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Kinetic study of isothermal oil shale pyrolysis
Journal of Analytical and Applied Pyrotjwis, 10 (1986) 153-166
153
Elsevier Science Publishers B.V., Amsterdam - Printed in The Netherlands
KINETIC STUDY OF ISOTHJWWAL OIL SHALE PYROLYSIS 1. ~~E~~CAL MODEL OF THE EVOLUTION OF ORGANIC PYROPRODUCTS
H. BAR, R. IRAN and 2. AIZENSHTAT
*
Casali Institute for Applied Chemistry * and the Department of Organic Chemistry, The Hebrew University of Jerusalem, Jerusalem, 9i904 (Israel)
(Received November 14th, 1985; accepted July 22nd, 1986)
SUMMARY An isothermal fluidized bed reactor was used for a kinetic study of oil shale pyrolysis. The rate of volatile hydrocarbon evolution was monitored by flame ionization detector. An innovative approach to the data obtained, which we adopted in the present study, led us to a simple kinetic model. The rate of volatile hydrocarbon evolution is described as a linear combination of three parallel independent first-order reactions characterized by three rate constants, k, = 2.6~10~ exp(-23.6 kcal/RT) s-l, k2 = 2.3.106 exp(-26.0 kcal,/RT) s-l and k3 = 9.3.105 exp( - 28.1 kcal/RT) s-l. The kinetic effect due to the particle size of the sample is probably due to heat transfer effects.
INTRODUCTION
There is ~nsiderabl~ comm~rci~ interest in above-hound oil shale pyrolysis using fluidized bed techniques, which entail rapid heating of the oil shale followed by essentially isothermal retorting with the subsequent rapid removal of the pyrolysis products. A kinetic model is essential for the efficient development of economically feasible conversion technologies. Recently two isothermal kinetic studies using a fluidized bed reactor with flame ionization detector as monitor technique were reported by Wallman et al. [l] and Richardson et al. [2]. In both works a first-order global kinetic was assumed, and semi-logarithmic curves of (1 - conversion) versus time were used for the data interpretation. Both Wallman et al. and Richardson et al. described the rate of oil formation with two sequential first-order rate equations. There is good agreement between the two models for the initial decomposition step; Wallman’s model, however, predicts a dependence of 0165-2370/86/$03.50
0 1986 Ekevier Science Publishers B.V.
154
the second step kinetics and yield on particle size, while Richardson et al. did not find such a dependence. Wallman et al. [l] and Rajeshwar et al. [3] reviewed the few previously published works employing the isothermal approach to the kinetic study of oil shale pyrolysis. Based on the information available at the initiation of the present work it was obvious that the fluidized bed reactor with flame ionization detector is the technique of choice for isothermal kinetic study of oil shale pyrolysis. The above statement can be supported by the comparison of three studies which used the Green River Formation oil shale as feed stock: Hubbard and Robinson [4] reported that at 500 “C the half-life (t,,,) of the reaction is 5-6 min, Allred [S] reported t,,, = 4 min for experiments at 504”C, and Wallman et al. [l] who used the fluidized bed technique reported t,,, = 0.5 min at 498°C. The marked advantage of the fluidized bed for isothermal kinetic study probably stems from two inherent properties: fast (almost instant) heat transfer (solid to solid), and fast sweeping of the sample with an inert gas. It was suggested by Campbell et al. [6] that retention of the pyroproducts in a liquid state could be minimized by both fast heatup and sweeping rates.
EXPERIMENTAL
A small stainless-steel fluidized bed reactor (Fig. 1) was used to pyrolyze small samples of oil shale particles under inert conditions. A weighted sample of the shale, not greater than 0.5% (w/w) of the bed was dropped into the preheated reactor, producing a negligible drop in bed temperature. Heat transfer in the fluidized bed was very rapid, and the volatile products were rapidly swept by the guiding gas (nitrogen) to a flame ionization detector. This system was built with minimum dead volume, which enables the precise follow-up of fast reactions without peak broadening due to diffusion. The vapour residence time in the reactor was usually less than 0.3 s. The flame ionization detector produced a signal proportional to the concentration of the total organic carbon in the product stream. Since the reaction is very fast at the beginning and very slow at the end, the speed of the recorder paper was decreased as the reaction progressed. A measured amount of n-butane was injected into the reactor (through the calibration gas inlet) before and after each experiment for quantitative calibration of the detector. The experimental curves were digitized and the data processing was done by computer. The shale samples were obtained from Zefa-Ef’e deposit (Israel). The samples were sieved, and dried at 11OOC. The organic matter content of this shale was 13.5%; most of it (98%) kerogen and 2% bitumen. The elemental analysis of the kerogen was: C = 66.0% H = 7.3%, S = 8.3% 0 = 16.6%
155
,/piq iEATED
TRANSFER
LINE
\
CWRT
ELECTRO 1
FID
METER
RECORDER
ADJUSTABI
SAMPLE INLET DEVICE
r-’ h
d=
DUST
FILTER
ADjUSTABLE RESTRICT0
R
CALIBRATION GAS INLET CAPILLARY
PIPE
THERMOCOUPLE
Fig. 1. The fluidized bed reactor system.
