Complementary Analysis of the Water-Soluble and Water-Insoluble

6 days ago - Article Options. ACS ActiveView PDF. Hi-Res Print, Annotate, Reference QuickView. PDF (2871 KB) · PDF w/ Links (480 KB) · Full Text HTML ...
0 downloads 8 Views 3MB Size
Download PDF
Article Cite This: Energy Fuels XXXX, XXX, XXX−XXX

pubs.acs.org/EF

Complementary Analysis of the Water-Soluble and Water-Insoluble Fraction of Catalytic Fast Pyrolysis Biocrudes by Two-Dimensional Gas Chromatography Mette Kristensen,*,† Asger B. Hansen,‡ Ofei D. Mante,§ David C. Dayton,§ Sylvain Verdier,‡ Peter Christensen,† and Jan H. Christensen† †

Department of Plant and Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871 Frederiksberg C, Denmark Haldor Topsoe A/S, Haldor Topsoes Allé 1, 2800 Kgs. Lyngby, Denmark § RTI International, Center for Energy Technology, 2040 Cornwallis Road, Research Triangle Park, North Carolina 27709, United States ‡

S Supporting Information *

ABSTRACT: Catalytic fast pyrolysis (CFP) biocrudes are of interest in the search for renewable energy and fuel. Depending on the process conditions, the produced biocrude can contain low to high percentage of oxygenates such as polyphenols, aldehydes/ ketones, furan derivatives, acids, and sugars. The presence of these oxygenates leads to difficulties in handling, storage, and downstream processing. A better understanding of the chemical composition of biocrudes produced under different conditions, and their reactivity in the hydrotreatment process, is required to optimize the CFP process. In this study, we perform a comprehensive characterization of five biocrude samples from loblolly pine (pinus taeda), produced under different CFP conditions, by fractionation, automatic precolumn derivatization, and comprehensive two-dimensional gas chromatography (GC × GC). The findings show that sample fractionation simplifies the chromatograms by separating the biocrudes into fractions based on polarity. Additionally, fractionation and derivatization enable the analysis of polar oxygenates (e.g., acids and sugars) that are present in low relative amounts in the biocrudes. In general, the use of complementary GC × GC methods resulted in separation and detection of compounds in a wide polarity range and enabled the detection of polar oxygenates in the biocrude samples.

1. INTRODUCTION

The chemical complexity of bio-oils is epitomized by a broad distribution of boiling points and molecular weights of the compounds and by thermal instability due to highly reactive compounds. Consequently, one single analytical method cannot be used to comprehensively and quantitatively characterize biooils.1 Gas chromatography with mass spectrometric detection (GC-MS) is the preferred analytical method for mineral oil characterization, and it has also been used extensively for analysis of bio-oils. 2,8 However, since the beginning of 2000, comprehensive two-dimensional gas chromatography (GC × GC) has been used to improve compound separation, peak capacity, and sensitivity.9 GC × GC improves the characterization by better separating compounds that are coeluting in onedimensional GC. Additionally, high-resolution mass spectrometry (HR-MS), such as high-resolution time-of-flight mass spectrometry (HR-TOF-MS), further improves the sensitivity and facilitates compound identification. GC × GC-FID, GC × GC-MS,9−13 and GC × GC-HR-MS14 have, in several studies, been shown to be suitable methods for identifying compounds in bio-oils. Marsman et al. (2008) analyzed one flash pyrolysis oil and two hydrodeoxygenated pyrolysis oils (HDO oils) by GC × GC-MS. They found that benzenediols, mono- and dimethoxy phenols, aldehydes, and esters of organic acids were the major

The demand for renewable energy sources, and fuels for transportation, results in a strong interest in production and analysis of bio-oils. Bio-oils can be formed by various thermal processes: one is catalytic fast pyrolysis (CFP), where the biomass is reacted in the presence of a suitable catalyst at moderate to high temperatures in the absence of oxygen. In the CFP process, large biopolymers, mainly lignin, cellulose, and hemicellulose, undergo cracking, depolymerization, and deoxygenation. This results in a dark liquid composed of a complex mixture of smaller compounds.1,2 The chemical composition of biocrudes depends on the feedstock, catalyst, and the pyrolysis conditions. Typically, CFP results in the formation of aromatic hydrocarbons due to the promotion of extensive deoxygenation reactions. However, promotion of partial deoxygenation during CFP of biomass results in the formation of various oxygenated compounds, including sugars and anhydrosugars, hydroxyaldehydes, hydroxyketones, carboxylic acids, and phenolic compounds.1,3 The presence of oxygenates in the biocrude contributes to poor fuel quality (low energy content, poor volatility, high viscosity, corrosivity, and instability), which eventually complicates storage, transportation, and upgrading of bio-oils.1,4−7 Despite these complications, production of bio-oils is expected to contribute to an ever increasing global energy demand. © XXXX American Chemical Society

Received: February 1, 2018 Revised: April 5, 2018 Published: April 8, 2018 A

DOI: 10.1021/acs.energyfuels.8b00415 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels Table 1. Sample Information and CFP Parameters for Biocrudes F1−F5 sample

F1

F2

F3

F4

F5

fraction CFP severity, °C average apparent vapor residence time in the mixing zone, s moisture content, wt %a S, wt %b N, wt ppmc H, wt %d O, wt %e C, wt %f sum H, C, N, S, O

light 520 1.41 8.0 0.027 708.22 8.3 17 73.9 99.3

heavy 465 1.00 8.93 0.00661 682.58 6.74 14.9 72.75 94.5

15% light + 85% heavy 520 1.41 9.35 0.01081 986.67 7.3 25.5 64.5 97.5

15% light + 85% heavy 520 1.41 9.85 0.01018 966.94 7.02 28 62.9 98.0

heavy 575 0.75 10.38 0.00582 N.D. 6.49 28.75 62.6 97.8

a f

ASTM method E203. bASTM method D4294. cASTM method D5762 or D4629. dASTM method D7171. ePerkinElmer 2400 Series II analyzer. ASTM method D5291. The nitrogen content in F5 could not be detected (N.D.) by ASTM method D5762 or D4629.

developed, validated, and tested a GC × GC-HR-MS method with automatic precolumn BSTFA derivatization.

