Ind. Eng. Chem. Res. 2002, 41, 4201-4208
4201
Thermogravimetric Analysis and Devolatilization Kinetics of Wood Morten Gunnar Grønli,† Ga´ bor Va´ rhegyi,‡ and Colomba Di Blasi*,§ SINTEF Energy Research, Thermal Energy, N-7465 Trondheim, Norway, Research Laboratory of Materials and Environmental Chemistry, Chemical Research Center, Hungarian Academy of Sciences, P.O. Box 17, Budapest 1525, Hungary, and Dipartimento di Ingegneria Chimica, Universita` degli Studi di Napoli “Federico II”, P.le V. Tecchio, 80125 Napoli, Italy
Thermogravimetric curves have been measured at a heating rate of 5 K/min for several hardwoods (beech, alder, birch, and oak) and softwoods (Douglas fir, two pine species, redwood, and spruce), whose chemical composition varies within the usual standards. The analysis of the devolatilization characteristics is based on the introduction of several reaction temperatures. A comparison between hardwoods and softwoods shows that, in the latter case, the decomposition starts at lower temperatures, the hemicellulose shoulder is more delayed, and both the hemicellulose and cellulose zones are wider. Furthermore, the yields of char are higher. However, a devolatilization mechanism, consisting of three parallel reactions and the same set of activation energies for hemicellulose, cellulose, and lignin (100, 236, and 46 kJ/mol), can describe the hightemperature (>553 K) degradation behavior of all of the woods with a good accuracy. Modifications for the extension of the mechanism at lower temperatures are required only for species with significant extractive contents and consist of two further reactions (activation energies of 105 and 127 kJ/mol, respectively). Introduction The widespread availability of biomass (the third among primary energy resources, after coal and oil1), which is also renewable and potentially neutral in relation to global warming,2 motivated the extensive research undertaken in the past decade for the industrial development of thermochemical conversion plants (see, for instance, two recent reviews3,4). Mathematical modeling can be profitably applied for process design and optimization, but the validity of predictions is highly dependent upon an adequate description of chemical and physical processes, extensive model validation, and the correctness of input data. The knowledge of the solid devolatilization kinetics may help the better understanding and planning of important industrial processes because pyrolysis is not only an independent conversion technology but also part of the gasification and combustion processes. Numerous investigations have been carried out in order to determine the degradation kinetics of cellulose. (See, for instance, the reviews of Antal5 and Antal and Va´rhegyi.6) However, even with reference to small ashfree samples and the slow heating rates of thermogravimetric analysis (TGA), the specific properties of cellulose7 and the different measurement systems,8 among other factors, have been shown to exert a significant influence on the kinetic parameters. The situation is worse for wood because of the lower number of studies, the presence of several components, and the catalytic role played by inorganic matter in the reaction paths. The results currently available for fast and isothermal pyrolysis of wood have been examined by Di Blasi9 and reviewed by Di Blasi and Branca10 recently, so only the * Corresponding author. Tel: 39-081-7682232. Fax: 39-0812391800. E-mail:
[email protected]. † SINTEF Energy Research. ‡ Hungarian Academy of Sciences. § Universita` degli Studi di Napoli “Federico II”.
main findings are summarized here. In the majority of studies, the process is modeled by means of a one-step global reaction for degradation/devolatilization with activation energies of 60-170 kJ/mol. This approach is very useful when the kinetic constants for the formation rates of primary product classes (liquids, gas, and char) should also be estimated. Indeed, the collection of products and determination of yields, to be coupled with weight loss characteristics for kinetic modeling, are usually carried out on a global (integral) basis. The results on the chemical kinetics of wood pyrolysis for slow heating rates (TGA) are summarized in former and recent reviews.11-13 However, only a few data have been reported recently. Usually, three main zones (or pseudocomponents) have been introduced, associated with the devolatilization of the main components.6,14-20 The decomposition processes were described by global reactions with typical activation energies of 105-111 kJ/mol (hemicelluloses), 195-213 kJ/mol (cellulose), and 35-65 kJ/mol (lignin).16 These multistep mechanisms, when coupled with the description of transport phenomena, do not allow the product distribution to be determined on dependence of the reaction conditions, because they are based on a constant ratio between the yields of volatiles and char. On the other hand, they provide a more accurate prediction of the conversion time than the one-step isothermal mechanisms. The conversion time is the sole variable of interest in several cases, such as, for instance, in fixed-bed thermochemical conversion of wood. In fact, given the thick particles and the slow external heat-transfer rates, the devolatilization conditions are comparable with those of thermal analysis and the corresponding product yields remain almost constant.21,22 However, the general validity of the present multistep mechanisms and/or their kinetic parameters cannot be evaluated yet because only a few wood species were examined, and there were significant differences in the experimental conditions and in the treatment of the data. It is also worth
10.1021/ie0201157 CCC: $22.00 © 2002 American Chemical Society Published on Web 07/27/2002
4202
Ind. Eng. Chem. Res., Vol. 41, No. 17, 2002
Table 1. Chemical Analysis of the Wood Samples on a Dry Basis and Proximate Analysis of the Wood and Lignin Samples A. Chemical Analysis of the Wood Samples on a Dry Basis species (botanical name)
geographic area
holocellulose wt %
lignin wt %
extractives wt %
ref
alder (Alnus incana) beech (Fagus sylvatica) birch (Betula pubescens) oak (Quercus spec.) Douglas fir (Pseudotsuga menziensii) pine A (Pinus sylvestris) pine B (Pinus pinea) redwood (Sequoia sempervirens) spruce (Picea abies)
NO IT NO USA USA NO IT USA NO
70.5 78 76 68.5 65 65 69 56 69
25 20 21 28 29 30 24 33 29
4.5 2 3 3.5a 6 5 7 11 2
15 24 15 15 24 15 24 24 15
B. Proximate Analysis of the Wood and Lignin Samples
a
species
volatile matter (wt %)
fixed carbon (wt %)
ash (wt %)
alder beech birch oak Douglas fir pine A pine B redwood spruce lignin (nonextracted beech) lignin (extracted Douglas fir) lignin (extracted pine B) lignin (extracted redwood) lignin (nonextracted redwood)
86 86.5 87.4 84.4 84.2 85 86.6 82.3 84.4 51.5 54.6 54 52.3 49.4
13.7 13.1 12.4 15.5 15.4 14.7 13.1 17.5 14.9 47.1 45.6 45.2 45.9 47.9
0.3 0.4 0.2 0.1 0.3 0.3 0.3 0.2 0.7 1.3 0.2 0.8 1.7 2.7
Measured in the present work.