N = 1.7% and ash = 0.08%. The mineral matrix consists mainly of CaCO,, SiO,, AlSi(O),, and FeS,. Curve fitting technique In order to fit a theoretical curve to an experimental curve five parameters are needed: k,, k,, k,, A: and A;. AT is not necessary since A: + AZ + AT = 1. k, is the value of the observed k at high conversions when the observed k. is constant. AT can be calculated directly from the experimental curve using the formula: (AT -A3)
=A;
exp(-k,t)
where: t = the time passed until we observe the slow reaction only ( kobserved= constant). This value is taken from figures like Fig. 3. (AT - As) = the contribution to the overall conversion of the plateau region [in Fig. 4 for example: (A; - A3) = 100% - 57% = 47%]. The other three parameters, k,, k, and AZ, ?ave to be found by regression analysis. The fitting of the theoretical curves with the experimen-
156
tal one is done now by a “visual” regression, i.e. by plotting an experimental curve on the computer screen and then plotting the theoretical curve changing parameters, rerunning etc. RESULTS AND DISCUSSION
The flame ionization detector essentially measures total organic carbon [7]; therefore the detector output is directly proportional to the rate of organic carbon generation, dA/dt, and the amount of organic carbon produced at any time t, A(t), is proportional to the integral of dA/dt from t = 0 to t (i.e. the area under the curve from t = 0 to t). The total amount of organic carbon produced, A*, is the integral of d A/dt over the total time for the experiment (i.e. the total area under the curve). Yield results
In order to gain a rough estimate of the total yield from the total area under the curves, the detector response was calibrated against Diesel oil (this is of course an arbitrary calibration). It was found that the total amount of products, A*, increased with the reactor temperature, T [therefore it will be designated as A*(T)]. The results of at least five experiments at each temperature are summarized in Table 1. The total yield did not vary (within experimental error) with the change in the particle size (between 0.2 and 3 mm), which is in agreement with the results of Richardson et al. [2] and contradicts the model proposed by Wallman et al. [l]. Kinetic results
An example of the computer data processing is presented in Figs. 2-5. The observed reaction rate constant k (in Fig. 4) was calculated according to the equation: dA/dt k=
[A*-A(t)]”
TABLE 1 Effect of temperature on the total yield Temperature (OC)
Product yield (g org C/lo3
400 450 500 550 600 650
14.7 41.8 43.2 44.6 46.0 47.2
+ 2.3 t_ 2.3 + 2.6 -I_2.7 k 2.8 k 3.1
g shale)
157
,,,,,t‘t‘,‘ttt~iII~~~~“l
0
0
500
1000
TIME
1500
2000
2500
(s)
Fig. 2. First step of the computer data processing: curve of flame ionization detector (FID) response versus time for an experiment at a reactor temperature of 425’C; particle size 0.2-0.3 mm.
where d A/d t is proportional to the height of the curve in Fig. 2, A* - A(t) is proportions to the area under the curve at the right side of the observed point (i.e. the area under the curve from t to the end of the experiment), and n is the reaction order. In an isothermal reaction, a constant k for a certain reaction order is expected. We failed to find a constant k for several reaction orders.
ioo-
25-
0 0
,,,,,1,,,,11,1,1111,1111, 1000 500
TIME
1500
2000
2500
(s)
Fig. 3. Second step of the computer data processing. This curve was obtained by integration of the curve in Fig. 2 and normalization (conversion = A*/A).
158
-7 0
20
80
&N”ERSI;OON
100
%
Fig. 4. Third step of the computer data processing. Natural (~-~)versus conversion ( kobsemedwas calculated by eqn. 1).
logarithms
of the observed
k
However, we found that k (assuming first-order reaction, n = 1) becomes constant at high conversion levels. In order to examine the dependence of k with conversion we plotted curves of the natural logarithms of k versus conversion (Fig. 4). As will be shown later, such curves are very useful for comparing different experiments conducted at different temperatures, or different particle sizes. In Fig. 4, In k continuously decreases until about 57% conversion when it becomes constant. Such behaviour might result from the detection of several simultaneous, independent first-order reactions.
0
500
1500
1000
TIME
2000
(s)
Fig. 5. Fourth step of the computer data processing. Natural logarithms versus time ( kobservedis the slope in the curve at any point in time).
of (1 -conversion)
159
IdAId
t
TIME
Fig. 6. Curve of reaction rate versus time of a combined reaction (dashed line) composed of two hypothetical independent first-order reactions (solid lines).
Fig. 6 shows the curves of the reaction rate versus time of two theoretical reactions (1 and 2), and a curve of the combined reaction (1 + 2). This figure indicates that, from a certain time, the observed k will become constant (2-only), since the fast reaction has already been completed and we are actually following a single reaction. Fig. 4 indicates that k becomes constant from 57% up to 100% conversion. This fact suggests that a small set of reactions will be sufficient to describe the pyrolytic reaction. In order to check this hypothesis we have devised a computer program which draws the curves of In k versus the conversion of a combined reaction consisting of three independent reactions.
k,
the observed reaction
A;-+A, k,
A;-+A,
k was calculated according to the equation
$ (k,ATexp( -kit)
$ (dA/dt)
k 1+2+3=
i=l 3 Z i=l
=
(A; -Aj)
i-l
(2) i AT exp( - kit)
i=l
160
-77
80
20
0
Fig. 7. Experimental conversion.
