Article pubs.acs.org/EF
Oil Shale Pyrolysis: Conversion Dependence of Kinetic Parameters Juliana Pedrilho Foltin,†,‡ Antonio Carlos Luz Lisboa,‡ and Arno de Klerk*,† †
Department of Chemical and Materials Engineering, University of Alberta, 9211 116th Street, Edmonton, Alberta T6G 1H9, Canada School of Chemical Engineering, The State University of Campinas (UNICAMP), Campinas - SP, Brazil
‡
ABSTRACT: Oil can be recovered from kerogen in oil shale by pyrolysis. The devolatilization kinetics of the pyrolysis of oil shale from the Irati Formation in Brazil was studied. Kinetic parameters were determined from dynamic thermogravimetric analysis over the temperature range 323−1173 K, using different model-free methods. Evaluation and validation were performed by pyrolysis at 673 K for 3 hours. It was found that the activation energy depended on the extent of conversion. Activation energy increased over the range 215−255 kJ/mol for conversion in the range 0.15 ≤ α ≤ 0.55, where α = 1 for pyrolysis at 1173 K. When the reaction rate was high, the conversion calculated using kinetic parameters derived by the Friedman method was more accurate than those calculated from the Flynn−Wall−Ozawa and the Kissinger−Akahira−Sunose methods. The latter two methods performed better when the reaction rate was lower, i.e., at higher conversion. Isothermal kerogen pyrolysis approached an incomplete conversion limit that could be increased only by increasing the temperature; this type of behavior was predicted by the conversion dependence of activation energy. The observed activation energy is an average of the different activation energies of the individual compounds in kerogen. As conversion progresses, the compounds with lower activation energies are more readily converted, so that the average activation energy of the compounds that remain increases with increasing conversion. The work highlighted the importance of employing conversion-dependent kinetic parameters when modeling oil shale pyrolysis for process design, especially when the process is designed for high kerogen conversion. This investigation had two objectives. The first objective was to develop a kinetic description of devolatilization by pyrolysis of oil shale from the Irati Formation in Brazil. The second objective was to evaluate the performance of different approaches to the kinetic modeling of oil shale pyrolysis for practical application. The scope of the kinetic investigation was restricted to the use of thermogravimetric analysis (TGA) as a tool for kinetic measurements, although the interpretation of the pyrolysis behavior was supplemented by characterization and spectroscopic analyses of the oil shale. TGA has been successfully employed for the development of pyrolysis kinetics with various oil shales.15−19 The data were modeled using model-free and model-fitting approaches in order to evaluate the activation energy and the pre-exponential factor.20,21 This was followed by a critical evaluation of the kinetics and the implications for practical use in the design of oil shale pyrolysis processes.
1. INTRODUCTION The term “shale” is used to describe geologically quite different geological formations, but the formations have some common features. The organic component (kerogen) is geologically immature, with low solubility in solvents, which can be converted to oil and gas by pyrolysis.1−3 Oil shale deposits are widely distributed, with the most abundant deposits found in the United States and Brazil, and significant deposits exist in Russia, Congo, Canada, Italy, China, Australia and Estonia.4,5 Above-ground mining and in situ subsurface recovery methods are used for oil shale, but unlike oil sands, the organic component cannot effectively be displaced at moderate temperatures by water or organic solvents; shale oil recovery from oil shale requires temperatures in excess of 300 °C.6 Potentially commercially attractive grades of oil shale contain at least 0.1 m3/t (∼25 US gal/t) recoverable oil.4 When reviewing the technologies developed or employed for shale oil production from oil shale,5,7−11 it is immediately apparent that pyrolysis plays a central role. The devolatilization kinetics is important in describing the rate of oil evolution as a function of pyrolysis time and temperature. This important first step in the development of process technology is the topic of this work. Pyrolysis of the oil shale to liberate shale oil involves a complex reaction network, and it involves the breaking of bonds with different activation energies within the organic matter and between the organic and mineral matter.12,13 There is consequently a distribution of activation energies, rather than a single activation energy, that must be considered during pyrolysis. The actual time−temperature−gas environment also affects the composition of the shale oil produced by oil shale pyrolysis, which in turn affects downstream refining.14 However, this aspect was not studied. © 2017 American Chemical Society