noting that the yields and composition of the products and the conversion times vary by wood species in pyrolysis tests executed under conditions of heat- and mass-transfer control, as a consequence of differences in both physical and chemical properties.24,25 In the present work TGA is employed for a systematic investigation of the devolatilization behavior of several wood species under conditions when the transport processes do not hinder the study of the chemistry effects. The main objectives are (a) to quantify the differences between hardwoods and softwoods, following the different amounts and chemical nature of the components and (b) to ascertain whether a single mechanism, consisting of a few parallel devolatilization reactions, and one set of kinetic data can be used with sufficient accuracy in all cases and to establish the limits of such an approach. Experimental Section Materials. The tests were carried out for four hardwoods (alder, beech, birch, and oak) and five softwoods [Douglas fir, redwood, spruce, and two species of pine wood indicated as A (Pinus sylvestris) and B (Pinus pinea), respectively] obtained from knot- and bark-free logs. Three lignins (Douglas fir, pine B, and redwood) separated from extracted samples according to the Klason method and two lignins (beech and redwood) which retain some extractive components (the Klason method applied to nonextracted samples) were also examined. The chief information concerning chemical composition and proximate analysis of the samples and the geographical area where the plants were grown is reported in Table 1. The amount of extractives and the Klason lignin content of the samples were determined in earlier work.15,24,25 The holocellulose (total hemicellulose and cellulose) content was simply evaluated as a difference.
The chemical composition of the hardwoods is roughly the same, apart from oak, which presents much higher lignin contents. On the other hand, for the softwoods, pine B comprises significantly lower lignin contents. Extractives for all wood samples of the study are in the range of the literature values.26,27 Despite the differences in chemical composition of woods belonging to the hardwood or softwood category, the data reported in Table 1A are in agreement with the literature. Indeed, it is reported26,27 that the former category contains less (16-24%) lignin than the latter (24-33%). Variable amounts of acid-soluble lignin affect the method of analysis so that the total lignin content of hardwoods can be 19-28%. Hence, the wood species examined here were chosen to span the entire range of variation of the usual (standard) limits of hardwoods and softwoods. Moreover, although this study only makes reference to holocellulose, it is worth noting that, while the cellulose content of both softwoods and hardwoods is in the range of 42 ( 2%, the hemicellulose and lignin are found in complementary proportions.27 Finally, the fixed-C content is directly related to the lignin percentage in the chemical composition.28 As expected, the ash content is small for all of the wood samples. Lignins are characterized by high fixed-C contents, with negligible differences between (nonextracted) hardwoods and softwoods. The two different separation procedures only give rise to lower ash and fixed-C contents (redwood). Apparatus and Procedure. A TA Instruments SDT 2960 simultaneous TG-DTA apparatus was employed for the thermogravimetric tests.8,21 This apparatus detects the mass loss with a resolution of 0.1 µg. The temperature is measured in the sample holder. Highpurity nitrogen was used for the tests at a flow rate of 150 mL/min. The nitrogen was purged for 20 min, before starting the heating program, to establish an inert
Ind. Eng. Chem. Res., Vol. 41, No. 17, 2002 4203
environment. The sample mass was 5 mg. The experiments started with a drying session (a heating rate of 30 K/min up to 383 K with a holding time of 30 min). The subsequent thermal decomposition was carried out at a slow heating rate (5 K/min to a final temperature of 773 K) to keep possible heat/mass-transfer intrusions at a minimum. Kinetic Modeling. An approach employed in several earlier studies was chosen to model wood devolatilization.6,14-21 The total volatiles released during the process consist of M fractions, whose dynamics are described by first-order kinetics:
dRj/dt ) Aj exp(-Ej/RT)(1 - Rj), j ) 1, M; Rj(0) ) 0 (1) Then, the overall mass loss rate is a linear combination of the dRj/dt rates: Figure 1. Mass fraction and time derivative of the mass fraction as functions of temperature for several hardwoods.
