 °C, Uf1): (a) powder, 40−100 μm, 50 mg; (b) thin lamella 0.5 × 12 mm; (c) cylinder 6 × 12 mm; (d) cylinder 6 × 20 mm.
Furthermore, it is important to notice that the absolute intensity for each experiment is not important in our approach because all mass spectra (from all investigated conditions) are normalized as one set of data by the MSC/EMSC method before PCA analysis. PCA analysis is thus conducted on the normalized relative mass spectra. Besides, PCA analysis for the three triplicate experiments is provided in Supporting Information. As it can be observed in Figure S.3, Douglas fir (DC1 and DC2) and oak (OC1) can be clearly differentiated by PCA with a spectral variation of 98% (PC1), while the variation for individual Douglas fir and oak only account for 1% (PC2). This means that triplicate experiments at the same operating conditions cannot be differentiated by PCA analysis, and they are very well reproducible. Therefore, the differences revealed in the next section by PCA are not due to a statistical bias but to significant differences between the mass spectra from the different operating conditions. 3.3. Comparison of Three Biomasses Based on Their PCA Results. The PCA method depicts the differences and similarities between experiments. PCA results including scores (top part) as well as X-loading (bottom part) for all investigated biomasses, and experimental conditions are displayed in Figure 6, in which different biomasses are marked in different symbols and colors. The three kinds of biomasses (Douglas fir, miscanthus, and oak) could be clearly separated by the principal components (PCs) and are illustrated in the scores plot of PC1 and PC2. The PC1 accounted for 41% of the total spectral variation and PC2 for 28%. PC1 can roughly
mechanism of lignin decomposition and its classification partly based on previous literature.1,49 The first step of lignin decomposition is the formation of primary char (Char 1) from the conversion of propyl chain and the rupture of Cβ-Cγ, α-O-4, β-O-4 and the release of the lignin-1 species, which are phenolic compounds with a double bond on the aromatic ring functions. In a second step, the structure of primary char is further converted to another more cross-linked char (Char 2), leading to the direct break of more C−C linkages within and between the alkyl chains and the formation of “lignin-2” species. The classification of these two kinds of lignin markers is listed in Table 2. Only m/z 150 and 124 assigned to lignin-1 and lignin-2 markers respectively are presented as characteristic markers in Figure 5a. The time profiles formation of other lignin markers are presented in Supporting Information. All lignin-derived compounds directly formed from lignin/char are defined here as primary products. Secondary reactions of both carbohydrate and lignin primary species could also occur in the surrounding gas phase, but they depend on temperature, residence time, and even on the contact time of volatiles with the hot char surface in the reactor.50−53 Few secondary reactions occur in our MFBR for the high fluidization gas flow rate (gas-phase residence time of 1 s). 3.2. Statistical Analysis and Reproducibility of the Data. Triplicates MS spectra obtained for experiments conducted in three different operating conditions are presented in Supporting Information (see Figure S.2). They demonstrate the very good reproducibility of our SPI-MS analysis. 7368
DOI: 10.1021/acs.energyfuels.5b01803 Energy Fuels 2015, 29, 7364−7374
Article
Energy & Fuels
Figure 5. Classification of pyrolysis products: (a) time profiles of some typical markers from hemicelluloses, cellulose, and lignin during Douglas fir pyrolysis (cylinder 6 × 12 mm, 400 °C, Uf 2). Profiles of other markers for these four classes (hemicelluloses, cellulose, lignin 1 and 2) are provided in Supporting Information. Here only four selected components are presented for sake of clarity and brevity; (b) simplified mechanism of lignin conversion.
Figure 4. Representative SPI mass spectra from the pyrolysis of miscanthus with different shapes (at 400 °C, Uf1): (a) powder, 40− 100 μm, 50 mg; (b) pressed cylinder 6 × 12 mm.