2. EXPERIMENTAL SECTION 2.1. Materials. The oil shale used in this study was extracted from the Irati Formation and supplied by Petrobras/SIX, located in São Mateus do Sul, Parana, Brazil. Two samples were employed in this study, with particle size ranges of 0.297−0.354 mm (48 mesh to 42 mesh) and 0.500−0.595 mm (32 mesh to 28 mesh). These size fractions were obtained by sieving the material using Tyler screens, for example, recovering material that passed through a 42 mesh, but did not pass through a 48 mesh Tyler screen. The smaller particle range was employed for the kinetic study, while the larger particle range was employed to check that mass transfer was not limiting. The oil shale was characterized as part of the investigation (see section 3.1). The Received: February 25, 2017 Revised: June 6, 2017 Published: June 27, 2017 6766
DOI: 10.1021/acs.energyfuels.7b00578 Energy Fuels 2017, 31, 6766−6776
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Energy & Fuels focus was on the kerogen and mineral matter components that may affect pyrolysis and the kinetic investigation. X-ray diffraction data is also presented, but characterization did not include a full mineralogical characterization, which was reported in the literature recently.22 2.2. Equipment, Procedure, and Analyses. Oil shale pyrolysis was studied using thermogravimetric analysis with dynamic heating. In a typical experiment, around 9.5 mg of oil shale with particle size range of 0.297−0.354 mm was weighed and put inside an alumina crucible, with the exact weight being recorded using a Mettler Toledo XS105 balance with 0.01 mg readability. The mass loss versus a defined temperature measurement was performed using a Mettler Toledo TGA/DSC1, LF 1100 furnace, with MX5 microbalance having a measuring range of 5 g and 1 μg readability. The analyses were performed under constant nitrogen flow rate of 50 mL/min. The measurements were conducted at atmospheric pressure, which in Edmonton, AB, Canada is on average 93 kPa because of its altitude. Mass loss was recorded over the temperature range 373−1173 K (100−900 °C) at different heating rates (β): 2, 5, 10, 15, 20, 25, 40, and 50 K/min. The final mass was considered to be mineral matter and unrecoverable organic matter, i.e., all material that did not form vapor and gaseous products. Two control experiments were also performed by TGA using 9.5 mg oil shale, one employing the 0.297−0.354 mm size range that was used for all TGA with dynamic heating, the other employing the 0.500−0.595 mm size range. The TGA of each sample was conducted under constant nitrogen flow rate of 50 mL/min. The temperature program had three segments: dynamic heating at β = 50 K/min from 323 to 673 K, then remaining isothermal at 673 K for 180 min, and finally dynamic heating at β = 50 K/min from 673 to 1173 K. The objectives of these experiments were to provide isothermal kinetics for validating the kinetic analysis performed by nonisothermal TGA, as well as to determine whether mass transport meaningfully affected the kinetic analysis. In addition to the pyrolysis experiments performed by TGA, pyrolysis was also studied by infrared spectroscopy. For this purpose, an ABB MB3000 Fourier transform infrared (FTIR) spectrometer was employed, which was equipped with a Pike DiffusIR attachment that has an environmental chamber. The environmental chamber is temperature-controlled and can be heated to 773 K. The oil shale (3.5 mg) was mixed with potassium bromide (35.0 mg) and pressed into the sample holder. The environmental chamber was purged with nitrogen, and the oil shale was heated to different temperatures at which the infrared spectra were recorded. Infrared spectra were collected with the following parameters: resolution of 16 cm−1, average of 120 scans, 729 detector gain, and spectral range of 5000−500 cm−1. Oil shale characterization was performed using different techniques. Proximate analysis was performed using a Leco TGA 701 in accordance with ASTM Standard 7582 test method for coal.23 CHNSO elemental analysis of the organic matter was performed using a Thermo Fisher Flash 2000 Organic Elemental Analyzer. Elemental analysis of the elements heavier than Na in the shale oil was performed with a Bruker S2 Ranger X-ray fluorescence (XRF) spectrometer. The X-ray diffraction (XRD) data was collected using a Philips X’PERT MPD diffractometer.