M
-dYcalc/dt )
cj dRj/dt ∑ j)1
(2)
where Ycalc is the simulated sample mass normalized to unity [Ycalc varies from 1 to Ycalc(t∞)] and parameter cj corresponds to the amount of volatiles produced by the jth component of a unit mass of sample between t ) 0 and ∞. The parameters cj, Aj, and Ej are determined by a least-squares evaluation of the curves. The theoretical char yield, Ycalc(t∞), can be calculated from the cj values: Ycalc(t∞) ) 1 - Σcj because Ycalc(t) ) 1 - ΣcjRj(t). The simultaneous evaluation of the DTG curves was carried out by means of a software previously developed.29,30 When the observed data of the kth experiment and their simulated counterparts are denoted by [dY/ dt]kobs(t) and [dY/dt]kcalc(t), respectively, the following sum is minimized: Nexp Nk
S)
{[dY/dt]kobs(ti) - [dY/dt]kcalc(ti)}2/Nk/hk2 ∑ ∑ k)1 i)1
(3)
where Nexp is the number of experimental curves evaluated simultaneously, Nk is the number of points on the kth evaluated curve (Nk varied between 500 and 1000 in the calculations), and hk denotes the height of the kth evaluated curve. The normalization by hk proved to be useful to evaluate simultaneously experiments having strongly differing magnitudes.31,32 The algorithm searched for those parameters that minimized the leastsquares sum. The convergence to meaningless solutions was avoided by determining suitable values or domains for certain parameters via a special evaluation strategy, as discussed in the following. Also, the obtained fit was characterized by the following variable: Nk
fit (%) ) 100{
{[dY/dt]ikobs(ti) ∑ i)1 [dY/dt]ikcalc(ti)}2/Nk}1/2/hk (4)
Equation 1 was solved numerically [separation of the variables followed by numerical integration along the experimental T(t) function] at each parameter set arising during the nonlinear optimization. The quantities Tpeakcalc are used to characterize the position of the peaks predicted by the model. The differences between the Tpeakcalc values, calculated at exactly 5 K/min heating
Figure 2. Mass fraction and time derivative of the mass fraction as functions of temperature for several softwoods.
rate, and those obtained by integration along the experimental T(t) program were on the order of 1 K. Results and Discussion Several parameters (characteristic reaction temperatures, devolatilization rates, and mass fractions), introduced to describe the thermogravimetric curves, are evaluated for the nine wood species listed above. Then results are presented concerning the use of the measured weight loss curves and a set of parallel firstorder reactions for the estimation of kinetic constants. Finally, a comparison is provided between measurements and predictions. Degradation Characteristics of Wood. The mass fraction, Y, and the time derivative of the mass fraction, -dY/dt (indicated as TG and DTG curves in the following), are reported as functions of temperature in Figures 1 and 2 for the hardwoods and softwoods, respectively. In agreement with previous findings,6 the DTG curves show two main regions. Because the temperature intervals of hemicellulose and cellulose decomposition partially overlap each other, the hemicellulose decomposition (first region) usually appears as a more or less pronounced “shoulder” instead of a well-defined peak. The second region is associated with the attainment of the maximum, mainly because of cellulose decomposi-
4204
Ind. Eng. Chem. Res., Vol. 41, No. 17, 2002
temperature, Tinitial, is assumed to correspond to a solid mass fraction equal to 0.975 (not shown in Figure 3, to avoid overcrowding). The beginning of hemicellulose decomposition is associated with Tonset(hc) defined by extrapolating the slope of the devolatilization rate in correspondence with the first local maximum in -d2Y/ dt2 (up to the zero level of the Y axis). Given the appearance of a shoulder, the decomposition temperature of the hemicellulose is characterized by Tshoulder, defined by the point where -d2Y/dt2 attains the value nearest to zero in this region. For the cases when the hemicellulose and cellulose decomposition is less overlapped, the parameter Tshoulder marks the peak top of the hemicellulose decomposition. The corresponding devolatization rate, -(dY/dt)shoulder, and mass fraction, Yshoulder, can be easily evaluated. The temperature Tpeak, where the maximum devolatilization rate is attained (associated mainly with cellulose decomposition), is also introduced with the corresponding -(dY/dt)peak and Ypeak. The beginning of the final, tailing region dominated by the lignin decomposition, is identified by Toffset(c), which is obtained by extrapolating the devolatilization rate corresponding to the local minimum in -d2Y/dt2 in this region (again up to the zero level of the Y axis). The last parameter is the char yield, Y773, that is, the percent of the solid mass fraction detected for T ) 773 K. A summary of the devolatilization characteristics for the hardwoods and the softwoods is given in Table 2 (average values are also included for each category). The initial degradation temperature is affected by the amount of extractives, which are the less stable components of wood. Apart from the lower value of pine B, the parameter Tinitial is quantitatively similar for all of the samples and roughly comprised between 508 and 522 K. Hardwoods exhibit a more clear-cut separation than softwoods between the first and second reaction zones. The first reaction zone begins and evolves at lower temperatures for the former category, while the maximum devolatilization rate (the second zone) is
Figure 3. Mass fraction and first and second time derivatives of the mass fraction as functions of temperature for alder wood and definitions of the characteristic reaction temperatures.
