Characterization of Bio-oils from Different Pyrolysis Process Steps and

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Characterization of Bio-oils from Different Pyrolysis Process Steps and Biomass Using High-Resolution Mass Spectrometry Patrícia V. Abdelnur,*,† Boniek G. Vaz,‡ José D. Rocha,† Marlon B. B. de Almeida,§ Marco Antonio G. Teixeira,§ and Rosana C. L. Pereira§ †

National Center for Agroenergy Research, Brazilian Enterprise for Agricultural Research (EMBRAPA), Parque Estaçaõ Biológica, PqEB s/n°, Avenida W3 Norte, 70770-901 Brasília, Federal District, Brazil ‡ Chemistry Institute, Federal University of Goiás, Campus Samambaia, 74001-970 Goiânia, Goiás, Brazil § Cenpes, Petrobras, Avenida Horácio Macedo, 950, Cidade Universitária, Ilha do Fundão, 21941-915 Rio de Janeiro, Rio de Janeiro, Brazil S Supporting Information *

ABSTRACT: Next-generation biofuels have been widely investigated because they have particular advantages compared to firstgeneration biofuels. Pyrolysis is an example of a thermochemical route extensively used in oil and coal industries worldwide to produce these biofuels. Strategies for low-cost upgrading are among the biggest challenges facing the adoption of bio-oils in the development of commercial biofuels. Specific biomass sources could be the best option for generating bio-oil with the required properties. For this, it is necessary to understand the composition of these biomasses and their bio-oils. Here, we analyzed bio-oil samples from the fast pyrolysis of different biomasses collected during two different steps of the process by direct-infusion highresolution mass spectrometry. First, a comparative study of two common high-resolution mass spectrometers, quadrupole timeof-flight mass spectrometry (Q-TOF MS) and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), was performed to validate the methodology and to investigate the differences in mass discrimination and resolution. FT-ICR MS showed the best performance because of its unsurpassed resolution and accuracy. We apply the common petroleomics tools to interpret the mass spectra obtained. The FT-ICR MS analysis reveals that bio-oils are dominated by Ox species. The class profile of bio-oils was strongly affected by the biomass and steps of the pyrolysis process.

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INTRODUCTION Much has been invested worldwide in the generation of a renewable chain of fuels based on biomass derivatives, which has been called next-generation biofuels. These have particular advantages compared to first-generation biofuels; they are nonfood materials and could provide a real reduction in greenhouse gas emissions. Biomass-based fuels could be generated from lignocellulosic biomass, such as woody crops, agricultural residues, and wastes. Some examples of these advanced biofuels are algae biodiesel, butanol, cellulosic ethanol, hydrotreated vegetable oil, biomass to liquid diesel, and biosynthetic gas.1 The main technologies described that produce these biofuels are based on biochemical and thermochemical routes. Pyrolysis is an example of a thermochemical route extensively used in oil and coal industries worldwide. Its application in biomass conversion is still innovative with pilot- and demonstrative-scale projects. Variations in technology and operation conditions can make changes in the process of pyrolysis. Torrefaction, also known as a mild form of pyrolysis, occurs at temperatures in the range of 250−300 °C, producing mainly torrefied biomasses and low yields of acidic pyrolignous extracts as condensable liquids.2 Slow pyrolysis, also known as carbonization, aims to produce high yields of charcoal yet is able to produce significant amounts of tar if an appropriated condensation system is connected to the furnace. In Brazil, 10 million metric tons of charcoal is produced yearly, to be used mainly as a bioreductor in steel and iron alloy production.3 © 2013 American Chemical Society