Table 1. Proximate Analysis of the Oil Shale from the Irati Formation, Southern Brazil description
proximate analysis (wt %) Measured
moisture volatile matter fixed carbon ash
1.8 18.8 2.8 76.6 Calculated
volatile matter, dry basis fixed carbon, dry basis ash, dry basis
19.1 2.8 78.1
Table 2. CHNSO Elemental Analysis of the Oil Shale from the Irati Formation, Southern Brazil description
ultimate analysis (wt %)
carbon hydrogen nitrogen sulfur oxygen mineralsa
14.0 1.9 0.3 3.8 6.3 73.7
a
Calculated by difference; material not converted to COx, H2O, N2, and SO2 under pyrolytic and oxidative pyrolytic conditions.
exclude the detection of those elements derived from mineral matter. The method of CHNS determination involves hightemperature pyrolytic oxidation with detection of CO2, H2O, N2, and SO2. Residual water and minerals that can produce any of the aforementioned gases would cause an increase in the reported values for the corresponding CHNS elements. Oxygen content is determined separately and relies on the formation of CO so that any reduction of mineral matter with transfer of oxygen to the organic matter will increase the reported oxygen content. The oil shale was not porous, and the total surface area was 1000 K10 and would not interfere with a TGA-based kinetic analysis of kerogen pyrolysis. Nevertheless, it was worthwhile to confirm whether carbonate minerals were present in meaningful quantities in the oil shale. Metal carbonates have two characteristic absorption bands in the infrared spectrum, a strong absorption at 1450−1410 cm−1 and a less intense absorption at 880−850 cm−1.35 A minor absorption band was found at 1443 cm−1, and no associated absorption band in the 880−850 cm−1 was detectable in the infrared spectra (Figure 4), which indicated a low carbonate content. This was consistent with the literature for this particular oil shale deposit.21 Furthermore, no carbonate minerals were identified (Figure 1). Characterization of the minerals found at different depths and locations in the Irati Formation indicated that quartz, albite, and smectite were common to all samples. Illite was also found in all samples, but in one it was present in low quantity. Other minerals that were found in only some of the samples were pyrite, kaolinite, chlorite, analcine and gypsum.21 Figure 1 indicated that silicon dioxide (e.g., quartz) and aluminum silicates (e.g., albite and smectite) were present and that illite was possibly present. The possible presence of iron pyrite (FeS2), as identified in some Irati oil shale samples,13,21 bore further investigation. In the presence of organic matter at elevated temperature, iron pyrite can result in transfer of sulfur to the organic matter, thereby affecting the composition of the oil kerogen. Analysis of the oil shale indicated a high content of both Fe and S (Table 3), but the molar ratio of Fe:S was 1:0.6; therefore, only some of the Fe could be in the form of iron pyrite. The presence of iron pyrite could not be confirmed by infrared spectroscopy, because the main infrared absorption band of iron pyrite is found at 350 cm−1.36 No evidence of iron pyrite was found by X-ray diffraction analysis (Figure 1); in fact, iron oxide was one of the main components on the oil shale. Even though some iron pyrite might have been present, the transfer of sulfur is slow, and it was unlikely that it would meaningfully interfere with the kinetic analysis. For example, it was found that iron pyrite decomposition at 673 K for 20 h affected a region of about 1 μm of organic matter in coal.37 4.3. Deriving Kinetics from TGA Data. The use of TGA to determine devolatilization kinetics during pyrolysis is one of the more reliable experimental approaches reported in the literature.27 Its main drawbacks for kinetic analysis are the comparatively slow heating rate and temperature limitations;27 the latter is not a relevant limitation in this study. Kinetics parameters were determined by relating the mass loss versus temperature response at different heating rates to the oil shale pyrolysis kinetics. The kinetics of decomposition analysis are based on the Arrhenius equation (eq 1) and kerogen transformation rate for the volatile product (eq 2):