tion, followed by a rapid decay and a long tail. The wide range of temperatures, where lignin decomposes, hinders the appearance of a peak attributable to this component.6 Also, volatile evolution at very low temperatures is usually associated with extractive decomposition. A close similarity is shown by all the hardwoods, except oak, whose peak is displaced toward lower temperatures. On the other hand, the same feature is also shown by the peak of the Douglas fir with respect to the other softwoods. The degradation characteristics of hardwoods and softwoods can be quantified through several parameters (introduced below and also listed in the Nomenclature section), which are related to the temperature ranges of the different zones of the weight loss curves (with the corresponding mass fractions and devolatilization rates) and the char yield. The solid mass fraction and the first and second time derivatives of the mass fraction are used for such definitions as shown in Figure 3 using alder wood as an example. The initial degradation
Table 2. Degradation Characteristics of the Wood Samples: Temperatures, Mass Fractions, and Devolatilization Rates A. Temperatures species
Tinitial (K)
Tonset(hc) (K)
Tshoulder (K)
Tpeak (K)
Toffset(c) (K)
Tshoulder Tonset(hc)
Toffset(c) Tpeak
alder beech birch oak Douglas fir pine A pine B redwood spruce average for hardwoods average for softwoods
515 521 517 510 516 511 482 508 522 516 508
509 512 513 506 532 533 529 528 526 510 530
561 568 568 550 579 595 592 588 601 562 591
622 622 626 611 607 624 623 624 625 620 621
644 645 645 633 639 650 651 650 649 642 648
52 56 55 44 47 62 63 60 75 52 61
22 23 19 22 32 26 28 26 24 22 27
B. Mass Fractions and Devolatilization Rates species
Yshoulder (%)
Ypeak (%)
Y773 (%)
-(dY/dt)shoulder × 103 s-1
-(dY/dt)peak × 103 s-1
(dY/dt)shoulder/ (dY/dt)peak
alder beech birch oak Douglas fir pine A pine B redwood spruce average for hardwoods average for softwoods
0.83 0.80 0.76 0.84 0.78 0.70 0.68 0.76 0.67 0.81 0.72
0.40 0.37 0.32 0.45 0.55 0.45 0.43 0.50 0.46 0.38 0.47
17.8 18.6 14.1 23.0 24.0 20.2 20.2 26.5 23.4 18.4 22.9
0.39 0.45 0.47 0.41 0.53 0.59 0.57 0.44 0.59 0.43 0.54
1.02 0.91 0.98 0.89 0.87 0.91 0.81 0.83 0.77 0.95 0.84
0.38 0.49 0.48 0.46 0.61 0.65 0.70 0.53 0.77 0.45 0.64
Ind. Eng. Chem. Res., Vol. 41, No. 17, 2002 4205
attained at about the same temperature for both cases. Indeed, Tonset(hc), Tshoulder, and Tpeak are in the ranges 506-513, 550-568, and 611-626 K for the hardwoods, while the corresponding softwood values are 523-533, 579-601, and 607-631 K. Furthermore, the lower temperatures of the first reaction zone for the hardwoods are associated with lower devolatilization rates [-(dY/dt)shoulder of (0.39-0.47) × 10-3 s-1 versus (0.440.59) × 10-3 s-1] and higher mass fractions (Yshoulder of 0.76-0.84 versus 0.60-0.78). For the hardwoods, the values of Tinitial are higher than those of Tonset(hc), which is probably an indication of a certain overlap between the degradation of extractive components and hemicellulose. The contrary occurs for the softwoods, where the large differences between Tinitial and Tonset(hc) may be a consequence, on the one hand, of a higher volatility of extractives (pine B) and, on the other hand, of a lower reactivity of hemicellulose. Differences between these components may be due to chemical composition. Indeed, hemicelluloses27 are mainly glucuronoxylan in hardwoods and galactoglucomannans in softwoods. Maximum devolatilization rates are slightly higher for hardwoods [(0.8-1) × 10-3 s-1 versus (0.70.9) × 10-3 s-1] and occur for lower solid mass fractions, characteristics also appearing as lower yields of char (14-23% versus 20-26.5%). Finally, the decomposition of hardwood cellulose is slightly faster than the corresponding softwood counterpart (temperatures Toffset(c) of about 6-10 K lower), although in the final part of the DTG curves lignins may also play an important role. The analysis of the degradation characteristics of hardwoods and softwoods confirms the main findings already reported for thick samples and packed beds.24,25 On the whole, the degradation of hardwoods takes place within a narrower range of temperatures than that of the softwoods. Indeed, the first (hemicellulose) and second (cellulose) reaction zones are sharper (see the differences between the characteristic reaction temperatures; Table 2A) with a quantitatively less important hemicellulose shoulder (see the ratio between the characteristic devolatilization rates; Table 2B). Moreover, the ratio between the volatile and the char yields is essentially determined by the fixed-C content of the sample. Thus, in accordance with proximate analysis, the highest char yields are observed for redwood (26.5%), Douglas fir (24%), and oak and spruce (about 23%). However, one of the results of this study is that, for wood species with chemical compositions comprised within the range of standard values for the hardwood and softwood categories,26,27 the differences in the corresponding degradation characteristics are not exceedingly large. So, it is worth searching for a common devolatilization mechanism. Evaluation Strategy and Kinetic Constants. Detailed reaction mechanisms, consisting of several steps for each or some of the main components and kinetic parameters specific to each wood, may be required for highly accurate predictions. However, for engineering applications, it is sufficient to take into account only the basic characteristics of the degradation process with a simplified mechanism based on the same set of kinetic parameters. Hence, both the minimum number of volatile fractions, M, and the related one-step reaction parameters, which prove to give an adequate description of all of the nine wood species considered here, should be determined. In all cases, one-step devolatilization reactions for hemicellulose, cellulose, and lignin were
Figure 4. Predicted (thin lines of various styles) and measured (circles, squares, and triangles) time derivatives of the mass fraction as functions of temperature for several lignin samples.