100
(dashed from Fig. 5) and theoretical
(solid) curves of In k versus
where ki = the rate constant of the i reaction, AT = the contribution of each reaction to the overall conversion (A: + A; + AT = 1 or lOO%), and t = time. The conversion was calculated according to the equation A
1+2+3
=
A,
t
i=l
=
i
A:[1
-
exp( -kit)]
(3)
i=l
In Figs. 7 and 8 the theoretical and the experimental curves are plotted on the same axis. The process of fitting (regression) theoretical curves to the experimental curves is described in the Experimental section. The results of the regression analysis are summarized in Table 2. This table shows that the contribution of the fast reactions to the overall reaction increases with the elevation of the temperature while the contribution of the slow reaction decreases. The values of In k from Table 2 were plotted against the inverse temperature; the resulting values of the activation energies (E,) and the frequency factors (k,) are summarized in Table 3. The above analysis indicates that the overall reaction can be described by the equation A(T, t) = 5 A*(T)i(I
- exp[ -k,,exp(
-E,dRT)]
t)
(4)
i=l
As will be shown later, the actual inner particle temperature is not constant during the reaction due to heat transfer effects. Therefore eqn. 4 holds true only when the particle size is very small.
161
Fig. 8. Experimental (dashed) and theoretical (solid) curves of In k versus conversionat (1) 425OC, (2) 450°C, (3) 475OC, (4) 500°C and (5) 525OC (particlesize0.2-0.3 mm).
TABLE 2 Regression analysis results (k in s- ‘) Temperature
(“C) 425 450 475 500 525
In kl
In k,
In k,
-
- 4.10 - 3.50 -2.90 - 2.40 - 1.70
-6.58 -5.89 -5.26 -4.64 -4.02
2.20 1.75 1.20 0.60 0.10
17 16 18 24 27
23 28 30 37 42
60 56 52 39 31
Recently we reported the results of a fluidized bed kinetic study [8], in which the rate of organic pyroproduct formation was described with two simultaneous independent first-order reactions. The present report is based on new, improved data, which are more reliable and accurate due to
TABLE 3 Activation energies and frequency factors obtained from linear regression analysis of values of In k against l/T given in Table 2 Reaction No.
Activation energy, -J& (kcal/mol)
Frequency factor, k, (s-1.106)
1 2 3
23.6kl.3 26.0 k 1.3 28.1 k 1.5
2.6 +0.12 2.3 +O.ll 0.93 f 0.05
162
TIME
1s)
Fig. 9. Upscaling of the upper left comer of Fig. 5 (see text).
experimental improvements involving, mainly, minimizing the dead volumes in the system. Analysis of the present data indicates that a set of two reactions is not sufficient; three or more reactions are needed to describe the pyrolytic reaction. In order to compare our experiments with those of Wallman et al. [l] and Richardson et al. [2] we plotted the curves of In (1 - conversion) versus time (Fig. 5). Wallman et al. and Richardson et al. approximated such curves by two straight-line segments. The use of curves of In (1 - conversion) versus time might be misleading because (1) k, the reaction rate constant, is measured from the slope of the curve and if the curve is not a straight line it is difficult to determine, and (2) the pyrolytic reaction has an asymptotic behaviour, the curve over-emphasizes the end of the reaction. In fact, the last few percents of the conversion dominate the shape of the curve. Fig. 9 is focused on the upper left corner of Fig. 5, by plotting the data from 0 to 55% conversion only. Obviously this is a curved line; the slope, i.e. kobserved is continuously decreasing. This is in accordance with the direct measurements of k (Fig. 4). Preliminary experiments with an American oil shale (Green River) indicate that this conclusion also holds for this sample (despite the large differences of the mineral matrix and the type of organic matter). Experiments
on partially pyrolyzed
material
Samples of oil shale were pyrolyzed in the reactor for 1.5 h at 400°C (after 1.5 h the reaction was practically completed). The samples were taken out of the reactor, cooled and then pyrolyzed again at a higher temperature (Fig. 10).
163
-5.0
1 0
I 20
1
I %
I
I
I
I .30
I
I 100
4COON&OON
Fig. 10. Kinetics at 500° C of a sample which had been retorted at 400 o C. The values of the theoretical (solid) curve are: Af = 26%, A; = 67%, k, =l s-l, k2 = 0.076 s-l and k3 = 0.01 S-l.
Two stage reaction hypothesis Table 1 shows that the amount of the products increases with the rise in temperature. Table 2 shows that the contribution of the fast and the slow reactions to the overall reaction varies with temperature. Table 3 indicates that the measured activation energies are lower than expected for an ordinary chemical bond cleavage. Fig. 10 indicates that, when a sample which has already been completely retorted at 400°C is pyrolyzed again at a higher temperature, it not only produces more products but there is a contribution from the fast reaction to the overall kinetics, although one would expect to see only the slow reaction. The above results indicate that the reaction pathway is probably not a one-stage mechanism. It is conceivable that the low values of Ea, and EQ2 (Table 3) are not chemically meaningful in the strict sense they were derived by regression analysis (i.e. fitting a sum of exponential5 to an experimental curve). However, Ea, is derived from k, values which are experimentally obtained. Therefore the EO, low value could indicate real lowering of activation energy and thus needs better understanding. There is a possibility that the rate determining step is associated with the volatilization or diffusion of the products. In order to check this possibility, samples of products were taken at different time intervals during the reaction and were analyzed by gas chromatography [9]. It was found that there is a slight increase in the light end products as the reaction progresses, indicating that volatilization and diffusion are probably not the rate determining steps.