contributed to catalysis in region IIb. However, no work was done to distinguish between mineral-catalyzed and thermal reactions. It should further be pointed out that the measured surface area of the oil shale was 210 kJ/mol for the other methods (Table 6). The values obtained from the Coats− Redfern method were too low to be realistic. When the pyrolysis of oil shale from the Irati Formation was studied using electron spin resonance (ESR) spectroscopy,38 two first-order reactions occurring in parallel were identified as the main free radical producing reactions. The activation energies for these two reactions were 226 ± 7 and 150 ± 40 kJ/ mol respectively, with associated pre-exponential factors of 0.9 × 1017 and 2.3 × 109 h−1 (or for comparison with Table 6, 1.5 × 1015 and 3.8 × 107 min−1). As another point of reference, Petersen et al.13 reported an activation energy distribution for Irati oil shale. There was a minor contribution of activation energies in the ranges 167− 192 and 247−260 kJ/mol, but most of the material had activation energies in the range 201−238 kJ/mol. The activation energy distribution centered around 218−222 kJ/ mol, which represented 63% of the kerogen. The average pre-
Table 6. Calculated Pre-exponential Factor (k0, min−1) and Activation Energy (E, kJ/mol) for the Pyrolysis Reaction Using Different Model-Free Methods Friedman α a
0.05 0.10a 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65 a
E
k0
143 141 221 217 232 234 228 249 240 253 269 300 328
× × × × × × × × × × × × ×
2.7 2.1 8.1 2.1 2.5 3.0 9.4 2.4 4.4 3.0 3.0 2.0 4.6
Flynn−Wall−Ozawa r2
12
10 1010 1015 1015 1016 1016 1015 1017 1016 1017 1018 1020 1021
0.773 0.955 0.982 0.995 0.999 0.998 0.995 0.994 0.995 0.988 0.969 0.931 0.703
E
k0
121 180 216 219 211 218 240 239 246 237 245 255 301
× × × × × × × × × × × × ×
1.0 2.7 1.7 1.0 1.8 4.6 1.5 1.1 3.0 4.8 1.7 5.6 5.6
Kissinger−Akahira−Sunose r2
11
10 1014 1016 1016 1015 1015 1017 1017 1017 1016 1017 1017 1020
0.895 0.895 0.977 0.993 0.990 0.996 0.995 0.998 0.992 0.997 0.992 0.982 0.868
E
k0
119 179 216 219 211 218 240 240 247 237 246 256 304
× × × × × × × × × × × × ×
5.3 2.3 1.7 1.0 1.6 4.3 1.6 1.2 3.3 4.8 1.8 6.3 8.3
r2 10
10 1014 1016 1016 1015 1015 1017 1017 1017 1016 1017 1017 1020
0.881 0.884 0.975 0.992 0.989 0.995 0.995 0.998 0.991 0.996 0.992 0.981 0.858
Region I, kinetic analysis invalid because of significant contribution of evaporation without pyrolysis. 6772
DOI: 10.1021/acs.energyfuels.7b00578 Energy Fuels 2017, 31, 6766−6776
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Energy & Fuels exponential factor was 4.4 × 1013 s−1 (or for comparison with Table 6, 2.6 × 1015 min−1). These values are close to the values the conversion range 0.15 ≤ α ≤ 0.30 reported in Table 6. Considerable variation in activation energies reported for different types of oil shale is found, e.g. see refs 12, 13, and 39, but the activation energy values for Irati oil shale calculated by the Coats−Redfern method were clearly outside of the range of realistic values. The failure of the Coats−Redfern method to yield realistic results may be related to the model used. A large number of reaction models have been proposed.18 A systematic evaluation of all the possible reaction models was not undertaken, because all of the models are based on the assumption that there is a single reaction pathway. However, the ESR investigation of Irati oil shale pyrolysis showed two reaction pathways,38 and the same is reported in more general overviews.14 4.4. Conversion Dependence of Activation Energy. The activation energy for the pyrolysis reaction changes with conversion (Table 6). This can be more clearly seen when plotting the activation energy as a function of conversion (Figure 11). The values derived from the kinetic analysis
determine the kinetics, but that too would be an oversimplification. However, in the literature it is not uncommon to find that investigators report a single average value for activation energy, because it enables an analytical solution for the reaction kinetics. For conversion in the region 0.15 ≤ α ≤ 0.55, the values for activation energy are mainly in the range 215−255 kJ/mol−1. However, using a single value for activation energy is an oversimplification, which not only averages the activation energy distribution at a specific level of conversion but also averages the activation energies over different levels of conversion. Kerogen is not a single substance. The measurement of the overall pyrolysis kinetics is a measurement of the contribution of numerous different reactions in parallel. Each of these pyrolysis reactions has its own activation energy, and the activation energies for pyrolysis of different species can be quite different. The activation energies can be represented as a distribution curve of fraction of kerogen in relation to activation energy. For example, this was done in the development work performed by ExxonMobil (normal distribution with activation energies ranging from 209−234 kJ/mol)40 and by Petersen et al. (distributions of activation energies that were not necessarily normal distributions).13 It is convenient to lump the different species together and express the activation energy as a single value, because it makes the analytical solution of the rate