wood. Furthermore, different temperatures (T1 and T2, 400 and 500 °C respectively) for Douglas fir and different shapes (cylinder and powder) for oak are differentiated by PCA. This means the temperature has the most impact on pyrolysis
make a distinction between the two woods and miscanthus, while PC2 completely differentiates the softwood and hard-
Table 2. Mass Assignments of the Main Products from Douglas Fir, Oak, and Miscanthus Pyrolysisa m/z
group
m/z
pyrolysis products
group
43 57 60 70 74 82 86 94 96
carbohydrates fragment carbohydrates fragment hydroxyacetaldehyde 2-butenal hydroxypropanal methylfuran ethyl-1-propenyl ether phenol furfural
C C C C C C H L2 C
138 140 142 144 148 150 152 154 162
L2 L2 C C L2 L1 L2 L2 C/L1
98 108 110 112 114 120 122 124 126
furfuryl alcohol/1,2-cyclopentanedione P-cresol 5-methylfurfural/catechol 2,5-furandione, 3-methyl-/cyclotene 3-hydroxy-2-penteno-1,5-lactone 4-vinylphenol (mis) dimethylphenol guaiacol 2-furaldehyde, 5-(hydroxymethyl) (dou and oak)/levoglucosenone (mis) 2,5-dimethyl-4-hydroxy-3(2h)-furanone (or isomer)
C L2 C/L2 C H/C L1 L2 L2 C
164 166 168 178 180 182 194 196 208
4-methylguaiacol 1,2-benzenediol, 3-methoxy 2-furanethanol, β-methoxy-(S) 1,4:3,6-dianhydro-α-D-glucopyranose p-coumaraldehyde 4-vinylguaiacol vanillin syringol levoglucosan (dou and oak)/ methoxycinnamaldehyde (mis) eugenol 4-propylguaiacol methylsyringol/vanillic acid coniferyl aldehyde/methyleugenol 4-vinylsyringol (oak and mis)/ coniferyl alcohol (dou) homovanillic acid/syringaldehyde phenol, 2,6-dimethoxy-4-(2-propenyl) acetosyringone sinapic aldehyde
C
210
sinapyl alcohol
L1
128
pyrolysis products
L1 L1 L2 L1 L1 L1/L2 L1 L1 L1
a
C: cellulose; H: hemicellulose; L1: lignin-1; L2: lignin-2 (see Figure 5 for the definition of lignin-1 and -2 species). Dou: if the product is specific to Douglas fir; oak: specific for oak; mis: for miscanthus. 7369
DOI: 10.1021/acs.energyfuels.5b01803 Energy Fuels 2015, 29, 7364−7374
Article
Energy & Fuels
comparison of all SPI-MS spectra, we found that the signal intensity of m/z 114 is especially high for oak powder, while the intensity of m/z 110 increases significantly from powder to cylinder for both oak and miscanthus (but not for Douglas fir). High loading values at PC2 for m/z 138 and 150 are related to the higher content in G (guaiacyl) groups for softwood and correlate with Douglas fir. The effect of inorganic content (which is higher in miscanthus) can also explain some differentiation between the biomasses especially on carbohydrates markers (m/z 144, 128, 126, etc.). This will be discussed further in the next section. All these findings are in very good agreement with a previous study.5 Nevertheless, the effect of pyrolysis conditions (temperature, particle size, etc.) cannot be well differentiated if all the biomasses are analyzed together in the same PCA because biomass composition has a higher effect on the markers (and on the score plots) than the pyrolysis conditions. For this reason, distinct PCA analyses for each biomass are presented in the following section. 3.4. Combined Effect of Particle Geometry, Temperature, and Fluidization Velocity on Three Biomasses Pyrolysis. 3.4.1. Effect of Particle Geometry, Temperature, and Fluidization Velocity on Douglas Fir Pyrolysis. Figure 2 depicts the SPI-MS spectra of Douglas fir with different shapes pyrolyzed at 400 °C and at the gas flow rate of 670 mL/min. A significant difference of volatiles composition between Douglas fir cylinder and powder is found. Peaks at m/z 124, 128, and 138 show relatively higher signal intensities in cylinder spectra, while the relative signal intensities of m/z 126 and 144 are higher in powder spectra. There is no obvious difference in SPIMS spectra between 6 × 12 mm and 6 × 20 mm cylinder Douglas fir highlighting the little effect of mass transfers within the direction of wood fibers (under these investigated pyrolysis conditions). Furthermore, the SPI-MS spectrum of 0.5 × 12 mm lamella is similar to the one of cylinder, whereas the peak maxima over time are similar for powders and lamella, and much more delayed in the case of cylinders. These observations would tend to prove that the heat transfers are similar in lamella and powders and that their SPI-MS differences are due to secondary reactions that may happen along the length of particles (that is much longer in the case of lamella: 12 mm instead of about 0.1 mm for powders). PCA results for all Douglas fir volatiles are shown in Figure S.4 (Supporting Information). The first PC accounts for 60% of the total spectral variation and the second PC for 27%. Compared with the PCA in Figure 6 (three biomasses), different temperatures (T1 and T2) and shapes (cylinder and powder) for Douglas fir volatiles can be more obviously separated in Figure S.4. The loadings plots show that m/z 126, 144 correlate with the low temperature (400 °C) and powder particles. The compound at m/z 128 has a high loadings value at PC2 and correlates with low temperature and cylinders, while m/z 124 seems to be a good marker for the high temperature regime (T2 - 500 °C) with a high loadings value on PC1. This can also be observed in mass spectra at different temperatures (see Figure S.5). To better interpret the differences in douglas volatiles composition for the various experimental conditions, distinct PCAs for carbohydrates and lignin markers are presented in Figure 7. Biplots for carbohydrate (top part) and lignin (bottom part) show that their PC1 defines 64% and 68%, respectively, while PC2 defines the same variance of 25%. PC1 correlates well with temperature in the carbohydrates biplot and shape of particles in the lignin biplot. It is quite clear that temperature rather than shape has more effect on carbohydrates
Figure 6. PCA of SPI mass spectra of all investigated biomasses and process conditions. Abbreviations: (1) D, douglas; M, miscanthus, O, oak (2) C1, cylinder 6 × 12 mm; C2, cylinder 6 × 20 mm; L, lamella 0.5 × 12 mm, P, powder (3) T1, 400 °C; T2, 500 °C (4) B, big flow rate (Uf1); M, middle flow rate (Uf 2); S, small flow rate (Uf 3).