components of these bio-oils. The HDO oils consisted of high amounts of cyclic hydrocarbons and alkylated phenolic derivatives.9 Torri et al. (2016) analyzed the composition of hardwood and softwood waste bio-oils by GC-MS and GC × GC-MS. They found that phenols and ketones were the dominant compounds and that GC × GC-MS analysis could more comprehensively characterize the bio-oils.10 Ristic et al. (2017) further concluded that GC × GC with a 1D polar column and a 2D nonpolar column gave better separation of oxygencontaining compounds in an Estonian pyrolysis shale oil than GC × GC with a nonpolar 1D column and a polar 2D column.15 Phenols and ketones were also found to be the major components of rice husk and peach pit bio-oils in a study by Moraes et al. (2012). Furthermore, Faccini et al. (2013) concluded that phenolic compounds were the major components in bio-oils produced from sawdust and diester residues.11,16 To improve upgrading of bio-oils, it is important to be able to characterize the bio-oils as comprehensively as possible. The large and complex fraction of oxygenates, both in the CFP feeds and in hydrotreated products, is difficult to analyze by GC-MS and GC × GC-MS, as many oxygenates require derivatization to become GC compatible. Derivatization facilitates the GC analysis by improving the thermal stability of polar molecules and by reducing undesirable reactions with the column stationary phase and the liner.17 Silylation is a common reaction type for derivatization and works by replacing active hydrogens with silyl groups. A versatile silylation agent is N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA). In BSTFA derivatization, the trimethylsilyl (TMS) group replaces the active hydrogen in alcohols, acids, amines, amides, and thiols.17 Derivatization has been used to analyze levoglucosan,18 various carbohydrates,19 and organic liquid products formed under thermal cracking.20 However, derivatization has not previously been applied in combination with GC × GC-HR-MS for the analysis of plantbased bio-oils. In this study, five biocrude samples from loblolly pine (Pinus taeda) with varying oxygen content (14.9−28.8 wt %), but produced under different CFP conditions, were characterized by complementary GC × GC methods. The characterization focuses on compound identification and detection of main relative concentration differences between the biocrudes. Samples were fractionated into water-soluble (WS) and waterinsoluble (WIS) fractions for comprehensive analysis of the biocrudes. The WIS fractions were analyzed by GC × GC with two types of detectors: flame ionization detection (FID) and mass spectrometric detection (MS). For further identification and characterization of polar oxygenates in the WS fractions, we

2. MATERIALS AND METHODS 2.1. Chemicals. Toluene (glass distilled grade, Rathburn), methanol (MeOH) (HPLC grade, Rathburn), dichloromethane (DCM) (HPLC grade, Rathburn), diethyl ether (DEE) (Sigma-Aldrich), and tetrahydrofuran (THF) (≥99.0%, Sigma-Aldrich) were used during the study. N,O-Bis(trimethylsilyl)trifluoroacetamide (BSTFA) (derivatization grade, Supelco) and anhydrous pyridine (99.8%, Sigma-Aldrich) were used for derivatization. Sylon CT 5% dimethyldichlorosilane (DMDCS) in toluene (Sigma-Aldrich) was used to deactivate all glassware before use, and molecular sieves (3 Å, Sigma-Aldrich) and solid potassium hydroxide (KOH) (56.11 g/mol, Merck) were used to dry reaction and washing solvents. A stock solution of five carboxylic acids was prepared in MeOH (CAMix): salicylic acid (22.45 μg/mL, >99%, Sigma-Aldrich), 1-naphthoic acid (19.28 μg/mL, 98%, Chiron), 1-hydroxy-2-naphthoic acid (20.00 μg/mL, 99%, Sigma-Aldrich), 2-carboxycinnamic acid (20.16 μg/mL, 97%, VWR), and 1-pyrene carboxylic acid (20.80 μg/mL, 97%, Sigma). The CA-Mix and a QC-Mix of all five CFP biocrudes (1 mg/mL in DCM:MeOH (1:1)) were used as quality control samples throughout the GC × GC-HR-MS analyses. The CA-Mix and D(+)-glucosemonohydrate (Merck) (0.87 mg/mL in pyridine) were used for validation of the derivatization method. 2.2. Samples. The sample set consisted of five biocrudes (F1−F5) made by CFP of loblolly pine sawdust (Pinus taeda). The five biocrudes were produced by RTI International (USA), and sample information and CFP parameters are shown in Table 1. The applied catalyst was a commercially available spray-dried, nonzeolite, alumina-based catalyst with a BET surface area of 114.6 m2/g and a mean particle size of approximately 70 μm. In the CFP process, biomass particles were continuously in contact with hot regenerated catalyst in the mixing zone of the riser reactor to promote partial deoxygenation of the primary pyrolysis vapors. The catalyst to biomass ratio for all experiments was 3:1. After reaction has been established for a total residence time of 0.5−2 s in the mixing zone, the entrained char and catalyst were separated from the product vapors and gases in a cyclone. The separated solids (catalyst, char, and ash) were transferred to the regenerator through a loop seal, where the char and coke on the catalyst were combusted with air. The pyrolysis vapors that exit the cyclone were subsequently condensed at two different points in the process. The heavy fraction was collected with a coalescing filter with input vapor temperature of 95−98 °C. The light fraction was collected further downstream with a second coalescing filter after the product gas stream was cooled to 4 °C in a chilled water-cooled heat exchanger. Each biocrude sample was separated into an organic-rich fraction (biocrude) and a water-rich fraction (aqueous phase). Finally, the permanent gases were directed into an electrically heated catalytic thermal oxidizer. Hence, the pyrolysis products included an organic liquid phase, an aqueous phase, char/catalyst coke, and gases. The organic liquid phase is referred to herein as biocrude. B