equation possible. However, that does not make the actual system homogeneous, and it is questionable whether this type of mathematical simplification is necessary. The rate at which the species with low pyrolysis activation energy is depleted is not the same as the rate at which the species with high pyrolysis activation energy are depleted. Because all of the reactions are pyrolysis-type reactions, it is likely that the reactions requiring low activation energy would proceed more rapidly and start proceeding at lower temperature than those requiring high activation energy, despite potential differences in their pre-exponential factor. With an increase in conversion there will be change in the ratio of pyrolysis reactions requiring low activation energy compared to pyrolysis reactions requiring high activation energy. The relative contribution of different activation energies will consequently change to indicate that on average higher activation energy is required for pyrolysis as conversion is increased (Figure 11). This is not a consequence of the increase in temperature, but a consequence of the extent of conversion that changes the chemical nature of the kerogen. 4.5. Conversion Dependence of Observed Kinetics. A known but often ignored drawback of TGA as a technique for determining oil shale pyrolysis kinetics is that the detection of conversion is related to the detection of mass loss. Reactions leading to the formation of oil products that are not volatile at the measurement temperature will not be recorded as a mass loss by TGA. Likewise, there are reactions, leading to coke-like residue remaining on the mineral matter,10 that cannot be observed by TGA either, because the product is not volatile. At lower pyrolysis temperatures and lower conversion levels, there is a higher chance of reactions of the type kerogen → nonvolatile product + volatile product, instead of kerogen → volatile products. The impact of this can be seen from the isothermal pyrolysis of the oil shale data at 673 K in the control experiments. When the data in Figure 3 is converted into conversion rate (dα/dt) and plotted as a function of reaction time (Figure 12), the isothermal conversion rate passes through
Figure 11. Activation energies calculated by model-free methods as a function of conversion.
represent weighted averages of activation energy distributions.12,13 With increasing conversion it is also possible that there is a change in the shape of the distribution of activation energies of the kerogen. The kinetic analysis did not determine the change in the shape of the activation energy distribution at different conversion levels, only that there was a progressive increase in average activation energy with increasing conversion. Burnham14 makes the point clearly that the model description of kerogen → bitumen → oil and gas is not supported by experimental evidence, despite its persistence in the literature. There are at least two paths to oil and gas. The existence of at least two major pathways to oil and gas during pyrolysis is also supported by quantitative ESR analysis.38 Any change in the ratio of these two pathways would lead to a change in the observed activation energy. Because it is likely that the contribution of the energetically more demanding pathway would increase with temperature, the observed increase in activation energy with conversion is also reflective of the increase in temperature at which the conversion was found during TGA. This observation might suggest that the reported increase in activation energy with conversion (Table 6) is a consequence of using TGA with dynamic heating to 6773
DOI: 10.1021/acs.energyfuels.7b00578 Energy Fuels 2017, 31, 6766−6776
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Energy & Fuels E = 1990·α 3 − 1820·α 2 + 600·α + 160
(11)
This was an approximation only, with a correlation coefficient of r2 = 0.975, and should be considered empirical with no fundamental basis. Alternative approaches to represent conversion dependent activation energy can be found in the literature, e.g., see ref 45. The same approach as in eq 11 was followed for the pre-exponential factor. To do so, the rate constant k was calculated for each data point in Table 6 at 673 K; using the E value determined by eq 11, for each k, the matching k0 was calculated. The k0 values were then regressed (eq 12), and the correlation coefficient of the regression was r2 = 0.999. The good correlation between k0 and E, both as functions of α, is indicative of what Janković17 calls the kinetic compensation effect. ln k 0 = 230·α 3 − 200·α 2 + 63.5·α + 29.9
Figure 12. Reaction rate during isothermal conversion of oil shale at 673 K, with t = 0 defined as the time at which 673 K was reached.