164
The same argument could be applied to the results of reactions carried out at higher temperatures (Fig. 8). Exaltation of the curves indicates a similar reaction profile, which in turn can be related to a similar reaction mechanism. The spacing between the various lines produced at different temperatures is almost constant and indicates an activation energy higher than 20 kcal/mol. A change in the rate deter~n~g step to a diffusion controlled reaction at higher temperatures would probably have a marked effect both on the shape of the curve and on the spacing between the curves, leading to unparallel spacing and convergence of the curves. Based on these observations we concluded that in the range of temperatures studied and reported in Fig. 8, diffusion is most likely not the rate determining step. This lowering in activation energy is usually explained by the use of Pitt’s model [lo] which was modified by Anthony et al. [11,12]. This model describes the pyrolytic process by an infinite number of independent first-order parallel reactions represented by a Gaussian distribution of activation energies (a single frequency factor common to all reactions is assumed). Anthony et al. [ll] showed that, if they assume one first-order reaction, the kinetic study yields an activation energy of about 10 kcal/mol, whereas treatment of the results by the modified Pitt model yields a Gaussian dist~bution of activation energies around a mean of 51-56 kcal/mol. This model was developed for coal programmed pyrolysis experiments and was adapted for oil shale programed experiments by Campbell et al. [13] and others. If we examine our results (Figs. 4 and 8) it is obvious that the model suggested by Pitt and Anthony et al. is unacceptable for isothermal experiments. Fig. 4 indicates, for example, that from 57% conversion to the completion of the reaction, the reaction is controlled by one k which leads to one discrete E,. Based on the above discussion we suggest the following two-stage mechanism: (1) The first stage, which is not the rate determining step, is the cleavage of the kerogen to form smaller activated fragments (free radicals) controlling the overall yield of the pyrolytic process. These activated fragments do not volatilize under the reaction conditions. (2) Secondary cleavage of the activated fragments of the first stage to the volatile products follows. Stage two can be described as a linear combination of three first-order reactions. At this stage, chemical bonds which are attached to a free radical site are cleaved, especially bonds /3 to free radical (P-cleavage). Such bond cleavages are associated with low activation energies (30-35 k&/mole) [14]. Rapid secondary reactions (rearrangements, secondary cracking, radical quenching etc.) in the gas phase probably follow the second stage. However, the flame ionization detector measures the total organic carbon converted from solid into organic gases, so reactions such as these could not be followed.
165
-5.05 0
20
40
60
80
100
% CONVERSION
Fig. 11. Kinetics of samples with different particle sizes at 500°C. ((-.-.-) 0.7-l mm, (- - -) 1.4-2 mm
) 0.2-0.3 mm,
The effect of particle size on the kinetics
Fig. 11 shows curves of In k versus conversion for experiments which were performed on samples of different particle size. The results indicate that even after the initial heating stage of the particle, there is a difference between k observed for small and for large particles. At low conversions the observed k for a reaction with small particles is greater (i.e. the reaction is faster) than for larger particles. As the reaction progresses, the observed k for small and large particles converge to the same value. This phenomenon becomes dominant as the temperature of the experiment increases, and might stem from heat transfer effects. The pyrolytic reaction is endothermic; there is probably a heat flux from the outer surface into the core of the particle during all the reaction stages. Therefore, there is a temperature gradient from the surface inwards. This gradient is proportional to the volume:surface ratio (i.e. the particle diameter) and to the reaction rate [15]. Since the reaction rate slows with time, the gradient decreases and the internal particle temperature increases until it reaches the effluent gas temperature, at which point the difference between the observed k of small and large particles disappears.
REFERENCES 1 P.H. Wallman, P.W. Tamm and B.G. Spars, in H.L. Stauffer (Editor), Oil Shale Tar Sands and Related Materials, ACS Symposium Series 163, American Chemical Society, Washington, DC, 1981, p. 93.
166 2 J.H. Richardson, E.B. Huss, L.L. Ott, J.E. Clarkson, M.O. Bishop, J.R. Taylor, L.J. Gregory and J.C. Morris, Fluidized-bed pyrolysis of oil shale: oil yield, composition and kinetics, UCID-19548, Lawrence Livermore National Laboratory, Livermore, CA, 1981. 3 K. Rajeshwar, R. Nottenburg and J. Dubow, J. Mater. Sci., 14 (1979) 2025. 4 A.B. Hubbard and W.E. Robinson, A thermal decomposition study of Colorado oil shale, Rep. Invest. U.S. Bur. Mines 4744, 1950. 5 V.D. Allred, Chem. Eng. Progr., 62 (1966) 55. 6 J.H. Campbell, G.H. Koskinas, T.T. Cobum and N.D. Stout, Oil shale retorting: Part 1. The effects of particle size and heating rate on oil evolution and intraparticle oil degradation, UCRL-52256 Lawrence Livermore National Laboratory, Livermore, CA, 1977. 7 R.A. Jones, An Introduction to Gas-Liquid Chromatography, Academic Press, New York, 1970. 8 H. Bar, M. Sc. Thesis, The Hebrew University of Jerusalem, 1984. 9 H. Bar, R. Ikan and Z. Aizenshtat, J. Anal. Appl. Pyrol, 10 (1986) 167. 10 G.J. Pitt, Fuel, 41 (1962) 267. 11 D.B. Anthony, J.B. Howard, H.C. Hottel and H.P. Meissner, Fifteenth Symposium (International) on Combustion, The Combustion Institute, Pittsburgh, PA, 1975, p. 1303. 12 D.B. Anthony and J.B. Howard, AIChE J., 22 (1976) 625. 13 J.H. Campbell, G. Gallegos and M. Gregg, Fuel, 59 (1980) 727. 14 J.H. RaIey, Fuel, 59 (1980) 419. 15 0. Levenspiel, Chemical Reaction Engineering, Wiley, New York, 2nd ed., 1972, p. 477.