Fast pyrolysis produces higher bio-oil (BO) yields compared to conventional pyrolysis because of the high heating rates, low residence times, and small particle sizes of the applied feedstock. In this study, samples were collected via a fast pyrolysis pilot plant in a 10−20 kg/h−1 capacity.4 Different biomass sources could be a good option for generating BOs with specific properties. BO is the condensable product fraction originating from biomass fast pyrolysis, exhibiting some interesting features: it is liquid, presents higher energy density than the original material, and is easy to pump and transport over large distances. However, BO has to be upgraded to reach suitable fuel properties. Strategies for lowcost upgrading are among the biggest challenges facing the adoption of pyrolysis BO in the development of commercial biofuels. A considerable number of studies have been performed investigating BO properties and chemical compositions to verify their potential as biofuel.5−9 The most common technique used to identify BO samples is gas chromatography−mass spectrometry (GC−MS). However, this technique is limited to identifying small-chain and nonpolar compounds, usually requiring one-step derivatization to analyze polar compounds. Only lightweight compounds in BO can be Received: May 1, 2013 Revised: September 26, 2013 Published: September 30, 2013 6646

dx.doi.org/10.1021/ef400788v | Energy Fuels 2013, 27, 6646−6654

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Figure 1. Biomass fast pyrolysis pilot plant (PPR 10), with 10 kg/h capacity, for (7) BO and (9) LFBO sample reservoir. (Rio de Janeiro, Brazil) and used without further purification. Ammonium hydroxide was obtained from Sigma-Aldrich (Rio de Janeiro, Brazil). BO samples originating from the fast pyrolysis process of different biomass samples (eucalyptus, eucalyptus bark, cellulosic mud, water hyacinth, and pine) were analyzed. Eucalyptus samples were collected from a pulp and paper plant. These samples are representative of the industrial process and are produced in large amounts in Brazil. Eucalyptus bark was collected from a debarking process before chipping the trunks. Primary cellulosic mud was collected at the end of the pulping process during filtration and purification of pulp. Water hyacinth was collected under Brazilian Environment Institute (IBAMA) rules from the Paraguay River near Corumbá in the state of Mato Grosso do Sul.25 Pine wood biomass sample was supplied by BTG (Enschede, Netherlands). General Experimental Procedures. Fast Pyrolysis Technology and BO Production. The pilot plant shown in Figure 1 is a circulating fluidized-bed reactor, with a capacity of 10 kg/h, located at the Bioware Company (Campinas, Brazil), where the pyrolysis runs were carried out. Some changes in the feed capacity are expected because of the bulk density variation of feedstock. Pretreated biomasses with a moisture content in the range of 10−12 wt % and particle sizes from 2 to 4 mm were fed from a silo (3) directly into the free board of the reactor (2), which was preheated and previously loaded with fine sand particles as a bed in the case of thermal pyrolysis, whereas alternatively, a reactive catalyst bed could have been used. A confined feed screw (3a) located at the bottom of the silo kept a regular preset feeding rate. Air was used as the fluidization agent. A blower (1) supplied the air flow, which passed through a heater (2) and finally fed in the reactor. The process is autothermal, once the air burned about 10% of the biomass to supply heat for the process. The reaction temperature ranged from 450 to 500 °C. As a result, the biomass was converted into biochar, vapor, and gas mixture. Volatile products left the reactor, dragging the finer char particles, which were separated by means of two insulated cyclones in series (5). A biochar reservoir (8) retained the biochar from the cyclones until it cooled to room temperature. After the cyclones, a two-stage recovering (condensation) system (6) separated pyrolysis liquids into two fractions. The first stage was an indirect cooler with water, and the second stage was a centrifugal device (condenser). The gases entered in the first stage at 200−250 °C and left at 80−90 °C. A stream rich in water and water-soluble compounds LBOF was condensed and collected in a tank (9). The uncondensed vapors entered in the second stage (centrifugal device), where aerosol drops coalesced and the BO was collected at 40−50 °C.