DOI: 10.1021/acs.energyfuels.8b00415 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels

employed with a 1D midpolarity RTX-1701 column (30 m; 0.25 mmID; 0.25 μm df) and a 2D low polarity Rxi-5Sil MS column (1.5 m; 0.15 mmID; 0.15 μm df) (Restek). For nonfractionated biocrudes, the PTV was operated in split mode with a split ratio of 1:100 and rapidly heated to 350 °C (hold 2 min) for sample transfer. For THF extracts of the WIS fraction, the PTV injector was operated in solvent−vent mode at 60 °C (hold 1 min) for solvent evaporation and rapidly heated to 350 °C (hold 1 min) during sample transfer. The GC oven was programmed from 40 to 300 °C with 2.5 °C/min; the He carrier gas flow was 1.5 mL/min; and the modulation period was 8 s. Data were acquired by the Thermo Chrom-Card data system. The GC × GC-ToF-MS analysis was done on a LECO Pegasus 4D instrument comprising an Agilent 7890A GC with a PTV injector, a quad-jet two-stage cryogenic (liq. N2) modulator, a secondary oven, an Agilent 7693 ALS, and a time-of-flight mass spectrometer (ToF-MS). The column setup was similar to that used for GC × GC-FID, a 1D midpolarity RTX-1701 column (30 m; 0.25 mmID; 0.25 μm df), and a 2 D low polarity Rxi-5Sil MS column (1.5 m; 0.15 mmID; 0.15 μm df) (Restek), as the GC oven and PTV injector were operated in the same modes as described above. The secondary oven was operated with a 5 °C offset to the main oven and the modulator with a 15 °C offset to the secondary oven. The MS was operated at a scan rate of 100 Hz with a m/ z range of 41−541 Da, with an ion-source temperature of 225 °C and a transfer line temperature of 250 °C. MS data were acquired and processed by the LECO ChromTof data system. 2.4.3. Data Processing. The GC × GC-ToF-MS analyses were processed using ChromTof and used for identification of compound classes in the 2D color plots. Based on the GC × GC-ToF-MS identification of compound classes, similar compound classes were identified in the GC × GC-FID color plots and used for setting up a twodimensional integration template. The integration template was used for integrating area counts for each compound class using a proprietary GC × GC software developed at the University of Copenhagen. The processing includes: retention time range selection, baseline, and 2D shift corrections. Area counts were normalized to the area count of the compound class of aliphatics (paraffins and naphthenes). This normalization was chosen, as the aliphatics were considered to remain unaffected by the solvent fractionation and thus give an unbiased normalization factor. Eventually, averages of the three batches were calculated. 2.5. Chemical Analysis of the WS Fractions by GC × GC-HRMS with Automatic Precolumn Derivatization. 2.5.1. Derivatization. BSTFA derivatization is very susceptible to moisture, which hydrolyzes the derivatization agent.26 Therefore, all glassware was deactivated with 5% DMDCS in toluene before use. The glass surface was coated with DMDCS for 15 s, rinsed twice with toluene, rinsed three times with MeOH, and dried under nitrogen flow. Pyridine was dried with KOH, and DCM was dried with molecular sieves, to eliminate water in the reaction. An amount of 100 μL of the sample fractions was evaporated to dryness under low nitrogen flow at 30 °C prior to automatic precolumn derivatization and analysis. Precolumn derivatization was done on an Agilent 7693A Automatic Liquid Sampler by adding 20 μL of BSTFA and 30 μL of pyridine to the dry sample, which were mixed for 20 s, and heated at 60 °C for 1 h. An amount of 50 μL of pyridine was then added to the sample, and the sample was mixed for 60 s before injection. 2.5.2. Quality Assurance and Quality Control. Each batch included the following QC samples: DCM solvent blank, QC-Mix, and a CA-Mix (see section 2.1). QC samples were used for quality control of the analysis in relation to daily variations, cross contamination, peak shape, chromatographic resolution, and sensitivity. Duplicates of the fractions were analyzed in two batches. The first batch included ten DEE/DCM fractions (duplicates of F1−F5), two blank fractions, four DCM solvent blanks, four QC−Mix samples, and three CA−Mix samples. The second batch included ten water fractions (duplicates of F1−F5), two blank fractions, six DCM solvent blanks, three QC−Mix samples, and four CA−Mix samples. 2.5.3. Chemical Analysis. The sample fractions were analyzed on a 7890B GC with a 7693 autosampler, connected to a 7200 qToF-MS (Agilent Technologies). A reverse column set was employed with a 1D

This study includes the analysis of two heavy fractions, one light fraction and two mixed fractions (15% light and 85% heavy). The two mixed fractions are duplicate samples from same pilot-plant run. More details about the pilot-scale catalytic biomass pyrolysis unit at RTI International, used to produce the five biocrudes, can be found in previously published work.21−23 2.3. Fractionation. The biocrudes were fractionated for further analysis. Fractionation of biocrudes can be performed in several ways.1 The fractionation method used in this study was adapted from Oasmaa et al. (2003 and 2012).24,25 An amount of 0.5 g of each biocrude sample was weighed into 8 mL amber glass vials. An amount of 5 mL of Milli-QWater was added, and the vials were shaken and centrifuged for 3 min at 1100g. The aqueous phase was filtered with a syringe membrane filter (nylon, 0.2 μm, Mikrolab Aarhus A/S) and transferred to a new vial in which it was extracted twice with 2 mL of DEE. Before each extraction, the aqueous phase was shaken and centrifuged (1100g for 3 min). The DEE fractions were collected and combined. Afterward, 2 mL of DCM was added to the aqueous phase. The mixture was shaken and centrifuged (1100g for 3 min), and the water and DCM phases were separated into different vials. A second extraction with DCM was performed, and the two DCM fractions were combined. The DEE/ DCM extracted aqueous phases were evaporated to dryness at 40 °C under nitrogen flow and dissolved in 5 mL of MeOH. Activated molecular sieves (activated overnight at 550 °C and kept in a desiccator until use) were added to the DEE and DCM fractions. After drying, the fractions were shaken and centrifuged, and the supernatant was transferred to 5 mL volumetric flasks. The fractions were volume adjusted to 5 mL with DEE and DCM, respectively. DEE and DCM fractions were combined before analysis. The water-insoluble fraction was extracted two times with 2 mL of THF, shaken, and centrifuged (1100g for 3 min). The liquid phase was transferred to 5 mL volumetric flasks, and volume was adjusted to 5 mL with THF. Undissolved particles were discarded. All sample fractions were made in duplicate, and all fractions were stored at −20 °C until chemical analysis. The CFP biocrude, the combined DCM and DEE fractions, the water fraction, and the THF fraction were analyzed in this study. Figure 1 shows an overview of the separation procedure for all fractions.