(12)
When the conversion dependence of the kinetics is considered, the time required in order to reach a specific level of conversion is different compared to an approximation using only a single value for the rate constant. This is illustrated by Figure 13, which compares the reaction time required for
a maximum. This is not related to mass transport, because both size ranges of oil shale resulted in very similar reaction rates based on TGA mass loss. The initially lower reaction rate is likely due to the formation of pyrolysis products that are not volatile and therefore not detected. This type of pyrolysis behavior appears similar to that observed during the thermal cracking of waxes, which develops a bimodal carbon number distribution during pyrolysis.42 The heavier products decrease over time with increasing conversion, but there is an equal probability of cracking for all bonds of similar strength. Thus, heavy products do not just form light products. Although kerogen is not wax, chemical bonds of equal strength will have equal probability of homolytic bond dissociation. Hence, the probability of forming nonvolatile products from the kerogen decreases only with increasing level of conversion, because as conversion progresses, the fraction of very heavy material that can form nonvolatile products decreases. 4.6. Implications for Practical Application. The geology of the oil shale formation determines whether mining and retorting or in situ subsurface production technology should be used. Retorting processes operate mainly on the principle of a moving bed for the oil shale with continuous stripping of the vapor phase. The way in which it is implemented differs between technologies. For example, the Petrosix process uses a moving bed similar to that found in moving bed gasifiers; the Tosco II process uses a rotary kiln similar to that found in cement production.5,8,10 In situ subsurface production by definition operate on the principle of a semibatch process, keeping the oil shale stationary and continuously removing the produced oil and gas. The technologies differ mostly in terms of the way in which heating is supplied and subsurface permeability is created.10,41,43,44 Considering the differences in potential application, the implication of this work will be analyzed by looking at how the kinetics describes the rate of oil and gas production by pyrolysis as a function of time. Although the rate equation is first-order with respect to kerogen, in practice the pyrolysis rate is not a simple first-order relationship with respect to time, due to the conversion dependence of the rate constant. The conversion dependence of the activation energy over the conversion range 0.15 ≤ α ≤ 0.65 was regressed as a thirdorder polynomial based on the results (Table 6 and Figure 11) of the Friedman method (eq 11).
Figure 13. Reaction time required after reaching α = 0.15 in order to reach the conversion values indicated. The calculated time is shown for constant k (●), conversion-dependent k (■) based on kinetic derived by the Friedman method, and the experimentally measured conversion (▲).