153
Elsevier Science Publishers B.V., Amsterdam - Printed in The Netherlands
KINETIC STUDY OF ISOTHJWWAL OIL SHALE PYROLYSIS 1. ~~E~~CAL MODEL OF THE EVOLUTION OF ORGANIC PYROPRODUCTS
H. BAR, R. IRAN and 2. AIZENSHTAT
*
Casali Institute for Applied Chemistry * and the Department of Organic Chemistry, The Hebrew University of Jerusalem, Jerusalem, 9i904 (Israel)
(Received November 14th, 1985; accepted July 22nd, 1986)
SUMMARY An isothermal fluidized bed reactor was used for a kinetic study of oil shale pyrolysis. The rate of volatile hydrocarbon evolution was monitored by flame ionization detector. An innovative approach to the data obtained, which we adopted in the present study, led us to a simple kinetic model. The rate of volatile hydrocarbon evolution is described as a linear combination of three parallel independent first-order reactions characterized by three rate constants, k, = 2.6~10~ exp(-23.6 kcal/RT) s-l, k2 = 2.3.106 exp(-26.0 kcal,/RT) s-l and k3 = 9.3.105 exp( - 28.1 kcal/RT) s-l. The kinetic effect due to the particle size of the sample is probably due to heat transfer effects.
INTRODUCTION
There is ~nsiderabl~ comm~rci~ interest in above-hound oil shale pyrolysis using fluidized bed techniques, which entail rapid heating of the oil shale followed by essentially isothermal retorting with the subsequent rapid removal of the pyrolysis products. A kinetic model is essential for the efficient development of economically feasible conversion technologies. Recently two isothermal kinetic studies using a fluidized bed reactor with flame ionization detector as monitor technique were reported by Wallman et al. [l] and Richardson et al. [2]. In both works a first-order global kinetic was assumed, and semi-logarithmic curves of (1 - conversion) versus time were used for the data interpretation. Both Wallman et al. and Richardson et al. described the rate of oil formation with two sequential first-order rate equations. There is good agreement between the two models for the initial decomposition step; Wallman’s model, however, predicts a dependence of 0165-2370/86/$03.50
0 1986 Ekevier Science Publishers B.V.
154
the second step kinetics and yield on particle size, while Richardson et al. did not find such a dependence. Wallman et al. [l] and Rajeshwar et al. [3] reviewed the few previously published works employing the isothermal approach to the kinetic study of oil shale pyrolysis. Based on the information available at the initiation of the present work it was obvious that the fluidized bed reactor with flame ionization detector is the technique of choice for isothermal kinetic study of oil shale pyrolysis. The above statement can be supported by the comparison of three studies which used the Green River Formation oil shale as feed stock: Hubbard and Robinson [4] reported that at 500 “C the half-life (t,,,) of the reaction is 5-6 min, Allred [S] reported t,,, = 4 min for experiments at 504”C, and Wallman et al. [l] who used the fluidized bed technique reported t,,, = 0.5 min at 498°C. The marked advantage of the fluidized bed for isothermal kinetic study probably stems from two inherent properties: fast (almost instant) heat transfer (solid to solid), and fast sweeping of the sample with an inert gas. It was suggested by Campbell et al. [6] that retention of the pyroproducts in a liquid state could be minimized by both fast heatup and sweeping rates.
EXPERIMENTAL
A small stainless-steel fluidized bed reactor (Fig. 1) was used to pyrolyze small samples of oil shale particles under inert conditions. A weighted sample of the shale, not greater than 0.5% (w/w) of the bed was dropped into the preheated reactor, producing a negligible drop in bed temperature. Heat transfer in the fluidized bed was very rapid, and the volatile products were rapidly swept by the guiding gas (nitrogen) to a flame ionization detector. This system was built with minimum dead volume, which enables the precise follow-up of fast reactions without peak broadening due to diffusion. The vapour residence time in the reactor was usually less than 0.3 s. The flame ionization detector produced a signal proportional to the concentration of the total organic carbon in the product stream. Since the reaction is very fast at the beginning and very slow at the end, the speed of the recorder paper was decreased as the reaction progressed. A measured amount of n-butane was injected into the reactor (through the calibration gas inlet) before and after each experiment for quantitative calibration of the detector. The experimental curves were digitized and the data processing was done by computer. The shale samples were obtained from Zefa-Ef’e deposit (Israel). The samples were sieved, and dried at 11OOC. The organic matter content of this shale was 13.5%; most of it (98%) kerogen and 2% bitumen. The elemental analysis of the kerogen was: C = 66.0% H = 7.3%, S = 8.3% 0 = 16.6%
155
,/piq iEATED
TRANSFER
LINE
\
CWRT
ELECTRO 1
FID
METER
RECORDER
ADJUSTABI
SAMPLE INLET DEVICE
r-’ h
d=
DUST
FILTER
ADjUSTABLE RESTRICT0
R
CALIBRATION GAS INLET CAPILLARY
PIPE
THERMOCOUPLE
Fig. 1. The fluidized bed reactor system.