Figure 1. Scheme of sample fractionation. DCM: dichloromethane, DEE: diethyl ether, THF: tetrahydrofuran. Gray boxes represent the fractions analyzed in this study. 2.4. Chemical Analysis of the Nonfractionated Biocrudes and the WIS Fractions by GC × GC-FID and GC × GC-ToF-MS. 2.4.1. Quality Assurance and Quality Control. The nonfractionated biocrude samples were dissolved in THF (1:1, v/v) and analyzed in duplicates in two batches together with control samples, including solvent blanks, fraction blanks, QC (a dewatered nonfractionated CFP biocrude dissolved in THF, 1:1), and a reference sample (light gas oil dissolved in tetrachloromethane, 4:1). The THF extracts of the WIS fraction were analyzed in triplicate in three different batches, together with the same control sample as above. 2.4.2. Chemical Analysis. The THF extracts of the WIS fraction and the nonfractionated biocrudes were analyzed by GC × GC-FID and GC × GC-ToF-MS. A Thermo Trace Ultra GC × GC-FID comprised of a programmed temperature vaporizing (PTV) injector, a dual-jet twostage cryogenic (liq. CO2) modulator, a flame ionization detector (FID), and an AI/AS 3000 Autosampler was used. A reverse column set was C

DOI: 10.1021/acs.energyfuels.8b00415 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels

Table 2. Mass Balance, Texture, and Moisture Content of the Four Fractions (DEE, DCM, Water, and THF) for the Five Biocrudes F1−F5 F1 F2 F3 F4 F5

DEE

DCM

water

THF

total

moisture contentb

texture

1.3% 1.3% 2.0% 1.4% 0.3%

0.7% 0.5% −2.5%a 0.3% 0.1%

1.1% 1.7% 2.3% 1.7% 0.5%

43.8% 90.1% 84.3% 87.6% 101.0%

46.9% 93.6% 88.6% 91.0% 101.9%

8.0 wt % 8.93 wt % 9.35 wt % 9.85 wt % 10.38 wt %

thin, easy to transfer lumpy, sticky very thick, droplets very thick, droplets very thick, strings

a The DCM fraction was not included in the total mass balance of F3 due to a clear uncertainty related to the negative value. bDetermined by ASTM method E203.

RTX-1701 column (30 m; 0.25 mmID; 25 μm df) and a 2D Rxi-5Sil MS column (2 m; 0.15 mmID; 15 μm df) (Restek). An amount of 1 μL of each sample was injected into the system in split mode (1:30), and helium was used as carrier gas with a flow rate of 2 mL/min. Ionization was done by electron impact ionization (EI) with 70 eV and an emission current of 35 μA. Ion source, transfer line, and injector temperatures were kept at 230 °C, 280 °C, and 280 °C, respectively. The oven temperature was ramped from 40 °C (hold 2 min) to 280 °C (hold 3 min) at a rate of 3 °C/min. The GC × GC-HR-MS system was equipped with a ZX2 thermal loop modulator (Zoex Corporation), and the modulation time was 3000 ms with a hot jet pulse of 500 ms. The hot jet temperature program was ramped from 80 °C (hold 2 min) to 280 °C with 4 °C/min. The MS was operated with a mass range of 30−500 Da and an acquisition rate of 25 Hz. A threshold of 150 counts was applied to reduce the size of the data files. 2.5.4. Data Processing. GC-Image R2.6 GC × GC software (LLC, USA) was used for a qualitative and semiquantitative analysis of the biocrudes, based on peak integration and plotting of total ion chromatograms (TICs) of the GC × GC-HR-MS data (GC × GC TICs). All TICs were baseline corrected, and the 2D retention time was shifted according to the largest peak (levoglucosan for the water fraction and catechol for the DEE/DCM fraction). An integration template was built and applied to all biocrude samples. The integration template included all peaks with a peak volume above 5 × 105 in at least one of the biocrude samples or the QC−Mix samples. Principal component analysis (PCA) models were made in LatentiX 2.12. The models were based on integrated peak volumes, which were normalized to the sum of all peak volumes (178 peaks in the water fraction and 79 peaks in the DEE/DCM fraction). Data were autoscaled, and a full cross validation was performed. High replicate variations for biocrude F2 were observed in the GC × GC TICs, with almost no peaks in replicate A. Additionally, due to the low response of compounds, the 2 D retention time shift could not be corrected appropriately. F2A was therefore excluded from further data treatment.

from the other samples. This can be explained by evaporation, as F1 is the only light CFP biocrude. 3.2. Chemical Analysis of the Nonfractionated Biocrudes and the WIS Fractions by GC × GC-FID and GC × GC-ToF-MS. 16 compound classes were identified and integrated in each sample. For a better overview of the data, we present the area counts as six pooled groups of compound classes normalized to the area count of the compound class of aliphatics (CC1). The integration areas for the 16 compound classes and the pooled compound groups can be seen in the Supporting Information. The six groups were considered to represent the composition of the lignocellulosic feedstock (loblolly pine) and the flash pyrolytic degradation reactions. Aliphatics (paraffins and naphthenes) were singled out in compound class CC1. Aromatic compounds (abietic acid derivatives and mono-, di-, and triaromatics) were pooled in CC2. Two compound groups of cellulosic origin were made: the smaller aliphatic acids and aldehydes/ketones in CC3 and furan derivatives (furans, furanons, and furfurals) in CC4. Various oxygenated aromatic compounds (mostly of lignin origin), that did not seem to belong to the phenolics, were pooled in CC5 (benzaldehyde/acetophenone, naphthalenols, and biphenylols). Finally, CC6 included the phenolics (of lignin origin), including phenols, catechols, anisols, guaiacols, and syringols. A list of relative amounts (area %) of all compound classes is given in the Supporting Information for both nonfractionated biocrudes and for the WIS fraction of the same biocrudes. The chemical composition of the nonfractionated biocrudes (Figure 2) shows that there are differences between the five biocrudes. F1 has low relative concentrations of all compound groups, while F5 has high relative concentrations of all compound groups. The relative concentrations of compounds in F2, F3, and F4 are intermediate to those of F1 and F5. F3 and F4 are very similar, whereas F2 has higher relative concentrations of aromatics (CC2), furan derivatives (CC4), and aromatic oxygenates (CC5). Figure 3 shows the chemical composition of the WIS fraction of biocrudes F1−F5. The bar chart shows that F1 contained the lowest relative concentrations of aromatics (CC2), furan derivatives (CC4), aromatic oxygenates (CC5), and phenolics (CC6). The chemical composition of F3 and F4 was also very similar for the WIS fraction. F3 and F4 had the highest relative concentrations of all compound groups. F2 had the lowest relative concentrations of small aliphatic acids/ketones/ aldehydes (CC3). The chemical composition of F5 was also similar to F3 and F4, however, with somewhat lower relative concentrations of aromatics (CC2), acids/ketones/aldehydes (CC3), and aromatic oxygenates (CC5). The WIS fractions and the nonfractionated biocrudes can, however, not be directly compared. The sample preparation methods and injection methods were different for the two sample