considered (three-step mechanism), integrated by additional reactions to take into account the low-temperature (extractive) phenomena. The determination of the kinetic mechanism (M) and kinetic parameters was accomplished according to the following main steps: (1) estimation of lignin parameters by simultaneous evaluation of the DTG curves of the lignin samples; (2) estimation of the parameters for a three-step mechanism (hemicellulose, cellulose, and lignin) through simultaneous evaluation of the nine wood curves; (3) further parameter evaluation for two fractions of low-temperature components; (4) optimization of a five-step reaction mechanism for the nine wood species. Figure 4 compares the predicted and measured DTG curves of lignin samples. Measurements do not show significant differences for temperatures below 570 K, apart from the slightly higher rates of the nonextracted samples, probably because of a certain contribution from extractives. Extraction results in a higher peak rate (redwood) and, in accordance with the fixed-C content, in lower yields of char (66% versus 68.5%, not shown). Also, for the nonextracted woods, the different peak temperatures (about 661 K for beech lignin and 677 K for redwood lignin) could be partly responsible for the attainment of lower Toffset(c) for the hardwoods. In agreement with previous literature,6 common to all cases are the slow devolatilization rates over a very wide range of temperatures and the very high char yields (63-68%). TGA of several lignins was carried out with the aim of providing a simple kinetic description for the evaluation of all of the wood samples, although a one-step devolatilization reaction with first-order kinetics clearly cannot take into account the relative maximum around 500 K. The simultaneous evaluation of the DTG curves was made by requiring the same value of the activation energy. The set of parameters El ) 46 kJ/mol and 0.5 e log Al/s-1 e 0.6 provides an acceptable approximation for the high-temperature features, as shown in Figure 4. These values correspond to 670 K e Tpeakcalc e 685 K, a range in good agreement with the observed values. The El value and the log Al range obtained in this way were employed in all of the subsequent calculations. In the second step, the simultaneous evaluation of the nine wood samples was carried out by means of the three-step mechanism. The wood samples containing a
4206
Ind. Eng. Chem. Res., Vol. 41, No. 17, 2002
Figure 5. Comparison between the observed (O) and simulated DTG curves (s) for pine B by means of the three-step model. Thin lines with various line styles denote the predicted volatile evolution from the different components.
significant amount of extractives (pine B and redwood) were evaluated from a temperature above the extractive peaks, that is, from 553 to 723 K. The other samples were evaluated from 423 to 723 K. This procedure resulted in a good fit between measurements and predictions (overall deviations between 0.6 and 2.2%) with the following set of parameters: Ehc ) 100 kJ/mol (6.33 e log Ahc/s-1 e 6.88, 0.31 e chc e 0.38) and Ec ) 236 kJ/mol (17.36 e log Ac/s-1 e 17.97, 0.24 e cc e 0.43) with also 0.087 e cl e 0.15. The activation energies and the ranges of the preexponential factors give the following intervals for the peak temperatures: 557 K e Tpeak,hccalc e 588 K and 610 K e Tpeak,ccalc e 628 K, values in good agreement with Tshoulder and Tpeak of the experimental curves (Table 2A). Two wood samples, pine B and redwood, exhibit partial peaks below 553 K, which are not described by the three-step mechanism as shown, for example, in Figure 5 (pine B). More specifically, one peak is observed, which can be described by the degradation of two fractions of extractives indicated as e1 and e2. The evaluation of the two curves over the entire temperature range resulted in the following set of parameters: Ee1 ) 105 kJ/mol, Ee2 ) 127 kJ/mol, log Ae1/s-1 ≈ 9.1, and
log Ae2/s-1 ≈ 10.4. These values correspond to Tpeak,e1calc ) 478 K and Tpeak,e2calc ) 519 K, respectively. The final evaluation assumed M ) 5, that is, up to five components could contribute to the DTG curve of a given wood sample. Each experiment was evaluated in the temperature range 423-723 K. The activation energies obtained from the previous steps were used as fixed values, and only the preexponential factors and the coefficients cj were determined by the method of least squares. Certain restrictions were employed to avoid convergence to meaningless solutions. Several samples did not contain components decomposing in the low-temperature region. In these cases ce1 and ce2 should obviously be zero. Without constraints, however, the simulated low-temperature peaks could “migrate” into the domains of hemicellulose and cellulose decomposition, contributing formally to the improvement of the fit there. To avoid this problem, the peak temperatures of components e1 and e2 were restricted into temperature domains around their mean values determined in the previous section. The following constraints were employed: 463 K e Tpeak,e1 e 493 K and 504 K e Tpeak,e2 e 534 K. At the given values of Ee1 and Ee2, these constraints are equivalent to 8.75 e log Ae1/s-1 e 9.53 and 10.05 e log Ae2/s-1 e 10.85. The resulting parameters and the corresponding Tpeakcalc values are shown in Tables 3 and 4. Details about the dynamics of the different fractions and a comparison between predicted and measured DTG curves are shown in Figures 6 and 7, for a hardwood (beech) and a softwood (Douglas fir) species, respectively. The agreement between predictions and measurements is good. The three-step mechanism suffices for the description of the hardwoods, except oak, whereas the presence of extractives in softwoods usually requires one or two additional reactions. In this case, the need for the introduction of further reaction steps (with respect to the widely used three-step mechanism) is evidenced by the lower reactivity of hemicellulose whose degradation is well separated from that of the lowtemperature components. On the other hand, as was already noted in the analysis of the characteristic reaction temperatures, the overlapping between the degradation dynamics of extractives and hemicellulose in the hardwoods makes the distinction between the two
Table 3. Parameters for the Five-Step Devolatilization Mechanism (Simultaneous Evaluation of Nine Wood Species over the Temperature Range 423-723 K)a fit/% log(Ae1/s-1) log(Ae2/s-1) log(Ahc/s-1) log(Ac/s-1) log(Al/s-1) ce1 ce2 chc cc cl a
alder
beech
birch
oak
Douglas fir
pine A
pine B
redwood
spruce
mean
std. dev.