N = 1.7% and ash = 0.08%. The mineral matrix consists mainly of CaCO,, SiO,, AlSi(O),, and FeS,. Curve fitting technique In order to fit a theoretical curve to an experimental curve five parameters are needed: k,, k,, k,, A: and A;. AT is not necessary since A: + AZ + AT = 1. k, is the value of the observed k at high conversions when the observed k. is constant. AT can be calculated directly from the experimental curve using the formula: (AT -A3)
=A;
exp(-k,t)
where: t = the time passed until we observe the slow reaction only ( kobserved= constant). This value is taken from figures like Fig. 3. (AT - As) = the contribution to the overall conversion of the plateau region [in Fig. 4 for example: (A; - A3) = 100% - 57% = 47%]. The other three parameters, k,, k, and AZ, ?ave to be found by regression analysis. The fitting of the theoretical curves with the experimen-
156
tal one is done now by a “visual” regression, i.e. by plotting an experimental curve on the computer screen and then plotting the theoretical curve changing parameters, rerunning etc. RESULTS AND DISCUSSION
The flame ionization detector essentially measures total organic carbon [7]; therefore the detector output is directly proportional to the rate of organic carbon generation, dA/dt, and the amount of organic carbon produced at any time t, A(t), is proportional to the integral of dA/dt from t = 0 to t (i.e. the area under the curve from t = 0 to t). The total amount of organic carbon produced, A*, is the integral of d A/dt over the total time for the experiment (i.e. the total area under the curve). Yield results
In order to gain a rough estimate of the total yield from the total area under the curves, the detector response was calibrated against Diesel oil (this is of course an arbitrary calibration). It was found that the total amount of products, A*, increased with the reactor temperature, T [therefore it will be designated as A*(T)]. The results of at least five experiments at each temperature are summarized in Table 1. The total yield did not vary (within experimental error) with the change in the particle size (between 0.2 and 3 mm), which is in agreement with the results of Richardson et al. [2] and contradicts the model proposed by Wallman et al. [l]. Kinetic results
An example of the computer data processing is presented in Figs. 2-5. The observed reaction rate constant k (in Fig. 4) was calculated according to the equation: dA/dt k=
[A*-A(t)]”
TABLE 1 Effect of temperature on the total yield Temperature (OC)
Product yield (g org C/lo3
400 450 500 550 600 650
14.7 41.8 43.2 44.6 46.0 47.2
+ 2.3 t_ 2.3 + 2.6 -I_2.7 k 2.8 k 3.1
g shale)
157
,,,,,t‘t‘,‘ttt~iII~~~~“l
0
0
500
1000
TIME
1500
2000
2500
(s)
Fig. 2. First step of the computer data processing: curve of flame ionization detector (FID) response versus time for an experiment at a reactor temperature of 425’C; particle size 0.2-0.3 mm.
where d A/d t is proportional to the height of the curve in Fig. 2, A* - A(t) is proportions to the area under the curve at the right side of the observed point (i.e. the area under the curve from t to the end of the experiment), and n is the reaction order. In an isothermal reaction, a constant k for a certain reaction order is expected. We failed to find a constant k for several reaction orders.
ioo-
25-
0 0
,,,,,1,,,,11,1,1111,1111, 1000 500
TIME
1500
2000
2500
(s)
Fig. 3. Second step of the computer data processing. This curve was obtained by integration of the curve in Fig. 2 and normalization (conversion = A*/A).
158
-7 0
20
80
&N”ERSI;OON
100
%
Fig. 4. Third step of the computer data processing. Natural (~-~)versus conversion ( kobsemedwas calculated by eqn. 1).
logarithms
of the observed
k
However, we found that k (assuming first-order reaction, n = 1) becomes constant at high conversion levels. In order to examine the dependence of k with conversion we plotted curves of the natural logarithms of k versus conversion (Fig. 4). As will be shown later, such curves are very useful for comparing different experiments conducted at different temperatures, or different particle sizes. In Fig. 4, In k continuously decreases until about 57% conversion when it becomes constant. Such behaviour might result from the detection of several simultaneous, independent first-order reactions.
0
500
1500
1000
TIME
2000
(s)
Fig. 5. Fourth step of the computer data processing. Natural logarithms versus time ( kobservedis the slope in the curve at any point in time).
of (1 -conversion)
159
IdAId
t
TIME
Fig. 6. Curve of reaction rate versus time of a combined reaction (dashed line) composed of two hypothetical independent first-order reactions (solid lines).
Fig. 6 shows the curves of the reaction rate versus time of two theoretical reactions (1 and 2), and a curve of the combined reaction (1 + 2). This figure indicates that, from a certain time, the observed k will become constant (2-only), since the fast reaction has already been completed and we are actually following a single reaction. Fig. 4 indicates that k becomes constant from 57% up to 100% conversion. This fact suggests that a small set of reactions will be sufficient to describe the pyrolytic reaction. In order to check this hypothesis we have devised a computer program which draws the curves of In k versus the conversion of a combined reaction consisting of three independent reactions.
k,
the observed reaction
A;-+A, k,
A;-+A,
k was calculated according to the equation
$ (k,ATexp( -kit)
$ (dA/dt)
k 1+2+3=
i=l 3 Z i=l
=
(A; -Aj)
i-l
(2) i AT exp( - kit)
i=l
160
-77
80
20
0
Fig. 7. Experimental conversion.