3. RESULTS 3.1. Fractionation. Mass balance was performed by fractionating each of the five biocrude samples, evaporating to dryness at room temperature under a gentle nitrogen stream, and weighing of the fractions. The fractions were weighed several times during the evaporation to ensure that the weight was stable and that the fractions reached dryness. Final mass balances of the fractions are shown in Table 2. The total value above 100% for F5 is due to uncertainties in the mass balance method. In F2−F4, the mass, not accounted for, might be due to the initial water content of the biocrudes. The moisture content of the biocrudes is around 8−10 wt %, and removal of water during the evaporation might explain why the mass balance does not reach 100%. Since all fractions were evaporated to dryness, there is a high probability that volatile compounds could have been lost. In the case of F1, which contains significant volatile components, it can be seen that the recovered mass was low (46.9%), which is significantly different D

DOI: 10.1021/acs.energyfuels.8b00415 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels

Reproducibility of the automated BSTFA derivatization method was tested for 11 selected compounds in a mixture of 21 oxygenates. Peak areas were normalized to the sum of all 11 compounds, and the standard deviations (SD) and relative standard deviations (RSD) for 17 replicate analyses are listed in Table 3. The RSDs are relatively high for some of the compounds Table 3. Average Peak Area for Oxygen-Containing Compounds Normalized to the Sum (n = 17) with Standard Deviations (SDs) and Relative Standard Deviations (RSDs) compound group

Figure 2. Relative concentration of the five compound classes, normalized to the compound group of aliphatics, determined by GC × GC-FID analysis of the nonfractionated biocrudes. Compound groups: CC2 (aromatics, including mono-, di-, and triaromatics and abietic acid derivatives), CC3 (shorter-chain aliphatic acids, ketones, and aldehydes), CC4 (furan derivatives, including furanons and furfurals), CC5 (oxygenated aromatics, including benzofurans, benzaldehydes, acetophenons, naphthalenols, and biphenylols), and CC6 (phenolics, including methoxybenzenes, hydroxybenzenes, hydroxy- and methoxy-benzenes, and benzenediols).

acids

alcohols ketones aldehydes

compound salicylic acid, 2TMS 1-naphthoic acid, TMS 1-hydroxy-2-naphthoic acid, 2TMS 2-carboxycinnanmic acid, 2TMS diphenic acid, 2TMS 1-naphthol, TMS 1-hydroxy pyrene, TMS a-tetralone acenaphthoquinone 1-naphthal 9-phenanthrene -carbaldehyde

average peak area normalized to sum

SD

RSD, %

40.27 3.44 0.03

4.97 0.47 0.01

12.35 13.76 19.34

0.03

0.01

40.74

5.88 16.60 16.80 5.63 0.88 0.58 9.86

2.25 2.38 1.51 0.31 0.44 0.05 0.91

38.26 14.34 8.99 5.52 49.97 8.31 9.24

but still below 50%, which are deemed acceptable in this study, where the focus mainly is on compound identification and detection of main relative concentration differences between samples. 3.3.2. Chemical Analysis. Tentative identification of 57 compounds in the water fraction and 41 compounds in the DEE/ DCM fractions was made by a NIST search (NIST qualification >20 %). The tentatively identified compounds were separated into seven compound groups for the water fractions and into ten compound groups for the DEE/DCM fractions. GC × GC TICs of the water and the DEE/DCM fractions for F3 are shown in Figure 4, with identification of the most abundant peaks. A full list of the tentatively identified compounds and compound groups can be seen in the Supporting Information, together with 2D and 3D plots of the GC × GC TICs of all biocrudes. Absolute and relative peak volumes are shown in Figure 5 for the water fractions and the DEE/DCM fractions. Values are listed in the Supporting Information. From the bar plots in Figure 5, clear differences between the CFP biocrudes can be seen. Additionally, in the water fractions, large similarity between replicates can be observed. In the DEE/ DCM fraction, the duplicate samples of F3 and F4 show that there was a low reproducibility of the sample preparation method. However, for the relative peak volumes, we see greater similarities between the replicates. From the tentatively identified compounds, it is clear that F1 had low absolute amount of peaks compared to the other biocrudes; F2 had many peaks in the water fraction; and F3 and F4 had many peaks in both fractions. The relative peak volumes show that the water fractions of all five biocrudes were quite similar. However, F5 had higher relative concentration of sugar molecules, especially compared to F1 (Figure 5). In the DEE/DCM fractions, the relative peak volume shows that F1 had a high relative contribution of phenols, whereas F3, F4, and F5 had higher relative contribution from benzenediols.

Figure 3. Relative concentration of the five compound classes, normalized to the compound group of aliphatics, determined by GC × GC-FID analysis of the WIS fraction. Compound groups: CC2 (aromatics, including mono-, di-, and triaromatics and abietic acid derivatives), CC3 (shorter-chain aliphatic acids, ketones, and aldehydes), CC4 (furan derivatives, including furanons and furfurals), CC5 (oxygenated aromatics, including benzofurans, benzaldehydes, acetophenons, naphthalenols, and biphenylols), and CC6 (phenolics, including methoxybenzenes, hydroxybenzenes, hydroxy- and methoxybenzenes, and benzenediols).

sets. For the WIS fractions, the fractionated biocrudes were dissolved in THF in a ratio of 1:10 w/v, whereas the nonfractionated biocrudes were dissolved in THF in the ratio 1:1 v/v. This could have led to differences in the chemical composition due to solubility. Additionally, the WIS fractions were injected in solvent−vent mode, whereas the nonfractionated biocrudes were injected in split mode with a split ratio of 1:100 (see section 2.4.2). The differences in injection method could also have led to differences in the chemical composition of the biocrudes, making it impossible to do a direct comparison. 3.3. Chemical Analysis of the WS Fractions by GC × GCHR-MS with Automatic Precolumn Derivatization. 3.3.1. Derivatization. Automatic precolumn silylation with BSTFA was tested on the CA-Mix and on D(+)-glucose, and it was found to be appropriate for analyzing both acids and sugars, as also shown in previous studies27 (see Supporting Information). E