behavior of Douglas fir, whereas the one of oak is most affected by their shapes. In the case of miscanthus pyrolysis, SPI-MS spectra with different sample shapes and pyrolysis temperatures are not well distinguished in Figure 6. This will be discussed later in the following section. It is worth mentioning that three points marked with DPT2M, OPT2M, and MPT2M are separated from other points (in the scores plots), and they are always at the right to the other points from powder pyrolysis. This suggest that the fluidizing gas rate has an effect on powder biomass pyrolysis, but it mainly happened at 500 °C and not at 400 °C (see DPT1M, OPT1M, and MPT1M). This may be explained by secondary reactions that could be promoted when the sand temperature is set at 500 °C (see temperature profile in Supporting Information) and when the residence time is increased from 1 s (big flow rate of 670 mL/ min) to 2.4 s (300 mL/min fluidizing flow rate).54,55 Secondary reactions are not significant at the low temperature (400 °C in the sand) even for our highest gas-phase residence times. The loading values reflect the variance of related compounds that are responsible for grouping the samples along the different PCs. As shown in the loadings plot, there are high loadings values for m/z 120 (positive value) and m/z 114 (negative value) at PC1 and for m/z 138, m/z 150 (positive value), and m/z 194 (negative value) at PC2. High loadings values in the loading plot for m/z 120 correlates with miscanthus, which is distributed in the right in the scores plot (important contribution of m/z 120 for PC1). Peaks at m/ z 194, 154, and 180 (syringyl species) can be correlated to oak (in the negative part, bottom part of PC2), which is a hardwood with a high content in syringyl groups. After 7370
DOI: 10.1021/acs.energyfuels.5b01803 Energy Fuels 2015, 29, 7364−7374
Article
Energy & Fuels
(400 °C) but with high flow rate (low gas-phase residence time, secondary reactions not significant) and powder samples. Therefore, the formation of these species is promoted by a faster heating rate that favors a higher pyrolysis temperature range. These labile species may be also converted in the hot nascent char in bigger particles (cylinders). This regime (powders, 400 °C) is also well correlated with m/z 164, 150, 178 in the lignin biplot (lignin-1 markers). (C) The third “pyrolysis regime” corresponds to the high temperature pyrolysis (500 °C) of powder particle. This is the fast heating rate and high temperature regime. This regime is even amplified if the flow rate of carrier gas is decreased (more secondary reactions). This regime is correlated mainly with m/z 98, 110 (carbohydrates markers) and with m/z 124 (lignin marker, guaiacol). The effect of gas flow rates on Douglas fir pyrolysis does not have the most significant effect (see Figure 7 or Figure S.4), but at least two effects can be described as follows: (1) at low temperature of 400 °C, the gas flow rate has almost no effect on the cylinder for Douglas fir pyrolysis, whose loadings are always gathered together in the biplot (see DC1T1B, DC1T1M, DC1T1S, and DC2T1B); (2) the influence of gas flow rate on Douglas fir pyrolysis becomes distinct when MFBR temperature is raised to 500 °C, especially for powder samples (DPT2B vs DPT2M). 3.4.2. Effect of Particle Geometry, Temperature, and Fluidization Velocity on Oak Pyrolysis. Figure 3 shows the SPI-MS spectra of oak with different shapes pyrolyzed at 400 °C and at gas flow rate of 670 mL/min. A big difference in SPIMS spectra between powder and cylinder could be seen, and peaks with visible changes have been marked with the star symbol. Compared to the SPI-MS spectra of Douglas fir cylinders, the ones of powder show relatively higher signal intensities at m/z 114, 126, and 144, but lower signal intensity at m/z 98, 110, 124, 138, 140, 154, 168, 182, and 194. Just like Douglas fir, there is no significant difference in SPI-MS spectra between 6 × 12 mm and 6 × 20 mm cylinder oak showing that mass transfers within the direction of the fiber do not have a significant effect on volatiles composition for oak cylinders. The SPI-MS spectrum of oak lamella is similar to the one of oak powder. In other words, mass and heat transfers’ conditions for oak lamella and oak powder yield similar products. This was not the case for Douglas fir (lamella is similar to cylinder). This is an interesting result. It may be easier for the volatiles to escape from oak lamella than from Douglas fir lamella. The PCA for oak samples is shown in Figure S.6 (Supporting Information). Unlike PCA results for Douglas fir, the biplot for oak shows that 86% of the total variance can be explained by PC1. PC2 defines a very minor part of the total variance (7%). PC1 mainly correlates with the effect of particle size and not with temperature or fluidization flow rate. The small particles group (powder and lamella) correlate with m/z 114, 144, 126 (high positive loadings values) and the cylinder group with m/z 154, 110, 124 (negative loadings values). Distinct PCA for carbohydrates and lignin markers are presented in Figure 8 to better understand the different pyrolysis regimes for oak similarly to Douglas fir. Concerning carbohydrate products, PC1 accounts for 88% of the total variance. PC2 defines a very minor part of the total variance (5%); hence it is not very significant and will not be further discussed. PC1 exhibits very clearly two pyrolysis regimes (and not three regimes as for Douglas fir): (1) at positive loadings values for m/z 114 and 144 (species
Figure 7. Distinct PCA of SPI-MS spectra of carbohydrates and lignin products from Douglas fir pyrolysis.
