Ind. Eng. Chem. Res. 2005, 44, 5079-5089
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Decomposition of Wood Particles in Fluidized Beds Nader Jand* and Pier Ugo Foscolo Chemical Engineering Department, University of L’Aquila, 67100 L’Aquila, Italy
High-temperature biomass pyrolysis is the first step of the thermochemical process taking place in a fluidized bed gasifier; it influences strongly the final product gas composition, specifically hydrogen content, as well as tar (heavy organics) production. In this work, the devolatilization of wood particles of controlled size and the combustion/gasification of the remaining char have been studied, as functions of time, in bubbling nitrogen-, steam-, and air-fluidized beds of sand. The influence of particle size, moderate moisture content, bed temperature, and fluidization severity has been investigated experimentally. A semiempirical model, to account for chemical reaction and mass transfer phenomena, has been developed for the devolatilization step. This considers heat transfer to and through the wood particles, and the global wood conversion process described in terms of a single apparent activation energy and a preexponential factor which varies with biomass size. Despite its extreme simplicity, the model is able to provide a remarkably good description of the empirical behavior over the whole range of particle size (5-20 mm) and bed temperature (560-740 °C) explored in the experimental study; its reliable predictions of the overall particle devolatilization time suggest its applicability over a substantially wider interval of variation of these parameters. Introduction Biomass is universally recognized as an abundant source of energy and chemicals, and one that does not contribute to the increase of greenhouse gases in the atmosphere. High-temperature biomass gasification in a fluidized bed reactor is, from among the available conversion options, the closest to industrial exploitation for the production of synthesis gas, and one of the most promising clean and sustainable sources of hydrogen fuel.1-4 Devolatilization is the first step in the biomass gasification process and influences strongly the quality and quantity of the gas produced. Thermally induced biomass decomposition occurs over the temperature range 250-500 °C;5,6 at the severe temperature conditions of gasifiers, the primary tar vapors undergo secondary reactions, which include cracking and steam reforming (both contributing to the yield of permanent gases: CO, CO2, H2, and light hydrocarbons) and polymerization to produce high molecular weight compounds and coke.7 In the fluidized beds of industrial gasifiers, the pyrolysis reactions take place while the particles are heated over a wide temperature range from just above ambient (the biomass feed temperature) up to almost 900 °C. These highly nonisothermal conditions, coupled with the complex chemical reactions and fluid dynamic interactions that typify the fluidization process, constitute difficulties both for experimental investigation and for theoretical modeling. Moreover, the particle morphological changes related to the release of volatile compounds, which represent a considerable fraction of the original biomass feedstock (up to 80%), cause shrinkage and/or fragmentation, both of which affect considerably the overall process duration.8 Devolatilization kinetic data are needed, however, to determine appropriate biomass residence times in the gas* To whom correspondence should be addressed. Tel.: +39-0862-434217. Fax: +39-0862-434203. E-mail: nader@ ing.univaq.it.
ifier, and a knowledge of the quantity and composition of the devolatilization products is required for an assessment of the secondary reactions which occur in the gas phase within the reactor, and for studies on the possibly beneficial effect of catalysts in such applications.9-11 Previous studies have demonstrated the necessity of experimental tests carried out under fluidization conditions for a reliable description of the biomass pyrolysis process taking place in industrial fluidized bed reactors: the particular solid and gas mixing phenomena observed in these systems make it extremely hazardous to extrapolate data obtained under different experimental conditions, such as from laboratory thermobalance experiments.12-14 Relatively few experimental data are reported in the literature for devolatilization of biomass in fluidized bed gasifiers, due to the practical difficulties of obtaining accurate instantaneous measurements of particle size and temperature.15,16 A simple means of evaluating devolatilization profiles, however, is from measurements of the flow rate and composition of evolved volatiles. For this purpose, the extensive use of direct flame observation and gas analysis is reported in the literature.17 These data need to be considered carefully in relation to the lag time following the evolution of volatiles from the particles up until their detection at the sampling point, the flow dispersion within the reactor vessel, and the influence on devolatilization itself of the heat of combustion released by the burning volatile gases. An experimental method for obtaining reliable devolatilization data has been described in a previous paper: 18 it is based on the simultaneous on-line gas analysis and dynamic pressure measurement following the introduction of a few biomass particles to the reactor. The record of instantaneous pressure in the reactor freeboard is utilized to identify the evolution of volatile gas,19 while the on-line analysis of the effluent gas stream enables its composition to be determined. Gas dispersion and lag times have been quantified by means