100
(dashed from Fig. 5) and theoretical
(solid) curves of In k versus
where ki = the rate constant of the i reaction, AT = the contribution of each reaction to the overall conversion (A: + A; + AT = 1 or lOO%), and t = time. The conversion was calculated according to the equation A
1+2+3
=
A,
t
i=l
=
i
A:[1
-
exp( -kit)]
(3)
i=l
In Figs. 7 and 8 the theoretical and the experimental curves are plotted on the same axis. The process of fitting (regression) theoretical curves to the experimental curves is described in the Experimental section. The results of the regression analysis are summarized in Table 2. This table shows that the contribution of the fast reactions to the overall reaction increases with the elevation of the temperature while the contribution of the slow reaction decreases. The values of In k from Table 2 were plotted against the inverse temperature; the resulting values of the activation energies (E,) and the frequency factors (k,) are summarized in Table 3. The above analysis indicates that the overall reaction can be described by the equation A(T, t) = 5 A*(T)i(I
- exp[ -k,,exp(
-E,dRT)]
t)
(4)
i=l
As will be shown later, the actual inner particle temperature is not constant during the reaction due to heat transfer effects. Therefore eqn. 4 holds true only when the particle size is very small.
161
Fig. 8. Experimental (dashed) and theoretical (solid) curves of In k versus conversionat (1) 425OC, (2) 450°C, (3) 475OC, (4) 500°C and (5) 525OC (particlesize0.2-0.3 mm).
TABLE 2 Regression analysis results (k in s- ‘) Temperature
(“C) 425 450 475 500 525
In kl
In k,
In k,
-
- 4.10 - 3.50 -2.90 - 2.40 - 1.70
-6.58 -5.89 -5.26 -4.64 -4.02
2.20 1.75 1.20 0.60 0.10
17 16 18 24 27
23 28 30 37 42
60 56 52 39 31
Recently we reported the results of a fluidized bed kinetic study [8], in which the rate of organic pyroproduct formation was described with two simultaneous independent first-order reactions. The present report is based on new, improved data, which are more reliable and accurate due to
TABLE 3 Activation energies and frequency factors obtained from linear regression analysis of values of In k against l/T given in Table 2 Reaction No.
Activation energy, -J& (kcal/mol)
Frequency factor, k, (s-1.106)
1 2 3
23.6kl.3 26.0 k 1.3 28.1 k 1.5
2.6 +0.12 2.3 +O.ll 0.93 f 0.05
162
TIME
1s)
Fig. 9. Upscaling of the upper left comer of Fig. 5 (see text).
experimental improvements involving, mainly, minimizing the dead volumes in the system. Analysis of the present data indicates that a set of two reactions is not sufficient; three or more reactions are needed to describe the pyrolytic reaction. In order to compare our experiments with those of Wallman et al. [l] and Richardson et al. [2] we plotted the curves of In (1 - conversion) versus time (Fig. 5). Wallman et al. and Richardson et al. approximated such curves by two straight-line segments. The use of curves of In (1 - conversion) versus time might be misleading because (1) k, the reaction rate constant, is measured from the slope of the curve and if the curve is not a straight line it is difficult to determine, and (2) the pyrolytic reaction has an asymptotic behaviour, the curve over-emphasizes the end of the reaction. In fact, the last few percents of the conversion dominate the shape of the curve. Fig. 9 is focused on the upper left corner of Fig. 5, by plotting the data from 0 to 55% conversion only. Obviously this is a curved line; the slope, i.e. kobserved is continuously decreasing. This is in accordance with the direct measurements of k (Fig. 4). Preliminary experiments with an American oil shale (Green River) indicate that this conclusion also holds for this sample (despite the large differences of the mineral matrix and the type of organic matter). Experiments
on partially pyrolyzed
material
Samples of oil shale were pyrolyzed in the reactor for 1.5 h at 400°C (after 1.5 h the reaction was practically completed). The samples were taken out of the reactor, cooled and then pyrolyzed again at a higher temperature (Fig. 10).
163
-5.0
1 0
I 20
1
I %
I
I
I
I .30
I
I 100
4COON&OON
Fig. 10. Kinetics at 500° C of a sample which had been retorted at 400 o C. The values of the theoretical (solid) curve are: Af = 26%, A; = 67%, k, =l s-l, k2 = 0.076 s-l and k3 = 0.01 S-l.
Two stage reaction hypothesis Table 1 shows that the amount of the products increases with the rise in temperature. Table 2 shows that the contribution of the fast and the slow reactions to the overall reaction varies with temperature. Table 3 indicates that the measured activation energies are lower than expected for an ordinary chemical bond cleavage. Fig. 10 indicates that, when a sample which has already been completely retorted at 400°C is pyrolyzed again at a higher temperature, it not only produces more products but there is a contribution from the fast reaction to the overall kinetics, although one would expect to see only the slow reaction. The above results indicate that the reaction pathway is probably not a one-stage mechanism. It is conceivable that the low values of Ea, and EQ2 (Table 3) are not chemically meaningful in the strict sense they were derived by regression analysis (i.e. fitting a sum of exponential5 to an experimental curve). However, Ea, is derived from k, values which are experimentally obtained. Therefore the EO, low value could indicate real lowering of activation energy and thus needs better understanding. There is a possibility that the rate determining step is associated with the volatilization or diffusion of the products. In order to check this possibility, samples of products were taken at different time intervals during the reaction and were analyzed by gas chromatography [9]. It was found that there is a slight increase in the light end products as the reaction progresses, indicating that volatilization and diffusion are probably not the rate determining steps.