DOI: 10.1021/acs.energyfuels.8b00415 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels

Figure 4. GC × GC TICs of the water fraction (A) and the DEE/DCM fraction (B) of biocrude sample F3 (B replicate). (A) NIST-identified compounds in the water fraction include #2: 1-(2-methoxy-1-methylethoxy)-2-propanol, TMS, #15: levulinic acid, 2TMS, #16: butanedioic acid, 2TMS, #23: lactic acid, 2TMS, #25: pentenoic acid, 4-[(trimethylsilyl)oxy]-, trimethylsilyl ester, #26: glycolic acid, 2TMS, #32: 4-hydroxybutanoic acid, 2TMS, #34: butanoic acid, 3,4-bis[(trimethylsilyl)oxy]-trimethylsilyl ester, #36: hydroquinone, 2TMS, #37: 3,4-dihydroxyphenylacetic acid, 3TMS, #38: catechol, 2TMS, #41: levoglucosan, 3TMS, #42: β-D-galactopyranoside, methyl 2,4,6-tris-O-(trimethylsilyl)-acetate, #43: 1,5-anhydrohexitol, 4TMS, #44: arabinose, 4TMS, #48: 3-methyl-2-furoic acid, TMS, and #49: D-threo-pentonic acid, 3-deoxy-2,5-bis-O-(trimethylsilyl)-2-C-[[(trimethylsilyl)oxy]methyl]-, lactone. (B) NIST-identified compounds in the DEE/DCM fraction include #7: phenol, TMS, #8: ortho- (shown), meta-, and para-cresol, TMS, #11: tyrosol, 2TMS, #16: guaiacol, TMS, #17: 2-methoxy-5-methylphenol, TMS, #20: vanillin/isovanillin, TMS, #21: acetovanillone, TMS, #25: 3-vanilpropanol, bis(trimethylsilyl)-, #26: catechol, 2TMS, #27: 3-methylcatechol, 2TMS, and #28: hydroquinone, 2TMS.

Figure 5. Absolute peak volume (A) and peak volume normalized to the sum of all identified compounds (B) in the water fractions. Compound groups: aliphatic alcohols, aliphatic acids, aliphatic acids 2 (aliphatic acids with hydroxyl groups), phenols, sugars, furans, and amines. Absolute peak volume (C) and peak volume normalized to the sum of all identified compounds (D) in the DEE/DCM fractions. Compound groups: aliphatic alcohols, aliphatic acids, ketones, phenols 1, phenols 2 (phenols with one additional ether, carbonyl, or hydroxyl group), phenols 3 (phenols with one ether and one carbonyl or hydroxyl group), benzenediols, furans, sugars, and others.

PCA models of normalized peak volumes in the water and the DEE/DCM fractions were used to further investigate the chemical differences between the biocrudes. Figure 6A and 6B

shows PC1 vs PC2 score and loading plots for the PCA model of 178 normalized peak volumes in the water fraction of the five biocrudes (including unidentified compounds). F1 was sepaF

DOI: 10.1021/acs.energyfuels.8b00415 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels

Figure 6. PCA model of peak volume normalized to the sum of all peaks in water fractions of CFP biocrudes F1−F5, score plot (A) and loading plot (B). Compound groups: aliphatic alcohols (diamonds), aliphatic acids (horizontal lines), aliphatic acids 2 (aliphatic acids with hydroxyl groups, circles), phenols (snowflakes), sugars (colored triangles), furans (squares), amines (open triangles), unknowns (cross), and others (identified compounds not included in any group, plus). PCA model of peak volume normalized to the sum of all peaks in DEE/DCM fractions of CFP biocrudes F1−F5, score plot (C) and loading plot (D). Compound groups: aliphatic alcohols (open diamonds), aliphatic acids (colored diamonds), ketones (open circles), phenols 1 (colored circles), phenols 2 (phenols with one ether, carbonyl or hydroxyl groups, white triangles), phenols 3 (phenols with one ether group and one carbonyl or hydroxyl group, snowflakes), benzenediols (colored squares), furans (open squares), sugars (colored triangles), unknowns (cross), and others (identified compounds not included in any group, plus).

WIS fractions has several advantages. The compounds are separated based on their water solubility, which simplify the chromatograms for both the WIS and the WS fractions. The preconcentration of the polar oxygenates in the WS fractions, and especially in the water subfractions, is important to detect these low-concentration compounds in a complex mixture of more nonpolar compounds in higher concentrations. Without fractionation, these compounds may hence remain undetected in the chromatograms. Additionally, poor chromatographic separation and detection of the polar oxygenates (e.g., some acids and sugars) are only possible, or highly improved, when derivatized. 4.2. WS and WIS Fractions of Five CFP Biocrudes. While the GC × GC-FID analysis provides peak areas that are proportional to actual concentrations of the compounds, the GC × GC-MS analysis results in peak volumes of uncalibrated m/z values. Peak volumes obtained from the GC × GC-MS analysis can hence be used to compare the biocrudes qualitatively, while peak volumes are not directly proportional to actual compound concentrations in each biocrude. By sample fractionation and complementary GC × GC analysis we observed some significant differences between the five loblolly pine CFP oils. GC × GC-ToF-MS and GC × GC-FID analysis of the nonfractionated and the WIS fraction showed that the light biocrude, F1, had the lowest relative concentrations of compound group CC2-CC6. Automatic precolumn derivatization, and analysis by GC × GC-HR-MS, further improved the characterization of the biocrude by analysis of the WS fraction. F1 was found to have few peaks compared to the other CFP

rated from the other samples by a negative PC1 score value. F2 was separated by a high positive PC2 score value, whereas F5 had a negative PC2 score. The loading plot in Figure 6B does not show any clear trends to describe the separation, probably due to the complex chemical composition of the biocrudes. However, most of the sugar compounds are clustering at positive PC1 loadings, indicating that there were few sugar molecules in the CFP F1 biocrude. The PCA model of 79 normalized peak volumes in the DEE/ DCM fractions shows separation of F1, F2, and F5 in the score plot (Figure 6C). The PC1 vs PC2 loading plot in Figure 6D shows that F1 is characterized by high relative concentrations of phenols. This was concluded as the F1 samples cluster in the upper left corner of the score plots with negative PC1 scores and positive PC2 scores and are explained by the phenols that cluster in the same corner in the PC1 vs PC2 loading plot (Figure 6D), with negative PC1 loadings and positive PC2 loadings. In contrast, F2 and F5 biocrudes have high positive PC1 scores and PC2 scores close to zero, which can be explained by a high relative concentration of aliphatic acids and sugars that have high positive PC1 loadings (Figure 6D). F3 and F4 biocrudes clustered at negative PC2 scores, which can be explained by high relative concentrations of benzenediols for these biocrudes, as the benzenediols have high negative PC2 loadings (Figure 6D).