1.5 na na 6.72 17.58 0.60 0 0 0.31 0.43 0.09
1.9 na na 6.63 17.58 0.60 0 0 0.34 0.39 0.10
2.2 na na 6.68 17.52 0.60 0 0 0.38 0.41 0.09
1.7 na 10.05 6.84 17.97 0.60 0 0.03 0.28 0.34 0.14
0.6 na 10.05 6.31 17.81 0.60 0 0.01 0.39 0.22 0.14
1.2 9.15 na 6.36 17.40 0.53 0.01 0 0.34 0.35 0.11
0.4 9.24 10.53 6.33 17.36 0.60 0.03 0.01 0.38 0.28 0.11
0.4 8.91 10.25 6.36 17.42 0.60 0.01 0.03 0.27 0.3 0.13
1 na na 6.40 17.43 0.58 0 0 0.33 0.32 0.14
1.2 9.10 10.22 6.51 17.56 0.59 0.01 0.01 0.34 0.34 0.12
0.7 0.17 0.23 0.20 0.20 0.02 0.01 0.01 0.04 0.07 0.02
Ee1 (kJ/mol) ) 105, Ee2 (kJ/mol) ) 127, Ehc (kJ/mol) ) 100, Ec (kJ/mol) ) 236, and El (kJ/mol) ) 46.
Table 4. Peak Temperatures Simulated for the Five-Step Devolatilization Mechanism (Kinetic Parameters as in Table 3) Tpeak,e1/K Tpeak,e2/K Tpeak,hc/K Tpeak,c/K Tpeak,l/K
alder
beech
birch
oak
Douglas fir
pine A
pine B
redwood
spruce
mean
std. dev.
na na 566 622 670
na na 571 622 670
na na 568 624 670
na 534 559 610 670
na 534 590 615 670
477 na 587 628 680
474 516 588 628 670
486 526 587 627 670
na na 585 626 673
479 528 578 622 671
7 9 12 6 3
Ind. Eng. Chem. Res., Vol. 41, No. 17, 2002 4207
which are very close to the corresponding values (Ehc ) 100 kJ/mol and Ec ) 236 kJ/mol) determined for all of the nine woods (the activation energy for the lignin component was not changed). Hence, it can be concluded that an improved description of the degradation characteristics of hardwoods, specifically for processes occurring in the first reaction zone, can be obtained only after a deeper understanding of the separate decomposition of extractives and hemicellulose and the consequent introduction of additional steps in the reaction mechanism. Conclusions
Figure 6. Comparison between the observed (O) and simulated DTG curves (s) for beech. Thin lines with various line styles denote the predicted volatile evolution from the different components. (See Table 3 for the corresponding parameters.)
Figure 7. Comparison between the observed (O) and simulated DTG curves (s) for Douglas fir. Thin lines with various line styles denote the predicted volatile evolution from the different components. (See Table 3 for the corresponding parameters.)