volatiles. But in the case of lignin volatiles, temperature has little effect. This may be explained by the more fragile chemical structure of carbohydrates volatiles compared to the one of lignin volatiles. From PCA results in Figure 7, three pyrolysis regimes could be defined as follows: (A) m/z 128 and 142 located on the upper-left of biplot, indicating that these two carbohydrate volatiles are much more easily formed in cylinder samples at lower temperature. This is probably because m/z 128 and 142 exhibit fragile chemical structures and are very sensitive to temperature. This may be also the reason why these two compounds are always difficult to be detected by GC-MS with a high-temperature injection of condensed products which may convert these compounds.36,48 The importance of m/z 128 and 142 for pyrolysis mechanisms highlights the interest of our online soft ionization MS analysis. Heat transfers into the cylinders also decrease the overall temperature of pyrolysis and promote the formation of species with lower activation energy in their kinetic rate of formation. The similar pyrolysis regime (cylinder, 400 °C) is also well correlated with m/z 138 as lignin marker. (B) m/z 144 and 126 are located on the bottom-left side in the biplots (negative loadings values for both PC1 and PC2). These two markers are more favored also by low temperature 7371
DOI: 10.1021/acs.energyfuels.5b01803 Energy Fuels 2015, 29, 7364−7374
Article
Energy & Fuels
rate of lignin volatiles, but they may also be less in the vicinity of the lignin macromolecules than they are for carbohydrates. Regarding the effect of gas flow rate on oak pyrolysis, very similar results as Douglas fir pyrolysis are obtained. At a low temperature of 400 °C, the gas flow rate has very little effect on the cylinder pyrolysis because they are gathered together in the biplot (see OC1T1B, OC1T1M, OC1T1S, and OC2T1B). However, this effect becomes more intense as the temperature increases to 500 °C, especially for powder samples (OPT2B vs OPT2M). 3.4.3. Effect of Particle Geometry, Temperature and Fluidization Velocity on Miscanthus Pyrolysis. The SPI-MS spectra of miscanthus with two particle types (pellet and powder) pyrolyzed at a MFBR of 400 °C and with a gas flow rate of 670 mL/min are depicted in Figure 4. Similarly to oak pyrolysis, signal intensities of peaks at m/z 110, 124, 138, 140, and 154 are more intense in the pellet than in powder, while the ones of m/z 114 and 162 are weaker. Compared to Douglas fir and oak, the powder sample of miscanthus produces volatiles with a high intensity of m/z 162 but very low intensity of m/z 144. We infer that m/z 162 may rather correspond to a lignin-1 type marker for miscanthus, as we mentioned before. PCAs for carbohydrates and lignin volatiles from miscanthus pyrolysis are presented in Figure S.7 (Supporting Information). PC1 accounts for 86% and 82% of the total variation for carbohydrates and lignin volatiles, respectively. PC2 defines 8% and 10% of the total variance for carbohydrates and lignin volatiles, respectively. PC2 is much less significant than PC1 for both lignin and carbohydrates. Similarly, miscanthus exhibits two regimes of pyrolysis as oak for carbohydrate products: (1) for the cylinder (pellet) correlated with negative loadings values of m/z 110 and 112; (2) for the powder correlated with m/z 114, 98, and 126. Concerning lignin products, the same two regimes are observed with m/z 124, 138 (cylinder), and mainly m/z 120 (powder) as the main markers. This result confirms the effect of inorganic species on the pyrolysis regime. Miscanthus has a higher content in inorganic materials (K, Ca, and Mg) than oak and Douglas fir (see Table S.2). Their catalytic effect reduces the effect of temperature on products composition. The cylinder promotes (compared to the powder) the formation of lignin-2 species (m/z 124 and 138) and the formation of m/z 110 (5-methylfurfural), which is a secondary product from 5-hydroxymethylfurfural (m/z 126). This could be explained by a combined effect of heat transfers and of secondary reactions. Secondary reactions may be promoted in cylinders due to a higher contact time of the volatiles with the hot nascent tar (than in the powder).