10.1021/ie040170a CCC: $30.25 © 2005 American Chemical Society Published on Web 11/26/2004
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of pulses of a tracer gas (CO) injected into the fluidized bed. This has shown flow-mixing within the reactor and transmission lines to be reasonably well modeled in terms of a perfect mixer together with plug flow transport: a dynamic system with a first-order time constant of about 7 s and a pure lag time of about 30 s. In this paper, we present and discuss experimental data that highlight the influence of initial biomass particle size, bed temperature, and other operating parameters on the evolution and composition of the primary gases released by the particles, H2, CO, CO2, CH4, and total hydrocarbons, and on the overall kinetics of biomass devolatilization. The combustion with air and gasification with steam of the remaining char have been also studied to quantify its production in the reactor following the devolatilization process and the progress with time of the burning and gasifying reactions. The study also provides a check on the influence of shrinkage and fragmentation of the original fuel particles, where this occurs, and yields reliable information on the combustion characteristics within fast, internally circulating fluidized bed (FICFB) reactors.20 An additional purpose of this paper is to present a very simple model describing the behavior of a single particle in a hot sand fluidized bed gasifier, in terms of devolatilization time and the global rate of wood conversion. Experimental data are shown to validate this model, which may be readily incorporated in dynamic simulation formulations of the fluidization process, such as that of Chen et al.21 published in this journal. The experimental findings of this study, reported below, show that, while the overall devolatilization time increases significantly with biomass size, its gradient with temperature remains approximately constant, indicating little variation in apparent activation energy over the full size range of particles tested. At first sight, these overall devolatilization time variations could be thought to be ascribable simply to heat transfer limitations, the larger particles requiring more time to reach the bed temperature than the smaller ones. Examination of the experimental results, however, shows this mechanism to be insufficient for fully quantifying the observed behavior, thereby pointing to the need to consider the additional effect of mass transfer limitations on the overall kinetic constant required to describe measured conversion rates. On the basis of these considerations, the assumption of a preexponential factor varying with the initial biomass particle size has been included in the model and checked against the available data. A rather wider range of fuel particle size has been examined than in most previous experimental and modeling studies (a 4-fold increase in diameter, corresponding to almost 2 orders of magnitude in particle wood mass) so as to better observe the influence of this quantity on the overall behavior, and with a view to industrial fluidized bed gasification applications. Experimental Section The experimental facility is shown schematically in Figure 1. The fluidized bed reactor, of 100 mm i.d., is encased in a cylindrical electric furnace to maintain it at the desired temperature level. The bed inventory consists of 380 µm sand particles. A feeding system at the top of the reactor enables a batch of wood particles to be dropped instantaneously on to the hot sand bed. These experimental conditions are representative of
Figure 1. Schematic view of the experimental facility.
what happens in practical applications because, in most fluidized bed gasifiers, the biomass feeding point is just above the bed surface. In addition, cold model observations have shown that, with density differences such as those in these systems, biomass particles even if inserted at the bottom of the fluidized bed tend to segregate very fast to the bed surface, most probably traveling upward with the bubbles. As mentioned in the Introduction, two complementary on-line measurement techniques have been utilized to determine the devolatilization kinetics: (i) dynamic pressure measurement in the freeboard, by means of a piezo-electric pressure transducer able to detect the increase in pressure which marks the beginning of evolution of gaseous matter from the biomass particles; (ii) effluent gas analysis, to determine the temporal profiles of the evolved volatiles (IR to detect CO, CO2, and CH4, FID to detect total H-C, expressed as propane equivalent concentration, and TC to detect H2). From knowledge of the flow rate of the fluidizing inert gas and of the composition of the effluent gas, estimates of the instantaneous and cumulative emissions of each analyzed volatile compound may be readily obtained. The total volatile flow rate, after correction for the time lag and dispersion phenomena in the reactor as discussed above, is in very good agreement with the intensity and duration of the pressure overshoot recorded in the reactor freeboard; direct evidence on this point is reported in the next section. Experimental tests have been carried out on this system under various conditions of operation: (i) beech wood spheres of controlled size, with initial diameters of 5, 10, 15, and 20 mm; (ii) bed temperatures of 560, 670, and 740 °C; (iii) excess fluidizing velocity ratios, U/Umf, in the range 2-4.8; (iv) fluidizing gas of nitrogen, steam, air; the tests with air always follow the biomass devolatilization in an inert or steam atmosphere and are performed to investigate the combustion of residual char; (v) dried and 8% moist wood particles.