analyzed by GC−MS analysis, owing to the low injector temperature in GC. However, some polar compounds, such acids and alcohols, can be identified, which is dependent upon the chromatographic column used in GC separation.10−12 MS has been shown to be a powerful technique for detecting polar compounds using an electrospray ionization source (ESI−MS). Direct-infusion mass spectrometry (DIMS) analysis has been widely used to detect and identify many chemical compounds in different matrices, such as food, 13,14 fuels, 15 and biofuels.16−19 Some advantages of this technique are minimal sample preparation steps, faster analyses, and a wider range of compounds detected at the same injection. Smith and Lee20 have analyzed BOs using laser desorption ionization−mass spectrometry (LDI−MS) and have detected a complex nature of them compared to non-phenolic compounds. Recently, ESI− MS has been used to detect a wide range of compounds (“phenolics and sugarics”) in BOs produced from red oak,21 pine pellets, and peanut hull22 biomasses. In the present study, BO samples originating from the pyrolysis of different biomasses were analyzed by DIMS using quadrupole time-of-flight mass spectrometry (Q-TOF MS). However, a considerable amount of compounds was detected, and the spectrum was quite similar to that generated for petroleum samples (showing a Gaussian shape of m/z ions), confirming the high complexity of BO samples. Afterward, the BO samples were analyzed through ultrahigh-resolution mass spectrometry (UHRMS), using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS),11,12 which has evaluated precision for petroleomic experiments as measured by repeatability and reproducibility.23 Petroleomic tools were used to characterize each sample according to their oxygen and carbon classes and double-bond equivalents (DBEs).5,11,24 Additionally, samples collected in two different steps of the fast pyrolysis process of each biomass [BO and light bio-oil fraction (LBOF)] were analyzed by DIMS. A different spectrum profile was obtained for each step of the process, inferring a specific chemical composition for each step.

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EXPERIMENTAL SECTION

Chemical Reagents and Samples. High-performance liquid chromatography (HPLC)-grade methanol was purchased from Merck 6647


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Figure 2. ESI(−)−MS spectrum using Q-TOF MS of (a) BO and (b) LBOF from the fast pyrolysis process of water hyacinth biomass. Pyrolysis gases exited on the top of centrifugal device and flowed to a combustion chamber to be burned (10). Optionally, the combustion gases could recirculate to the system from a gas distributor plate to serve as a fluidization agent and as a source of heating for the reactor bed (not shown in Figure 1). The plant operated at atmospheric pressure. Operational conditions were monitored and controlled using sensors distributed throughout the system, which was connected to a computer for data acquisition (11−15). Further information about biomass fast pyrolysis in Brazil is described elsewhere.26,27 For each biomass processed, two samples were collected in different steps of the pyrolysis process, BO and LBOF, and both were analyzed by MS. BO is the oil fraction with a low water content, and LBOF is the aqueous phase with a high water content and contains watersoluble compounds.27 BO and LBOF samples from eucalyptus, eucalyptus bark, cellulosic mud, and water hyacinth were produced at the Bioware Company (Campinas, Brazil), whereas BO from pine biomass was supplied by BTG (Enschede, Netherlands)28 via Petrobras (Rio de Janeiro, Brazil). MS Analysis. A standard solution (SS) of each BO and LBOF sample was prepared, dissolving 10 mg of BO in 10 mL of MeOH. Then, consecutive dilutions were performed to determine an ideal concentration for each analyzer because they have different sensitivities. The best conditions established were 0.1 mg/mL for QTOF MS analysis and 0.05 mg/mL for FT-ICR MS analysis, with both solutions containing 0.2% ammonium hydroxide in methanol. Q-TOF MS Analysis. ESI−MS analyses were performed in the negative-ion mode in Q-TOF MS (Waters, Manchester, U.K.), with the following conditions: capillary voltage, 1.4 kV; gas pressure, 0.3 psi; cone voltage, 35 V; extractor voltage, 4 V; source temperature, 100 °C; and desolvation temperature, 100 °C. Aliquots of 100 μL of SS were transferred to a flask containing 900 μL of methanol with a 0.2% ammonium hydroxide solution. After shaking for 30 s using a vortex and 5 min of centrifugation, 100 μL of this solution was diluted to 1 mL of the total volume with methanol containing a 0.2% ammonium hydroxide solution. This resulting solution was then directly infused into the mass spectrometer. All of the ESI(−)−Q-TOF MS data were analyzed using the MassLynx 3.5 software (Waters, Manchester, U.K.). Mass spectra were accumulated over 60 s to generate final data ranging from m/z 50 to 1000. FT-ICR MS Analysis. Aliquots of 100 μL of SS were transferred to a flask containing 900 μL of methanol with a 0.2% ammonium hydroxide solution. After shaking for 30 s using a vortex and 5 min