components very difficult and the introduction of any further reaction step somewhat arbitrary. Because of the lower number of adjustable parameters, the overall deviations are higher for hardwoods (1.5-2.2% versus 0.4-1.2% of softwoods). Apart from the same value of the activation energies, the standard deviations on the remaining parameters are also small. It is, however, worth noting that the cellulose coefficient is higher for the hardwoods (about 0.34-0.43 versus 0.22-0.35), because of the higher char yields and extractive contributions in softwoods. The average difference of the observed and calculated final residues (T ) 773 K) is also small (about 1%). Finally, the evolution of the volatile fractions of the main components and the corresponding activation energies is in good agreement with that of previous studies.6,16 To improve the fit between measurements and predictions, the four hardwoods and the five softwoods were evaluated separately. The results are not significantly different from those of the simultaneous evaluation of all of the woods (Table 3), in terms of both overall deviations and kinetic parameters. In particular, Ehc ) 100 kJ/mol, Ec ) 227 kJ/mol (hardwoods) and Ehc ) 98 kJ/mol, Ec ) 256 kJ/mol (softwoods) were obtained,
The devolatilization behavior of several hardwoods and softwoods (alder, beech, birch, oak, Douglas fir, pine A, pine B, redwood, and spruce), grown in Europe and USA, was investigated by thermogravimetry. These species present chemical compositions which vary over the widest range usually accepted for the hardwood and softwood categories. The DTG curves appear qualitatively similar for both cases, apart from a higher overlap between the hemicellulose and cellulose zones for the softwoods. From the quantitative point of view, based on the definition of characteristic reaction temperatures, softwoods show a lower reactivity of hemicellulose components, probably because of peculiarities in their chemical structure/composition (Tshoulder higher than about 20-30 K with respect to the hardwoods). Also, the zone of cellulose decomposition is wider. The fixed-C content of the samples is an effective indicator of the ability to produce char from a given wood (char yields are 14-23% for the hardwoods and 20-26.5% for the softwoods). The devolatilization dynamics of all of the wood species of the study can be described well by a simple mechanism. This consists of five parallel, first-order reactions for the amounts of the volatile fractions associated with two extractive components, hemicellulose, cellulose, and lignin. The same set of activation energies (105, 127, 100, 236, and 46 kJ/mol, respectively) applies for all of the woods. The differences in the characteristic reaction temperatures and the yields of char between hardwoods and softwoods are taken into account by preexponential factors and total volatile fractions. Standard deviations are about 0.2 for the logarithms of the preexponential factors and comprised between 0.01 and 0.07 for the five volatile fractions. When extractive contents are low, the mechanism reduces to the well-known three-step reactions (hemicellulose, cellulose, and lignin) with activation energies and dynamics of the related volatile fractions in good agreement with the previous literature. The common kinetic model for the hardwood and softwood devolatilization is hoped to facilitate the future development of comprehensive models where chemical kinetics are coupled with transport phenomena for the simulation of practical conversion systems. Nomenclature Symbols R ) volatile fraction A ) preexponential factor cj ) fraction of volatiles produced by the jth component E ) activation energy h ) absolute value of the maximum of the observed variable
4208
Ind. Eng. Chem. Res., Vol. 41, No. 17, 2002
M ) number of components Nexp ) number of experimental curves Nk ) number of points for the generic thermogravimetric curve m ) sample mass T ) temperature Tinitial ) temperature corresponding to Y ) 0.975 Tpeak ) temperature of the maximum devolatilization rate Tonset(hc) ) extrapolated temperature for the beginning of hemicellullose decomposition Tshoulder ) temperature corresponding to the hemicellulose shoulder Toffset(c) ) extrapolated temperature for the termination of cellulose decomposition (and the beginning of lignin tail) t ) time Y ) solid mass fraction Y773 ) char yield as a percent of the initial solid mass Subscripts c ) cellulose e1 ) first fraction of extractives e2 ) second fraction of extractives hc ) hemicellulose l ) lignin peak ) peak of the DTG (devolatilization rate) curve shoulder ) hemicellulose shoulder offset(c) ) cellulose offset onset(hc) ) hemicellulose onset Superscripts calc ) calculated obs ) observed
Acknowledgment The research was supported by the Norwegian Ferroalloy Producers Association (FFF), Organic Power ASA, and the Norwegian Research Council through the NYTEK and KLIMATEK programs (Norway), the Hungarian National Research Fund through Contracts OTKA T25341, T25347, and T37705, and the Ministry of Environment Protection through Grant 27753-2/2001 (Hungary) and MURST (Italy). Literature Cited (1) Werther, J.; Saenger, M.; Hartge, E. U.; Ogada, T.; Siagi, Z. Combustion of agricultural residues. Prog. Energy Combust. Sci. 2000, 26, 1. (2) Abbas, T.; Costem, P. G.; Lockwood, F. C. Solid fuel utilization: from coal to biomass. Twenty-sixth Symposium (Int.) on Combustion; The Combustion Institute: Pittsburgh, PA, 1996; pp 3041-3058. (3) Sami, M.; Annamalai, K.; Wooldride, M. Co-firing coal and biomass fuel blends. Prog. Energy Combust. Sci. 2001, 27, 171. (4) Maniatis, K. Progress in biomass gasification: An overview. In Progress in Thermochemical Biomass Conversion; Bridgwater, A. V., Ed.; Blackwell Science Ltd.: Oxford, U.K., 2001; Vol. 1, pp 1-31. (5) Antal, M. J. Biomass Pyrolysis: a Review of the Literature. Part IsCarbohydrate pyrolysis. In Advances in Solar Energy; Boer, K. W., Duffie, J. A., Eds.; American Solar Energy, Inc.: Boulder, CO, 1982; pp 61-111. (6) Antal, M. J.; Va´rhegyi, G. Cellulose pyrolysis kinetics: the current state of knowledge. Ind. Eng. Chem. Res. 1995, 34, 703. (7) Antal, M. J.; Va´rhegyi, G.; Jakab, E. Cellulose pyrolysis: Revisited. Ind. Eng. Chem. Res. 1998, 37, 1267. (8) Grønli, M.; Antal, M. J.; Va´rhegyi, G. A round-Robin study of cellulose pyrolysis kinetics by thermogravimetry. Ind. Eng. Chem. Res. 1999, 38, 2238. (9) Di Blasi, C. Comparison of semi-global mechanisms for primary pyrolysis of lignocellulosic fuels. J. Anal. Appl. Pyrolysis 1998, 47, 43.