Figure 8. Distinct PCA of SPI-MS spectra of carbohydrates (top) and lignin (bottom) products from oak pyrolysis.
promoted by a fast heating rate) which correlate with small particles (powder and lamella) whatever the temperature or gas flow-rate; (2) at negative loadings values for m/z 110 and 112 for cylinders. The effect of temperature is much less significant on oak carbohydrate products compared with Douglas fir ones for the two following potential reasons: (1) Oak has a higher thermal conductivity than Douglas fir, leading to faster intraparticle heat transfers thus reducing the intraparticle thermal lag (for big particles); (2) Oak has a higher content in inorganic materials (mainly K and Ca) than Douglas fir (see Table S.2). The catalytic effect of inorganic materials is thus promoted for oak and may reduce the activation energies for primary species formation. Therefore, it may reduce the effect of temperature. Concerning the PCA for lignin markers, PC1 and PC2 account for 63% and 31% of the total variance, respectively. PC2 is here more significant than the PC2 for carbohydrate products. Lignin markers for oak exhibit a similar behavior as for Douglas fir with the three regimes of pyrolysis: (A) Regime related to cylinders at 400 °C correlated with m/ z 154, 168, and 182 (negative loadings values for both PC1 and PC2); (B) Regime related to powder at 400 °C correlated with m/z 180, 194, and 208 (lignin-1 markers, positive loadings values for PC1); (C) Regime related to powder at 500 °C correlated with m/z 124 and 138 (lignin-2 markers, negative loadings values for PC1 and positive for PC2). The different feature of lignin compared with the carbohydrates in oak may be explained by a lower catalytic effect of inorganic materials for lignin markers. Inorganic materials may have a lower chemical effect on the formation
4. CONCLUSION The fast pyrolysis of three types of biomass (Douglas fir, oak, and miscanthus) has been conducted in a microfluidized bed reactor, and their pyrolysis products were measured online by a time-of-flight mass spectrometer equipped with a soft photoionization source. Most of detected m/z peaks have been assigned to a molecular structure from GC/MS analysis. The SPI-MS spectra as a function of biomass type, particle shape and size, sand temperature, and fluidizing gas flow rate were compared by the PCA method. The main conclusions related to the changes in SPI-MS spectra with a total of 28 conditions can be summarized as follows: (1) The three types of biomasses can be clearly differentiated by PCA regardless of the other pyrolysis conditions (temperature, particle size, or fluidization flow rate). The main markers 7372
DOI: 10.1021/acs.energyfuels.5b01803 Energy Fuels 2015, 29, 7364−7374
Article
Energy & Fuels to differentiate Douglas fir, miscanthus, and oak are m/z 120 (4-vinylphenol marker of miscanthus), 138 (4-methylguaiacol, marker of guaiacyl groups in Douglas fir), and 194 (2,6dimethoxy-4-(2-propenyl)-phenol, marker of syringyl groups in oak). (2) Three pyrolysis regimes can be defined for Douglas fir pyrolysis on both carbohydrates and lignin products. These three regimes are mainly characterized by m/z 128 (2,5dimethyl-4-hydroxy-3(2h)-furanone, marker for “cylinder400°C” regime), 144 (fragment from levoglucosan, marker for “powder-400°C” regime), and 110 (5-methylfurfural, marker for “powder-500°C”). (3) Only two pyrolysis regimes can be defined for oak carbohydrates products and for miscanthus carbohydrates and lignin products due to the dominant catalytic effect of inorganic materials on products composition. SPI-MS combined with a MFBR is an interesting method to study the mechanism of biomass pyrolysis since it avoids the condensation of bio-oil for liquid sampling followed by high temperature injection in GC/MS. This sampling procedure can alter the chemical structure of some compounds (e.g., m/z 128). This method could be applied to the thermal decomposition of all other carbonaceous solids. These results could also be used to further optimize biomass fast pyrolysis in fluidized bed reactors or in other devices to targeted products.