of centrifugation, 500 μL of this solution was taken and diluted to 1 mL of the total volume with methanol containing a 0.2% ammonium hydroxide solution and injected using a micro-ESI. Solvents and additives were of HPLC grade, purchased from Sigma-Aldrich, and used as received. General ESI conditions were as follows: capillary voltage, 3.10 kV; flow rate, 5 μL min−1; tube lens voltage, −39 V; and capillary voltage, −100 V. Ultrahigh-resolution MS was performed with a Thermo Scientific 7.2 T ESI−FT-ICR MS LTQ-FT ULTRA (Thermo Scientific, Bremen, Germany). A scan range of m/z 200−1000 was used, and 100 microscans were collected in each run. The average resolving power (Rp) was 400 000 at m/z 400, where Rp was calculated as m/Δm 50%, that is, by the m/z value divided by the peak width at 50% peak height. Time-domain data (ion cyclotron resonance signal or transient signal) were acquired for 700 ms. Microscans were co-added using Xcalibur 2.0 software (Thermo Scientific, Bremen, Germany). The molecular weight distribution for each sample was first verified by LTQ analysis to ensure the validity of the molecular weight distribution based on FT-ICR MS. ESI(−)−FT-ICR MS data were analyzed using the Composer software (Sierra Analytics, Modesto, CA). In addition to external calibration, an internal recalibration was applied to the peak list (using Composer software) prior to final peak assignment. A set of theoretical homologues series for a specific heteroatom class (most abundant class for each ion mode) was selected as an internal calibrant because of their presence in all samples, low errors, and high average peak intensities. Similar tools used for petroleum analysis, such as class distribution, DBE versus carbon number, and van Krevelen diagrams, were used to process these highly complex spectra.

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RESULTS AND DISCUSSION

BO Analysis Using Q-TOF MS. Figure 2 shows ESI(−) mass spectra of BO and LBOF of water hyacinth, which were collected from different steps of the pyrolysis process. Note that the mass spectra of these two samples are different, revealing differences in their chemical composition because of the chemical fractionation that occurred in the process. The BO samples were collected at the end of the process and contained many more compounds, including heavy compounds, such as O-containing compounds (Figure 2a), and the LBOF samples, collected at the beginning of the process, contained more 6648


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Figure 3. (a) ESI(−)−MS spectrum of eucalyptus BO using Q-TOF MS. Mass-to-charge (m/z) ratio from 351.00 to 351.40 using (b) Q-TOF MS (resolution of 5000) and (c) FT-ICR MS (resolution of 400 000).