4. DISCUSSION 4.1. Fractionation and Automatic Precolumn Derivatization. Fractionation of CFP biocrude samples into WS and G

DOI: 10.1021/acs.energyfuels.8b00415 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels biocrudes, as seen in the GC × GC-TICs (Supporting Information) and in the low absolute peak volume of tentatively identified peaks in the water fractions (Figure 5). This corresponds well with the findings in the nonfractionated biocrude and the WIS fraction and with the fact that F1 was a low-viscosity and light biocrude (Table 1). The bar plots (Figure 5) and the PCA models (Figure 6) indicated that the WS fractions of F1 contained a high relative concentration of phenols in the DEE/DCM fraction compared to F2−F5. F1 had low oxygen content (17 wt %, Table 1) and low amounts of sugars and benzenediols (Figure 5). The chemical compositions of F3 and F4 were similar in both the WIS and the WS fractions. F3 and F4 originate from the same CFP biocrude, a mixture of a light and a heavy fraction, and were therefore expected to be similar in their chemical composition (Table 1), as confirmed by the analysis of the WS fraction. F3 and F4 also clustered together in both PCA models (Figure 6). In the WIS fraction, all compound groups were found in high relative concentrations compared to the other biocrudes. F3 and F4 had a high number of peaks in both WS fractions (Figure 5). The two biocrudes clustered with benzenediols in the PCA model of normalized peak volumes in the DEE/DCM fractions (Figure 6). Additionally, in the PCA model of normalized peak volumes in water fractions, the two biocrudes clustered with sugars (Figure 6). The nonfractionated biocrude, F2, had high relative concentrations of aromatics (CC2), furan derivatives (CC4), and aromatic oxygenates (CC5), whereas F5 had high relative concentrations of all compound classes. In the WIS fractions, F2 had the lowest relative concentrations of small aliphatic acids/ ketones/aldehydes (CC3). F5 had a chemical composition similar to F3 and F4, however, with somewhat lower relative concentrations of aromatics (CC2), acids/ketones/aldehydes (CC3), and aromatic oxygenates (CC5). GC × GC-HR-MS with automatic precolumn derivatization revealed further characterization of the heavy CFP biocrudes. F2 had a high number of peaks in the water fraction but a low number of peaks in the DEE/DCM fraction (Figure 5). The PCA models from this study predicted that F2 contained high relative concentrations of sugars and aliphatic acids (Figure 6). F5 had fewer peaks compared to F2−F4 in the water fraction and the fewest peaks of all biocrudes in the DEE/DCM fraction (Figure 5). F5 had high relative concentrations of sugar molecules in the water fraction and high relative contribution from benzenediols in the DEE/ DCM fractions (Figure 5). In general, the analyses suggest that the chemical composition of the biocrudes is a function of pyrolysis conditions. The pyrolysis temperature (465−575 °C) is the most influential factor. Higher pyrolysis temperature promotes vapor-phase cracking and enhanced deoxygenation, but yields tend to be lower because of increased char and gas formation. For instance, the analysis of DEE/DCM fractions showed that F5, a biocrude produced at 575 °C, contained relatively higher fractions of benzenediols and lower fractions of phenol 3 compounds (phenols with one ether and one carbonyl or hydroxyl group), suggesting greater deoxygenation. Additionally, compounds classified as others that include higher molecular weight hydrocarbons were high in the WIS fraction of F5 caused by increased thermal cracking. On the other hand, the WIS fraction of F2 from the biocrude produced at 465 °C was found to have higher fraction of phenol 3 and phenol 2 compounds (Figure 5). Besides, the DEE/DCM fractions (F1, F3, and F4) sampled from the biocrude produced at 520 °C had relatively higher

phenol 1 fraction that constituted simple phenols (cresols, xylenols, and other alkyl phenols). Furthermore, the WS fraction analysis showed that F2 had a high number of peaks in the water fraction, and the PCA models suggested that F2 contained high relative concentrations of sugars and aliphatic acids. Therefore, it can be inferred that demethylation of methoxyphenols (phenol 3) is enhanced at high pyrolysis temperature as evidenced by the relatively high amount of benzenediols in the WIS fraction of F5. This also explains why the WIS fraction of F2, produced at a relatively lower temperature (465 °C), had more methoxylated phenols (phenol 3). Besides, it could be inferred that the use of moderate pyrolysis temperature at 520 °C enhances direct demethoxylation to yield more simple phenols. In general, the impact of temperature on the formation of WS components such as carboxylic acids, carbonyl compounds, and anhydrosugars is inconclusive from the limited samples evaluated. The results could be due to the fact that other parameters such as residence time were also varied across the CFP experiments. Typically, higher temperatures should have reduced the formation of anhydrosugars, but it could be seen in F5 biocrude that the use of shorter residence time may have limited that effect.

5. CONCLUDING REMARKS Analysis of nonfractionated and fractionated biocrudes by complementary GC × GC methods showed that we were able to characterize and distinguish between five biocrude samples from loblolly pine (Pinus taeda) produced under different CFP conditions. Fractionation into WS fractions and automatic precolumn derivatization enabled the analysis of polar oxygenates in the biocrudes. The combination of sample fractionation, automatic derivatization of polar compounds, and three complementary GC × GC methods resulted in a comprehensive characterization of the five CFP biocrude samples.