■
from the conversion of cellulose, hemicelluloses and lignin. Renewable Sustainable Energy Rev. 2014, 38, 594−608. (2) Lede, J.; Authier, O. Temperature and heating rate of solid particles undergoing a thermal decomposition. Which criteria for characterizing fast pyrolysis? J. Anal. Appl. Pyrolysis 2015, 113, 1−14. (3) Mohan, D.; Pittman, C. U.; Steele, P. H. Pyrolysis of wood/ biomass for bio-oil: A critical review. Energy Fuels 2006, 20 (3), 848− 889. (4) Bahng, M.-K.; Mukarakate, C.; Robichaud, D. J.; Nimlos, M. R. Current technologies for analysis of biomass thermochemical processing: A review. Anal. Chim. Acta 2009, 651 (2), 117−138. (5) Fendt, A.; Streibel, T.; Sklorz, M.; Richter, D.; Dahmen, N.; Zimmermann, R. On-line process analysis of biomass flash pyrolysis gases enabled by soft photoionization mass spectrometry. Energy Fuels 2012, 26 (1), 701−711. (6) Xiong, Q. G.; Aramideh, S.; Kong, S. C. Modeling effects of operating conditions on biomass fast pyrolysis in bubbling fluidized bed reactors. Energy Fuels 2013, 27 (10), 5948−5956. (7) Yu, J.; Yao, C. B.; Zeng, X.; Geng, S.; Dong, L.; Wang, Y.; Gao, S. Q.; Xu, G. W. Biomass pyrolysis in a micro-fluidized bed reactor: Characterization and kinetics. Chem. Eng. J. 2011, 168 (2), 839−847. (8) Liu, X. H.; Xu, G. W.; Gao, S. Q. Micro fluidized beds: Wall effect and operability. Chem. Eng. J. 2008, 137 (2), 302−307. (9) Yu, J. A.; Yue, J. R.; Liu, Z. E.; Dong, L.; Xu, G. W.; Zhu, J. H.; Duan, Z. K.; Sun, L. X. Kinetics and mechanism of solid reactions in a micro fluidized bed reactor. AIChE J. 2010, 56 (11), 2905−2912. (10) Yu, J.; Zeng, X.; Zhang, J. W.; Zhong, M.; Zhang, G. Y.; Wang, Y.; Xu, G. W. Isothermal differential characteristics of gas-solid reaction in micro-fluidized bed reactor. Fuel 2013, 103, 29−36. (11) Garcia-Perez, M.; Wang, X. S.; Shen, J.; Rhodes, M. J.; Tian, F. J.; Lee, W. J.; Wu, H. W.; Li, C. Z. Fast pyrolysis of oil mallee woody biomass: Effect of temperature on the yield and quality of pyrolysis products. Ind. Eng. Chem. Res. 2008, 47 (6), 1846−1854. (12) Mourant, D.; Lievens, C.; Gunawan, R.; Wang, Y.; Hu, X.; Wu, L. P.; Syed-Hassan, S. S. A.; Li, C. Z. Effects of temperature on the yields and properties of bio-oil from the fast pyrolysis of mallee bark. Fuel 2013, 108, 400−408. (13) Zhou, S.; Garcia-Perez, M.; Pecha, B.; Kersten, S. R. A.; McDonald, A. G.; Westerhof, R. J. M. Effect of the fast pyrolysis temperature on the primary and secondary products of lignin. Energy Fuels 2013, 27 (10), 5867−5877. (14) Garcia-Perez, M.; Wang, S.; Shen, J.; Rhodes, M.; Lee, W. J.; Li, C.-Z. Effects of temperature on the formation of lignin-derived oligomers during the fast pyrolysis of Mallee woody biomass. Energy Fuels 2008, 22 (3), 2022−2032. (15) Kersten, S.; Garcia-Perez, M. Recent developments in fast pyrolysis of ligno-cellulosic materials. Curr. Opin. Biotechnol. 2013, 24 (3), 414−420. (16) Shen, J.; Wang, X. S.; Garcia-Perez, M.; Mourant, D.; Rhodes, M. J.; Li, C. Z. Effects of particle size on the fast pyrolysis of oil mallee woody biomass. Fuel 2009, 88 (10), 1810−1817. (17) Westerhof, R. J. M.; Nygard, H. S.; van Swaaij, W. P. M.; Kersten, S. R. A.; Brilman, D. W. F. Effect of particle geometry and microstructure on fast pyrolysis of beech wood. Energy Fuels 2012, 26 (4), 2274−2280. (18) Zhou, S.; Garcia-Perez, M.; Pecha, B.; McDonald, A. G.; Westerhof, R. J. M. Effect of particle size on the composition of lignin derived oligomers obtained by fast pyrolysis of beech wood. Fuel 2014, 125, 15−19. (19) Salehi, E.; Abedi, J.; Harding, T. Bio-oil from sawdust: Effect of operating parameters on the yield and quality of pyrolysis products. Energy Fuels 2011, 25 (9), 4145−4154. (20) Kersten, S. R. A.; Wang, X.; Prins, W.; van Swaaij, W. P. M. Biomass pyrolysis in a fluidized bed reactor. Part 1: Literature review and model simulations. Ind. Eng. Chem. Res. 2005, 44 (23), 8773− 8785. (21) Haas, T. J.; Nimlos, M. R.; Donohoe, B. S. Real-time and postreaction microscopic structural analysis of biomass undergoing pyrolysis. Energy Fuels 2009, 23 (7), 3810−3817.
ASSOCIATED CONTENT
S Supporting Information *
The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.energyfuels.5b01803. Composition of biomass samples (sugars and lignin, minerals); char yields for cylinders; time profiles of main markers from carbohydrates and lignin; mass spectra and PCA analysis from triplicate experiments showing the good reproducibility of our methodology for three different conditions; PCA analysis of all investigated products for Douglas fir and oak pyrolysis; SPI mass spectra showing the effect of temperature for Douglas fir pyrolysis; distinct PCA of SPI MS of carbohydrates and lignin products from miscanthus pyrolysis; temperature profile in the MFBR (PDF)
■
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS The financial support from the ANR French agency through the project “PYRAIM” is gratefully acknowledged. Funding from Europe (FEDER), the French State and Lorraine Region through the project CPER MEPP is also kindly acknowledged for a part of the purchase of the PI-TOFMS system at CNRSNancy. We also wish to thank Michel Mercy (CNRS, Nancy) for his technical support and kind help with some experimental measurements.