“light” compounds, such as acids and sugar-derivative compounds (Figure 2b). The highest ion intensity detected in negative mode, m/z 255 (Figure 2a), in the BO sample refers to the saturated fatty acid palmitic acid (C16:0; C16H32O2);29 however, the highest ion intensity detected in the LBOF, m/z 161, was attributed to the sugar compound levoglucosan (C6H10O5) (Figure 2b). The high abundance of sugar-derivative compounds in the LBOF samples was also observed for the other biomass samples submitted to fast pyrolysis (see Figure 1S of the Supporting Information). This occurs because the hot product vapors meet, as a first step, a quench stream (water + LBOF recycled), which further condensates water and light compounds. This fraction contained more “light” compounds, such as acids and polyhydroxilated compounds, which indicate derivatives of the conversion of sugar structures (Figure 2b). Comparing BO samples from different biomass sources and processes under different stages of development, it was clearly noticed that each one has a specific fingerprinting MS spectrum. BO from water hyacinth has more fatty acid compounds, whereas BO from eucalyptus bark contains a triterpenoid acid (C30H46O3)30 as the highest ion intensity detected. BOs from eucalyptus, cellulosic mud, and pine presented similar chemical composition profiles, with levoglucosan having the highest detectable ion intensity. Q-TOF MS versus FT-ICR MS. Because of the high chemical composition complexity of these samples, we use UHRMS, using ESI−FT-ICR MS, as a tool that has the power to broadly characterize these samples at a molecular level. The results obtained when applying both analytical approaches were compared: Q-TOF MS (resolution of 5000) and FT-ICR MS (resolution of 400 000). To illustrate the differences in the amount and quality of information obtained by each analyzer, Figure 3 shows the mass-scale-expanded segment at m/z 351 from the mass spectrum of eucalyptus BO obtained from Q-TOF MS and FT-

ICR MS. This mass scale-expanded segment in the FT-ICR mass spectrum demonstrates baseline separation of six different compounds, whereas only one compound had been observed in the Q-TOF mass spectrum. Resolution of all of those doublets requires a mass resolving power (m/Δm 50% at m/z 351) greater than 17 000 if the two closely spaced ion peaks have similar magnitudes. An even higher resolving power is required if their abundances are different. Such an ultrahigh resolving power is easily achieved by FT-ICR MS or other UHRMSs, such as Orbitrap or ultrahigh-resolution TOF MS. This infers that Q-TOF MS does not have enough resolution to separate compounds with the same nominal mass. For a detailed and complete chemical composition characterization of BO and LBOF samples, they should be analyzed using UHRMS. However, Q-TOF MS could be a good option for pyrolysis process evaluation during development and optimization, detecting major compounds in BO and LBOF samples, with the advantage of being a more robust and cheaper instrument. Another important and significant difference among the two mass spectrometers is mass discrimination; some instrumentation and/or experimental conditions have a higher sensitivity for low mass ions versus high mass ions or vice versa. Hence, the experimental conditions were carefully optimized to minimize mass discrimination for the mass range of interest. Additionally, ion source conditions and ion guide voltages were optimized to reduce aggregation and minimize fragmentation. Despite having performed all of these settings, the FT-ICR MS data showed mass discrimination against very low mass ions, especially those below m/z 140 (see Figure 2S of the Supporting Information). However, the ions detected by FTICR MS and Q-TOF MS show similar relative abundance. In the FT-ICR MS, the ion flight time between the quadrupole and the ICR affects the transmission of high mass ions versus low mass ions. The ion flight time determines how long the ICR cell has the gate open for the ion injection, during 6649