(10) Di Blasi, C.; Branca, C. Kinetics of primary product formation from wood pyrolysis. Ind. Eng. Chem. Res. 2001, 40, 5547. (11) Roberts, A. A review of kinetics data for the pyrolysis of wood and related substances. Combust. Flame 1970, 14, 261. (12) Antal, M. J. Biomass pyrolysis: a review of the literature, Part 2sLignocellulose pyrolysis. In Advances in Solar Energy, an annual review of research and development; Boer, K. W., Duffie, J. A., Eds.; American Solar Energy Society, Inc.: Boulder, CO, 1985; Vol. 2, pp 175-255. (13) Di Blasi, C. Modelling and simulation of combustion processes of charring and non charring materials. Prog. Energy Combust. Sci. 1993, 19, 71. (14) Va´rhegyi, G.; Szabo´, P.; Antal, M. J., Jr. Reaction kinetics of the thermal decomposition of cellulose and hemicellulose in biomass materials. In Advances in Thermochemical Biomass Conversion; Bridgwater, T., Ed.; Chapman and Hall: London, 1994; Vol. 2, pp 760-771. (15) Grønli, M. G. A theoretical and experimental study of the thermal degradation of biomass. Ph.D. Thesis, NTNU, Trondheim, Norway, 1996. (16) Va´rhegyi, G.; Antal, M. J.; Jakab, E.; Szabo´, P. Kinetic modelling of biomass pyrolysis. J. Anal. Appl. Pyrolysis 1997, 42, 73. (17) Teng, H. S.; Lin, H. C.; Ho, J. A. Thermogravimetric analysis on global mass loss kinetics of rice hull pyrolysis. Ind. Eng. Chem. Res. 1997, 36, 3974-3977. (18) Teng, H.; Wei, Y. C. Thermogravimetric studies on the kinetics of rice hull pyrolysis and the influence of water treatment. Ind. Eng. Chem. Res. 1998, 37, 3806-3811. (19) O Ä rfa˜o, J. J. M.; Antunes, F. J. A.; Figueiredo, J. L. Pyrolysis kinetics of lignocellulosic materialss3 independent reactions model. Fuel 1999, 78, 349-358. (20) Helsen, L.; Van den Bulck, E. Kinetics of the low-temperature pyrolysis of chromated copper arsenate-treated wood. J. Anal. Appl. Pyrolysis 2000, 53, 51-79. (21) Sørum, L.; Grønli, M. G.; Hustad, J. E. Pyrolysis characteristics and kinetics of municipal solid wastes. Fuel 2001, 80, 1217. (22) Di Blasi, C.; Signorelli, G.; Portoricco, G. Fixed-bed countercurrent gasification of biomass at laboratory scale. Ind. Eng. Chem. Res. 1999, 38, 2571. (23) Di Blasi, C. Dynamic behaviour of stratified downdraft gasifiers. Chem. Eng. Sci. 2000, 55, 2931. (24) Di Blasi, C.; Branca, C.; Santoro, A.; Perez Bermudez, R. A. Weight loss dynamics of wood chips under fast radiative heating. J. Anal. Appl. Pyrolysis 2001, 57, 77. (25) Di Blasi, C.; Branca, C.; Santoro, A.; Gonzalez Hernandez, E. Pyrolytic behaviour and products of some wood varieties. Combust. Flame 2001, 124, 165. (26) Hillis, W. E. Wood and biomass ultrastructure. In Fundamentals of Biomass Thermochemical Conversion; Overend, R. P., Milne, T. A., Mudge, L. K., Eds.; Elsevier: London, 1985; pp 1-34. (27) Theander, O. Cellulose, hemicellulose and extractives. In Fundamentals of Biomass Thermochemical Conversion; Overend, R. P., Milne, T. A., Mudge, L. K., Eds.; Elsevier: London, 1985; pp 35-60. (28) Antal, M. J.; Allen, S. G.; Dai, X.; Shimizu, B.; Tam, M. S.; Grønli, M. G. Attainment of the theoretical yield of carbon from biomass. Ind. Eng. Chem. Res. 2000, 39, 4024. (29) Va´rhegyi, G.; Jakab, E.; Antal, M. J. Is the BroidoShafizadeh model for cellulose pyrolyis true? Energy Fuels 1994, 8, 1345. (30) Va´rhegyi, G.; Szabo´, P.; Jakab, E.; Till, F.; Richard, J. F. Mathematical modelling of char reactivity in Ar-O2 and CO2-O2 mixtures. Energy Fuels 1996, 10, 1208. (31) Va´rhegyi, G.; Szabo´, P.; Mok, W. S. L.; Antal, M. J. Kinetics of the thermal decomposition of cellulose in sealed vessels at elevated pressures. Effects of the presence of water on the reaction mechanism. J. Anal. Appl. Pyrolysis 1993, 26, 159-174. (32) Conesa, J. A.; Marcilla, A.; Font, R.; Caballero, J. A. Thermogravimetric studies on the thermal decomposition of polyethylene. J. Anal. Appl. Pyrolysis 1996, 36, 1-15.
Received for review February 8, 2002 Revised manuscript received June 17, 2002 Accepted June 25, 2002 IE0201157