isothermal reaction at 673 K based on kinetic data determined by the Friedman method using constant values for E and k0 at α = 0.40 (Table 6), the conversion-dependent E and k0 values (eq 11 and 12), and the isothermal kinetics from the control experiment (Figure 3). A temperature of 673 K was selected for the comparison, because the isothermal data in Figure 3 was collected at that temperature; industrial processes typically operate at a higher temperature. There is an observable difference in calculated reaction time required for kerogen conversion using kinetics using a single value for E and k0 and that taking the conversion dependence of E and k0 into account (Figure 13). Using a constant k has potentially serious implications for process design aimed at high kerogen conversion. The activation energy for conversion of the more refractive species in the kerogen is high, and it is these species that remain mostly unconverted during the initial stages of pyrolysis. In the example given (Figure 13), the additional reaction time required for incremental conversion at 673 K increases rapidly as the conversion exceeds about 50%. This is not captured by a description based on a single value for 6774
DOI: 10.1021/acs.energyfuels.7b00578 Energy Fuels 2017, 31, 6766−6776
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Energy & Fuels Notes
activation energy and a conversion-independent kinetic constant. To put this into perspective, the conversion after 3 h of conversion at 673 K can be calculated. The experimentally observed conversion is 68.5%. The conversion-dependent kinetics based on the Friedman method calculated a kerogen conversion of 61.6%. Using conversion-independent kinetics, the calculated conversion is 89.5% after 3 h (and near complete conversion is predicted after 8 h). The control experiments conducted at 673 K (Figure 3) indicated that reaction over a longer period of time is unlikely to lead to near complete conversion. Employing the simplification of a single activation energy for the practical design of an oil shale pyrolysis can lead to an over prediction of the kerogen conversion, especially for designs aimed at more extensive conversion.
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS This study was funded through the program “Science Without Borders”, the University of Alberta, and the State University of Campinas. Mohan S. Pathak (University of Alberta) is thanked for performing the control experiments.
■
5. CONCLUSIONS The mass loss associated with heating of oil shale could be divided into different temperature regions: evaporation of light fraction of kerogen (region I), kerogen pyrolysis (region IIa), kerogen pyrolysis and catalytic cracking by mineral matter (region IIb), and high-temperature decomposition of kerogen and mineral matter (region III). Kinetic analysis was limited to region IIa, where kerogen pyrolysis and cracked product evaporation were the dominant processes. The main conclusions from the work are provided below. (a) Devolatilization kinetics of kerogen pyrolysis was calculated from the nonisothermal TGA measurements by the model-free methods of Friedman, Flynn−Wall−Ozawa, and Kissinger−Akahira−Sunose. It was found that activation energy depended on the extent of conversion and increased over the range 215−255 kJ/mol for conversion in the range 0.15 ≤ α ≤ 0.55, where α = 1 for pyrolysis at 1173 K. (b) Kinetic analysis by the Coats−Redfern method using first-order kinetics was insensitive to heating rate but resulted in activation energies that were unrealistically low. (c) The prediction of kinetics based on the model-free methods was compared against the experimentally measured kinetics during isothermal pyrolysis at 673 K. The reaction rate calculated using kinetic parameters derived by the Friedman method was more accurate than those of other methods at lower conversion, typically 0.15 ≤ α ≤ 0.30, when the reaction rate was high. Kinetic parameters calculated by the Flynn− Wall−Ozawa and Kissinger−Akahira−Sunose methods became more accurate at higher conversion, when reaction rate was lower. (d) Isothermal kerogen pyrolysis approached an incomplete conversion limit that could be increased only by increasing the temperature. This type of behavior was predicted by the conversion dependence of activation energy. The scientific basis for the conversion-dependent change in activation energy could be explained. (e) For process design purposes, the importance of modeling oil shale pyrolysis kinetics with conversion-dependent activation energy was highlighted.
■
■
NOMENCLATURE E = activation energy (kJ/mol) f(α) = reaction model g(α) = integrated reaction model k = reaction rate constant (units depend on reaction order) k0 = pre-exponential factor (min−1 for first order) m = mass of oil shale (mg) mo = mass of oil shale before pyrolysis (mg) mf = mass of oil shale after pyrolysis (mg) n = reaction order r = correlation coefficient for linear regression R = universal gas constant (kJ/mol·K) t = time (min) T = temperature (K) α = kerogen conversion as defined by eq 3 (mg/mg) β = heating rate (K/min) REFERENCES
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AUTHOR INFORMATION
Corresponding Author
*Phone: 780-248-1903. Fax: 780-492-2881. E-mail: deklerk@ ualberta.ca. ORCID
Arno de Klerk: 0000-0002-8146-9024 6775
DOI: 10.1021/acs.energyfuels.7b00578 Energy Fuels 2017, 31, 6766−6776
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DOI: 10.1021/acs.energyfuels.7b00578 Energy Fuels 2017, 31, 6766−6776