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water hyacinth, with O2 as the most abundant class; the other BOs have the most abundant class with 4−6 oxygens, accounting for ∼12−20% of the identified peaks, corroborating with previous results reported by Jarvis et al.22 and Smith et al.21 To verify the differences between the chemical compositions of the BO samples, two BO samples from water hyacinth and eucalyptus biomasses were selected and a detailed inspection of their composition was performed. The oxygen class distribution was completely different for each BO analyzed (see Figure 3S of the Supporting Information). BO from eucalyptus contains more oxygen compounds compared to that from water hyacinth. This could be explained considering the thermal chemical conversion of hemicellulose, cellulose, and lignin as reported by Yang et al.32 The pyrolysis of hemicellulose occurred quickly, with the weight loss of hemicellulose mainly happening at 220−315 °C and that of cellulose happening at 315−400 °C. However, lignin was more difficult to decompose, because its weight loss happened in a wide temperature range of 160−900 °C and the generated solid residue was very high (40 wt %). Because water hyacinth has a lower lignin content compared to eucalyptus, it is expected that its conversions mainly in H2, CO, CO2, H2O, and some oxygenated compounds are those represented in Figure 3S of the Supporting Information. On the other hand, because eucalyptus has a higher lignin content, its conversion not is totally complete, with a high amount of oxygenated compounds remaining in the final product, mainly ligninderivative compounds.25 Figure 5 shows water hyacinth and eucalyptus BO negativeion ESI isoabudance-countoured diagrams of DBE versus carbon for three Ox heteroatom classes (O4, O6, and O8). The oxygen classes for both oils span different compositional spaces with number and DBE. Water hyacinth BO contains more O4 compounds, from C8 to C22, and DBE 5−15. However, eucalyptus BO contains more O6 and O8 compounds, from C6 to C30, and DBE 2−18. In general, the lower oxygen heteroatom classes (O1−O6) have lower DBE values of 1−6, whereas the high oxygen heteroatom classes (O7 or higher) have higher DBE values (>7). This means that, in such compounds, an increase in DBE and carbon number is

which trapping of injected ions occurs through the high magnetic field inside the cell. If sufficient time is not given, some high mass ions might not have arrived at the cell. In contrast, if the gate is open too long, some low mass ions will be lost. The effect of the ion flight time on mass discrimination is notorious in FT-ICR, and typically, there is no good way of efficiently trapping ions in a very wide mass range.31 The mass spectra acquisition conditions were set to reach the best way to avoid the mass discrimination. Chemical Characterization of BO by FT-ICR MS. FTICR MS has been shown to be an ideal tool for the deep chemical composition characterization of BO samples, especially for its unparalleled ability to simultaneously resolve and identify thousands of peaks in complex mixtures at the level of molecular formula assignment.22 To demonstrate the high mass accuracy obtained, tables of assignment molecular formulas for the some Ox class identified in the eucalyptus BO is include in Tables 1S−5S of the Supporting Information. In addition, petroleomic-like tools are necessary to process these highly complex matrixes. The first data process performed was the characterization of BO samples according to their oxygen classes using the Composer software (Figure 4). Each

Figure 4. Oxygen class distribution for each BO analyzed by ESI(−)− MS using FT-ICR MS.

BO sample has a different profile of oxygen compounds, which is directly related to the biomass used in the fast pyrolysis process. The chemical composition analysis showed several heteroatom classes consisting of 2−12 oxygens, except for

Figure 5. DBE versus carbon number diagrams to (a) water hyacinth BO and (b) eucalyptus BO. 6650


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accompanied by a high oxygen content. Jarvis et al.22 reported a similar trend for pine pellet BO. Chemical Characterization of BO and LBOF Samples. Another data process was performed to compare samples collected in two different steps of the fast pyrolysis process (BO and LBOF) using the same biomass. The samples obtained from the same biomass used for FT-ICR MS characterization were selected to compare the results. Water hyacinth BO contains a majority of O 2 −O 5 compounds, whereas LBOF samples are concentrated in O2− O8 compounds (Figure 6a). The high oxygen composition in