■
REFERENCES
(1) Collard, F.-X.; Blin, J. A review on pyrolysis of biomass constituents: Mechanisms and composition of the products obtained 7373
DOI: 10.1021/acs.energyfuels.5b01803 Energy Fuels 2015, 29, 7364−7374
Article
Energy & Fuels
micro fluidized bed reactor analyzer. Bioresour. Technol. 2015, 181, 155−162. (41) Zhang, Y. M.; Yao, M. Q.; Sun, G. G.; Gao, S. Q.; Xu, G. W. Characteristics and kinetics of coked catalyst regeneration via steam gasification in a micro fluidized bed. Ind. Eng. Chem. Res. 2014, 53 (15), 6316−6324. (42) Muhlberger, F.; Wieser, J.; Morozov, A.; Ulrich, A.; Zimmermann, R. Single-photon ionization quadrupole mass spectrometry with an electron beam plumped excimer light source. Anal. Chem. 2005, 77 (7), 2218−2226. (43) Vinciguerra, V.; Spina, S.; Luna, M.; Petrucci, G.; Romagnoli, M. Structural analysis of lignin in chestnut wood by pyrolysis-gas chromatography/mass spectrometry. J. Anal. Appl. Pyrolysis 2011, 92 (2), 273−279. (44) Labbe, N.; Rials, T. G.; Kelley, S. S.; Cheng, Z. M.; Kim, J. Y.; Li, Y. FT-IR imaging and pyrolysis-molecular beam mass spectrometry: new tools to investigate wood tissues. Wood Sci. Technol. 2005, 39 (1), 61−76. (45) Gaston, K. R.; Jarvis, M. W.; Pepiot, P.; Smith, K. M.; Frederick, W. J.; Nimlos, M. R. Biomass pyrolysis and gasification of varying particle sizes in a fluidized-bed reactor. Energy Fuels 2011, 25 (8), 3747−3757. (46) Trendewicz, A.; Evans, R.; Dutta, A.; Sykes, R.; Carpenter, D.; Braun, R. Evaluating the effect of potassium on cellulose pyrolysis reaction kinetics. Biomass Bioenergy 2015, 74, 15−25. (47) Bahng, M.-K.; Donohoe, B. S.; Nimlos, M. R. Application of an fourier transform-infrared imaging tool for measuring temperature or reaction profiles in pyrolyzed wood. Energy Fuels 2011, 25, 370−378. (48) Evans, R. J.; Milne, T. A. Molecular characterization of the pyrolysis of biomass 0.1. Fundamentals. Energy Fuels 1987, 1 (2), 123−137. (49) Sharma, R. K.; Wooten, J. B.; Baliga, V. L.; Lin, X. H.; Chan, W. G.; Hajaligol, M. R. Characterization of chars from pyrolysis of lignin. Fuel 2004, 83 (11−12), 1469−1482. (50) Scott, D. S.; Majerski, P.; Piskorz, J.; Radlein, D. A second look at fast pyrolysis of biomass - the RTI process. J. Anal. Appl. Pyrolysis 1999, 51 (1−2), 23−37. (51) Ranzi, E.; Cuoci, A.; Faravelli, T.; Frassoldati, A.; Migliavacca, G.; Pierucci, S.; Sommariva, S. Chemical kinetics of biomass pyrolysis. Energy Fuels 2008, 22 (6), 4292−4300. (52) Stiles, H. N.; Kandiyoti, R. Secondary reactions of flash pyrolysis tars measured in a fluidized-bed pyrolysis reactor with some novel design-features. Fuel 1989, 68 (3), 275−282. (53) Boroson, M. L.; Howard, J. B.; Longwell, J. P.; Peters, W. A. Heterogeneous cracking of wood pyrolysis tars over fresh wood char surfaces. Energy Fuels 1989, 3 (6), 735−740. (54) Shin, E. J.; Nimlos, M. R.; Evans, R. J. Kinetic analysis of the gasphase pyrolysis of carbohydrates. Fuel 2001, 80 (12), 1697−1709. (55) Heo, H. S.; Park, H. J.; Yim, J. H.; Sohn, J. M.; Park, J.; Kim, S. S.; Ryu, C.; Jeon, J. K.; Park, Y. K. Influence of operation variables on fast pyrolysis of Miscanthus sinensis var. purpurascens. Bioresour. Technol. 2010, 101 (10), 3672−3677.