164
The same argument could be applied to the results of reactions carried out at higher temperatures (Fig. 8). Exaltation of the curves indicates a similar reaction profile, which in turn can be related to a similar reaction mechanism. The spacing between the various lines produced at different temperatures is almost constant and indicates an activation energy higher than 20 kcal/mol. A change in the rate deter~n~g step to a diffusion controlled reaction at higher temperatures would probably have a marked effect both on the shape of the curve and on the spacing between the curves, leading to unparallel spacing and convergence of the curves. Based on these observations we concluded that in the range of temperatures studied and reported in Fig. 8, diffusion is most likely not the rate determining step. This lowering in activation energy is usually explained by the use of Pitt’s model [lo] which was modified by Anthony et al. [11,12]. This model describes the pyrolytic process by an infinite number of independent first-order parallel reactions represented by a Gaussian distribution of activation energies (a single frequency factor common to all reactions is assumed). Anthony et al. [ll] showed that, if they assume one first-order reaction, the kinetic study yields an activation energy of about 10 kcal/mol, whereas treatment of the results by the modified Pitt model yields a Gaussian dist~bution of activation energies around a mean of 51-56 kcal/mol. This model was developed for coal programmed pyrolysis experiments and was adapted for oil shale programed experiments by Campbell et al. [13] and others. If we examine our results (Figs. 4 and 8) it is obvious that the model suggested by Pitt and Anthony et al. is unacceptable for isothermal experiments. Fig. 4 indicates, for example, that from 57% conversion to the completion of the reaction, the reaction is controlled by one k which leads to one discrete E,. Based on the above discussion we suggest the following two-stage mechanism: (1) The first stage, which is not the rate determining step, is the cleavage of the kerogen to form smaller activated fragments (free radicals) controlling the overall yield of the pyrolytic process. These activated fragments do not volatilize under the reaction conditions. (2) Secondary cleavage of the activated fragments of the first stage to the volatile products follows. Stage two can be described as a linear combination of three first-order reactions. At this stage, chemical bonds which are attached to a free radical site are cleaved, especially bonds /3 to free radical (P-cleavage). Such bond cleavages are associated with low activation energies (30-35 k&/mole) [14]. Rapid secondary reactions (rearrangements, secondary cracking, radical quenching etc.) in the gas phase probably follow the second stage. However, the flame ionization detector measures the total organic carbon converted from solid into organic gases, so reactions such as these could not be followed.
165
-5.05 0
20
40
60
80
100
% CONVERSION
Fig. 11. Kinetics of samples with different particle sizes at 500°C. ((-.-.-) 0.7-l mm, (- - -) 1.4-2 mm
) 0.2-0.3 mm,
The effect of particle size on the kinetics
Fig. 11 shows curves of In k versus conversion for experiments which were performed on samples of different particle size. The results indicate that even after the initial heating stage of the particle, there is a difference between k observed for small and for large particles. At low conversions the observed k for a reaction with small particles is greater (i.e. the reaction is faster) than for larger particles. As the reaction progresses, the observed k for small and large particles converge to the same value. This phenomenon becomes dominant as the temperature of the experiment increases, and might stem from heat transfer effects. The pyrolytic reaction is endothermic; there is probably a heat flux from the outer surface into the core of the particle during all the reaction stages. Therefore, there is a temperature gradient from the surface inwards. This gradient is proportional to the volume:surface ratio (i.e. the particle diameter) and to the reaction rate [15]. Since the reaction rate slows with time, the gradient decreases and the internal particle temperature increases until it reaches the effluent gas temperature, at which point the difference between the observed k of small and large particles disappears.
REFERENCES 1 P.H. Wallman, P.W. Tamm and B.G. Spars, in H.L. Stauffer (Editor), Oil Shale Tar Sands and Related Materials, ACS Symposium Series 163, American Chemical Society, Washington, DC, 1981, p. 93.
166 2 J.H. Richardson, E.B. Huss, L.L. Ott, J.E. Clarkson, M.O. Bishop, J.R. Taylor, L.J. Gregory and J.C. Morris, Fluidized-bed pyrolysis of oil shale: oil yield, composition and kinetics, UCID-19548, Lawrence Livermore National Laboratory, Livermore, CA, 1981. 3 K. Rajeshwar, R. Nottenburg and J. Dubow, J. Mater. Sci., 14 (1979) 2025. 4 A.B. Hubbard and W.E. Robinson, A thermal decomposition study of Colorado oil shale, Rep. Invest. U.S. Bur. Mines 4744, 1950. 5 V.D. Allred, Chem. Eng. Progr., 62 (1966) 55. 6 J.H. Campbell, G.H. Koskinas, T.T. Cobum and N.D. Stout, Oil shale retorting: Part 1. The effects of particle size and heating rate on oil evolution and intraparticle oil degradation, UCRL-52256 Lawrence Livermore National Laboratory, Livermore, CA, 1977. 7 R.A. Jones, An Introduction to Gas-Liquid Chromatography, Academic Press, New York, 1970. 8 H. Bar, M. Sc. Thesis, The Hebrew University of Jerusalem, 1984. 9 H. Bar, R. Ikan and Z. Aizenshtat, J. Anal. Appl. Pyrol, 10 (1986) 167. 10 G.J. Pitt, Fuel, 41 (1962) 267. 11 D.B. Anthony, J.B. Howard, H.C. Hottel and H.P. Meissner, Fifteenth Symposium (International) on Combustion, The Combustion Institute, Pittsburgh, PA, 1975, p. 1303. 12 D.B. Anthony and J.B. Howard, AIChE J., 22 (1976) 625. 13 J.H. Campbell, G. Gallegos and M. Gregg, Fuel, 59 (1980) 727. 14 J.H. RaIey, Fuel, 59 (1980) 419. 15 0. Levenspiel, Chemical Reaction Engineering, Wiley, New York, 2nd ed., 1972, p. 477.