for highly acidic to weakly acidic species in BO is more asymmetric than that for petroleum and because a few highly abundant, very acidic species dominate the broadband mass spectra.22 With these results, it was possible to conclude that the chemical composition of the samples is dependent upon the process conditions on the step of the process that they are collected and is strongly affected by the biomass used in the process. van Krevelen Diagrams of BO and LBOF Samples. A chemical composition data analysis was performed using the van Krevelen diagram, a graph where each derivative compound class is detected in a specific region of the diagram. The van Krevelen diagram is obtained by plotting the ratios H/C versus O/C. Each region of the diagram refers to a specific class of compounds, such as lipid-, lignin-, and condensed aromatic-derivative compounds,33 which easily and clearly make the major classes of compounds in a sample observable. The diagrams were plotted to BO samples from water hyacinth (Figure 8a), pine (Figure 8b), eucalyptus (Figure 8c), cellulosic mud (Figure 8d), and eucalyptus bark (Figure 8e). In Figure 8, the blue dots mean compounds detected in high relative abundance. Water hyacinth BO samples are concentrated in lipidderivative compounds as fatty acids (palmitic acid), whereas cellulosic mud BO contains lipid- and lignin-derivative compounds. Eucalyptus BO contains a lot of lignin-, cellulose-, and hemicellulose-derivative compounds. Levoglucosan (C6H10O5) is the most intense sugar in this sample. Pine BO contains more cellulose- and hemicellulose-derivative compounds. Eucalyptus bark BO has a high concentration of triterpenoid acid (C30H46O3). Each biomass submitted to the pyrolysis process directly infers the chemical composition of BO. Some of them contain more sugar-derivative compounds, and others have more ligninderivative compounds, depending upon biomass processed. BO composition is affected by biomass composition but could be also impacted by different vapor residence times34 or catalytic effect of the sand used in the different fluidized beds. In this study, pine and eucalyptus BOs were produced by two different setups. Therefore, the chemical composition of these samples could be affected by the biomass and also the pyrolysis process. The same approach was used to compare the BO and LBOF compositions from water hyacinth and eucalyptus. A clear separation between BO and LBOF from water hyacinth was noted, as mentioned before. BO contains more lipid-derivative compounds, whereas LBOF has lipid-derivative compounds and also cellulose- and hemicellulose-derivative compounds (Figure 9). Eucalyptus BO and LBOF have lignin-, cellulose-, and hemicellulose-derivative compounds. However, most celluloseand hemicellulose-derivative compounds were extracted in the LBOF sample. This infers that the separation method worked for both BO and LBOF samples; however, because eucalyptus BO presented a high concentration of levoglucosan, the separation was not clear using oxygen class (Figure 6) and carbon class distribution (Figure 7) graphs.

Figure 6. Oxygen class distribution graph of BO and LBOF of (a) water hyacinth and (b) eucalyptus.

LBOF indicates the presence of high concentrations of derivatives of the conversion of sugar structures. This occurs, as was previously explained, because there is a quenching of the temperature at the first step of the fast pyrolysis process, which condenses the water, and furthermore, water-soluble compounds, such as sugar-derivative compounds (high oxygen composition), are extracted at this part of the process, where LBOF samples are collected. On the other hand, eucalyptus BO and LBOF samples could not be clearly distinguished in the oxygen class composition graph (Figure 6b), which infers that the separation process at the pyrolysis process was not efficient for this biomass under the tested conditions. Further data processing was performed for these samples, generating carbon distribution graphs for BO and LBOF from water hyacinth and eucalyptus biomasses (Figure 7). Of note, water hyacinth BO had more heavy compounds with a higher number of carbon molecules (Figure 7a). On the other hand, LBOF presented more “light compounds”, containing a lower number of carbon molecules in the structure (Figure 7b). Once again, it is possible to infer that the separation process was not efficient for the eucalyptus biomass because many compounds, including heavy compounds with high numbers of carbon, were detected in the LBOF sample collected at the beginning of the process. There was no Gaussian shape to the total carbon number distribution graph because the abundance distribution

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CONCLUSION DIMS has been successfully used for analyses of BO composition. UHRMS, using FT-ICR MS, has shown to be an essential tool for an unequivocal characterization of BO and 6651


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Figure 7. Carbon distribution graph of BO and LBOF of (a) water hyacinth and (b) eucalyptus.

Figure 8. van Krevelen diagrams of the BO samples from (a) water hyacinth, (b) pine, (c) eucalyptus, (d) cellulosic mud, and (e) eucalyptus bark.