(22) Hossain, M. M.; Scott, I. M.; Berruti, F.; Briens, C. Optimizing pyrolysis reactor operating conditions to increase nicotine recovery from tobacco leaves. J. Anal. Appl. Pyrolysis 2015, 112, 80−87. (23) Kanaujia, P. K.; Sharma, Y. K.; Agrawal, U. C.; Garg, M. O. Analytical approaches to characterizing pyrolysis oil from biomass. TrAC, Trends Anal. Chem. 2013, 42, 125−136. (24) Reale, S.; Di Tullio, A.; Spreti, N.; De Angelis, F. Mass spectrometry in the biosynthetic and structural investigation of lignins. Mass Spectrom. Rev. 2004, 23 (2), 87−126. (25) Akalin, M. K.; Karagoz, S. Analytical pyrolysis of biomass using gas chromatography coupled to mass spectrometry. TrAC, Trends Anal. Chem. 2014, 61, 11−16. (26) Jarvis, M. W.; Haas, T. J.; Donohoe, B. S.; Daily, J. W.; Gaston, K. R.; Frederick, W. J.; Nimlos, M. R. Elucidation of biomass pyrolysis products using a laminar entrained flow reactor and char particle imaging. Energy Fuels 2011, 25 (1), 324−336. (27) Shin, E. J.; Nimlos, M. R.; Evans, R. J. A study of the mechanisms of vanillin pyrolysis by mass spectrometry and multivariate analysis. Fuel 2001, 80 (12), 1689−1696. (28) Carpenter, D. L.; Deutch, S. P.; French, R. J. Quantitative measurement of biomass gasifier tars using a molecular-beam mass spectrometer: Comparison with traditional impinger sampling. Energy Fuels 2007, 21 (5), 3036−3043. (29) Cole, D. P.; Smith, E. A.; Lee, Y. J. High-resolution mass spectrometric characterization of molecules on biochar from pyrolysis and gasification of switchgrass. Energy Fuels 2012, 26 (6), 3803−3809. (30) Liu, Y.; Shi, Q.; Zhang, Y. H.; He, Y. L.; Chung, K. H.; Zhao, S. Q.; Xu, C. M. Characterization of red pine pyrolysis bio-oil by gas chromatography-mass spectrometry and negative-ion electrospray ionization fourier transform ion cyclotron resonance mass spectrometry. Energy Fuels 2012, 26 (7), 4532−4539. (31) Jarvis, J. M.; McKenna, A. M.; Hilten, R. N.; Das, K. C.; Rodgers, R. P.; Marshall, A. G. Characterization of pine pellet and peanut hull pyrolysis bio-oils by negative-ion electrospray ionization fourier transform ion cyclotron resonance mass spectrometry. Energy Fuels 2012, 26 (6), 3810−3815. (32) Abdelnur, P. V.; Vaz, B. G.; Rocha, J. D.; de Almeida, M. B. B.; Teixeira, M. A. G.; Pereira, R. C. L. Characterization of bio-oils from different pyrolysis process steps and biomass using high-resolution mass spectrometry. Energy Fuels 2013, 27 (11), 6646−6654. (33) Olcese, R.; Carre, V.; Aubriet, F.; Dufour, A. Selectivity of biooils catalytic hydrotreatment assessed by petroleomic and gc*gc/msfid analysis. Energy Fuels 2013, 27 (4), 2135−2145. (34) Brown, A. L.; Dayton, D. C.; Nimlos, M. R.; Daily, J. W. Characterization of biomass pyrolysis vapors with molecular beam, single photon ionization time-of-flight mass spectrometry. Chemosphere 2001, 42 (5−7), 663−669. (35) Genuit, W.; Boon, J. J.; Faix, O. Characterization of beech milled wood lignin by pyrolysis-gas chromatography photoionization massspectrometry. Anal. Chem. 1987, 59 (3), 508−513. (36) Dufour, A.; Weng, J. J.; Jia, L. Y.; Tang, X. F.; Sirjean, B.; Fournet, R.; Le Gall, H.; Brosse, N.; Billaud, F.; Mauviel, G.; Qi, F. Revealing the chemistry of biomass pyrolysis by means of tunable synchrotron photoionisation-mass spectrometry. RSC Adv. 2013, 3 (14), 4786−4792. (37) Weng, J.; Jia, L.; Wang, Y.; Sun, S.; Tang, X.; Zhou, Z.; KohseHoeinghaus, K.; Qi, F. Pyrolysis study of poplar biomass by tunable synchrotron vacuum ultraviolet photoionization mass spectrometry. Proc. Combust. Inst. 2013, 34, 2347−2354. (38) Fendt, A.; Geissler, R.; Streibel, T.; Sklorz, M.; Zimmermann, R. Hyphenation of two simultaneously employed soft photo ionization mass spectrometers with thermal analysis of biomass and biochar. Thermochim. Acta 2013, 551, 155−163. (39) Zeng, X.; Wang, F.; Wang, Y. G.; Li, A. M.; Yu, J.; Xu, G. W. Characterization of char gasification in a micro fluidized bed reaction analyzer. Energy Fuels 2014, 28 (3), 1838−1845. (40) Mao, Y. B.; Dong, L.; Dong, Y. P.; Liu, W. P.; Chang, J. F.; Yang, S.; Lv, Z. C.; Fan, P. F. Fast co-pyrolysis of biomass and lignite in a 7374
DOI: 10.1021/acs.energyfuels.5b01803 Energy Fuels 2015, 29, 7364−7374