■

ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.energyfuels.8b00415. Integration areas and area count of nonfractionated biocrudes, integration areas and area count of the WIS fraction of the biocrudes, derivatization, GC×GC TICs of the WS fractions (water and DEE/DCM), compound identified in water fractions, Compounds identified in DEE/DCM fractions, absolute and relative peak volumes in water and DEE/DCM fractions, and additional tables and figures (PDF)

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected] (Mette Kristensen). ORCID

Mette Kristensen: 0000-0002-9858-4766 Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS The U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office is acknowledged for the financial support under contract EE-0005358 H

DOI: 10.1021/acs.energyfuels.8b00415 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels

(22) Mante, O. D.; et al. Integration of catalytic fast pyrolysis and hydroprocessing: a pathway to refinery intermediates and ″drop-in″ fuels from biomass. Green Chem. 2016, 18 (22), 6123−6135. (23) Mante, O. D.; et al. Pilot-scale catalytic fast pyrolysis of loblolly pine over gamma-Al2O3 catalyst. Fuel 2018, 214, 569−579. (24) Oasmaa, A.; Kuoppala, E.; Solantausta, Y. Fast pyrolysis of forestry residue. 2. Physicochemical composition of product liquid. Energy Fuels 2003, 17 (2), 433−443. (25) Oasmaa, A.; Kuoppala, E.; Elliott, D. C. Development of the Basis for an Analytical Protocol for Feeds and Products of Bio-oil Hydrotreatment. Energy Fuels 2012, 26 (4), 2454−2460. (26) Shareef, A.; Angove, M. J.; Wells, J. D. Optimization of silylation using N-methyl-N-(trimethylsilyl)-trifluoroacetamide, N,O-bis-(trimethyl.silyl)-trifluoroacetamide and N-(tert-butyldimethylsilyl)-N-methyltrifluoroacetamide for the determination of the estrogens estrone and 17 alpha-ethinylestradiol by gas chromatography-mass spectrometry. Journal of Chromatography A 2006, 1108 (1), 121−128. (27) Halket, J. M.; Zaikin, V. G. Derivatization in mass spectrometry 1. Silylation. Eur. J. Mass Spectrom. 2003, 9 (1), 1−21.

(Catalytic Upgrading of Thermochemical Intermediates to Hydrocarbons). Kristoffer Gulmark Poulsen, Josephine Lübeck and Sissel Bjørn Svendsen, University of Copenhagen, are acknowledged for their work with fractionation of the five CFP oils.

■

REFERENCES

(1) 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. (2) Mullen, C. A.; Boateng, A. A. Chemical composition of bio-oils produced by fast pyrolysis of two energy crops. Energy Fuels 2008, 22 (3), 2104−2109. (3) Charon, N.; et al. Multi-technique characterization of fast pyrolysis oils. J. Anal. Appl. Pyrolysis 2015, 116, 18−26. (4) Kanaujia, P. K.; et al. Analytical approaches to characterizing pyrolysis oil from biomass. TrAC, Trends Anal. Chem. 2013, 42, 125− 136. (5) Yu, Y.; Chua, Y. W.; Wu, H. W. Characterization of Pyrolytic Sugars in Bio-Oil Produced from Biomass Fast Pyrolysis. Energy Fuels 2016, 30 (5), 4145−4149. (6) Wang, S. R.; et al. Stepwise Enrichment of Sugars from the Heavy Fraction of Bio-oil. Energy Fuels 2016, 30 (3), 2233−2239. (7) Bridgwater, A. V. Principles and practice of biomass fast pyrolysis processes for liquids. J. Anal. Appl. Pyrolysis 1999, 51 (1−2), 3−22. (8) Cheng, T. T.; et al. Molecular composition of oxygenated compounds in fast pyrolysis bio-oil and its supercritical fluid extracts. Fuel 2016, 172, 49−57. (9) Marsman, J. H.; et al. Identification and classification of components in flash pyrolysis oil and hydrodeoxygenated oils by twodimensional gas chromatography and time-of-flight mass spectrometry. Journal of Chromatography A 2008, 1188 (1), 17−25. (10) Torri, I. D.; et al. Bio-oil production of softwood and hardwood forest industry residues through fast and intermediate pyrolysis and its chromatographic characterization. Bioresour. Technol. 2016, 200, 680− 690. (11) Faccini, C. S.; et al. Comprehensive Two-Dimensional GC with TOF-MS Detection: Study of Pyrolytic Bio-Oil of Kraft Mill Residues. J. Braz. Chem. Soc. 2013, 24 (7), 1085−1098. (12) Cardoso, C. A. L.; Machado, M. E.; Caramao, E. B. Characterization of bio-oils obtained from pyrolysis of bocaiuva residues. Renewable Energy 2016, 91, 21−31. (13) Tessarolo, N. S.; et al. Chemical characterization of bio-oils using comprehensive two-dimensional gas chromatography with time-offlight mass spectrometry. J. Chromatogr. A 2013, 1279, 68−75. (14) Kloekhorst, A.; et al. Catalytic hydrodeoxygenation and hydrocracking of Alcell (R) lignin in alcohol/formic acid mixtures using a Ru/C catalyst. Biomass Bioenergy 2015, 80, 147−161. (15) Ristic, N. D.; et al. Quantitative compositional analysis of Estonian shale oil using comprehensive two dimensional gas chromatography. Fuel Process. Technol. 2017, 167, 241−249. (16) Moraes, M. S. A.; et al. Qualitative analysis of bio oils of agricultural residues obtained through pyrolysis using comprehensive two dimensional gas chromatography with time-of-flight mass spectrometric detector. J. Anal. Appl. Pyrolysis 2012, 98, 51−64. (17) Poole, C. F. Alkylsilyl derivatives for gas chromatography. Journal of Chromatography A 2013, 1296, 2−14. (18) Bae, M.-S.; et al. Analytical Methods of Levoglucosan, a Tracer for Cellulose in Biomass Burning, by Four Different Techniques. Asian J. Atmos. Environ. 2012, 6 (1), 53−66. (19) Fabbri, D.; et al. Gas chromatography/mass spectrometric characterisation of pyrolysis/silylation products of glucose and cellulose. Rapid Commun. Mass Spectrom. 2002, 16 (24), 2349−2355. (20) St’avova, J. Method development for the characterization of biofuel intermediate products using gas chromatography with simultaneous mass spectrometric and flame ionization detections. Journal of Chromatography A 2012, 1224, 79−88. (21) Dayton, D. C.; et al. Design and operation of a pilot-scale catalytic biomass pyrolysis unit. Green Chem. 2015, 17 (9), 4680−4689. I

DOI: 10.1021/acs.energyfuels.8b00415 Energy Fuels XXXX, XXX, XXX−XXX