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Figure 9. van Krevelen diagrams of the BO and LBOF to (a) water hyacinth and (b) eucalyptus.

1S), O4 compounds (Table 2S), O6 compounds (Table 3S), O8 compounds (Table 4S), and O10 compounds (Table 5S). This material is available free of charge via the Internet at http:// pubs.acs.org.

LBOF samples, because compounds with the same nominal mass were present in the samples. Otherwise, a pre-separation step should be performed before Q-TOF MS analysis. In addition, Q-TOF MS could be a good option for pyrolysis process evaluation, because it is a more robust and cheaper instrument. The chemical composition of BO and LBOF samples is strongly affected by the biomass type and process conditions. Each biomass submitted to the pyrolysis process directly affects the chemical composition of BO. Some of them contain more sugar-derivative compounds, and others have more lignin- and/ or lipid-derivative compounds. BO produced through fast pyrolysis of water hyacinth has more lipid-derivative compounds; eucalyptus bark has more triterpenoid acid compounds; and eucalyptus, pine, and cellulosic mud have more cellulosic- and lignin-derivative compounds. These characteristics seem to be directly related to the biomass composition and are under investigation. The analysis of the two product samples collected from different steps of the pyrolysis process, BO and LBOF, revealed different spectrum profiles for each sample. Samples collected at the first step of condensation, LBOF, contain more sugarderivative compounds because of the quenching of vapors, which results in water condensation and extraction of watersoluble compounds.

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AUTHOR INFORMATION

Corresponding Author

*Telephone: +55-61-3448-2340. Fax: +55-61-3448-1589. Email: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors thank EMBRAPA and Petrobras for permission to publish this work and for the financial support.

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REFERENCES

(1) Grayson, M.; Fairley, P.; Graham-Rowe, D.; Savage, N.; Sanderson, K.; Martin, J.; Gilbert, N.; Lynd, L. R.; Woods, J.; Robbins, M.; Moraes, M. Nat. Outlook 2011, 474, S1−S43. (2) Felfli, F. F.; Luengo, C. A.; Suárez, J. A.; Beatón, P. A. Energy Sustainable Dev. 2005, 9, 19−22. (3) Stamatov, V.; Rocha, J. D. Int. J. Global Energy Issues 2007, 27, 217−230. (4) Mesa-Perez, J. M.; Rocha, J. D.; Cortez, L. A. B.; Jordan, R. A. Fast pyrolysis as a BTL precursor. In Sugarcane BioethanolR&D for Productivity and Sustainability, 1st ed.; Cortez, L. A. B., Ed.; Edgar Blucher Ltda.: São Paulo, Brazil, 2010. (5) Leonardis, I.; Chiaberge, S.; Fiorani, T.; Spera, S.; Battistel, E.; Bosetti, A.; Cesti, P.; Reale, S.; De Angelis, F. ChemSusChem 2013, 6, 160−167. (6) Bayerbach, R.; Nguyen, V. D.; Schurr, U.; Meier, D. J. Anal. Appl. Pyrolysis 2006, 77, 95−101. (7) Bayerbach, R.; Meier, D. J. Anal. Appl. Pyrolysis 2009, 85, 98−107. (8) Oasmaa, A.; Elliott, D. C.; Muller, S. Environ. Prog. Sustainable Energy 2009, 28, 404−409.

ASSOCIATED CONTENT

S Supporting Information *

ESI(−)−MS spectrum using Q-TOF of (a) BO and (b) LBOF from fast pyrolysis of different biomasses (Figure 1S), typical mass spectrum of a eucalyptus BO acquired in Q-TOF MS and FT-ICR MS (Figure 2S), oxygen class distribution for (a) water hyacinth BO and (b) eucalyptus BO (Figure 3S), and estimated molecular formulas for the measured m/z values from ESI(−)− FT-ICR MS eucalyptus BO results for O2 compounds (Table 6653


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