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Figure 2. Volume shrinkage of 10 mm beech wood particles after two devolatilization tests.
The beech wood particles, obtained from wood logs, have been acquired from TAIL snc, Bergamo, Italy; they are of very reproducible size, with a negligible statistical variation. The 8% humidity content is that of the untreated particles. For complete drying, they are held in an oven at 110 °C until a constant weight is reached. The number of particles employed in each test is such that similar masses of wood are utilized each time, to operate always in the same gas concentration range. To reduce the influence of secondary reactions taking place outside the biomass particles, relatively high gas flow rates (average gas residence time 0.10-0.15 s) and low wood masses (about 2.5 g, corresponding to one particle of the largest size tested) have been adopted in each run. As confirmed by means of the power spectral density function (PSDF) of pressure fluctuations, the fluidizing velocities adopted span the vigorous bubbling regime up to slugging bed conditions. In a few tests, following the devolatilization stage, the reactor was cooled to room temperature in a nitrogen flow (instead of burning off the residual char with air), and the fuel particles were collected from the bed inventory. For all particle sizes investigated, it was found that the particles maintain their spherical shape throughout the devolatilization stage, with an overall reduction to about 50% of their original volume and without fragmentation, as shown in the photograph reproduced in Figure 2. For comparison, some devolatilization tests on the beech wood particles were carried out under thermogravimetric balance conditions, at a 10 °C/min heating rate; it was found that the overall mass loss was then somewhat lower than in the corresponding fluidized bed tests, higher heat-up rates, favoring volatiles formation at the expense of char, and/ or the action of mechanical attrition, both occurring within the fluidized bed environment, perhaps being responsible for these differences. For the tests carried out in the inert (nitrogen) atmosphere, the amount of tar released during the devolatilization phase has been estimated as the difference between the mass loss (original wood particle dry, ash free (daf) weight minus the residual char, obtained from the cumulative CO2 detected during the combustion phase) and the mass of evolved gases (CO, CO2, H2, and CH4) measured with the analytical equipment. The product yield distribution estimated in this way is reported in Figure 3, as a function of particle diameter and fluidized bed temperature. For each set of experimental conditions, the results have been averaged over at least three different test runs. A check on the closure of the mass balance is possible for some tests, where measurements of total hydrocarbons released by the wood particles are available; it has been found in these cases that the maximum error in the overall mass balance has been always less than (5%. Some clear trends are discernible in Figure 3. Tar
Figure 3. Products percentage yield resulting from wood devolatilization in inert atmosphere.
Figure 4. Cumulative gas composition for wood devolatilization tests in inert atmosphere, as a function of the particle size (Tb ) O, 560 °C; ], 670 °C; +, 740 °C).
fractions become progressively lower with increasing bed temperature, showing the importance of temperature on the secondary decomposition reactions of primary tar products within the particles. With large particles, the final residual mass (char) is somewhat greater than that corresponding to smaller wood sizes at the same bed temperature; this can be attributed to the comparatively lower effective temperature levels at which devolatilization occurs in a large particle, as will be discussed in the next section of this paper. It has also been found that both fluidization severity and moderate wood particle humidity have negligible influence on the product distribution and most other quantities observed in this study, within the limits of calculation error. Measured cumulative gas volumetric compositions are shown in Figure 4, as functions of particle size and bed temperature for devolatilization in the inert atmosphere. Increasing the particle size reduces CO (by far the preponderant component) and consequently carbon in the volatiles gases: this tendency is in agreement with the increase in residual char noted above. Additional tests were performed with the 5 and 10 mm
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Figure 5. Comparison of volatile gas composition obtained when nitrogen and steam are utilized as fluidizing medium, respectively. Tar is expressed as propane-equivalent concentration.
particles at 650 and 750 °C to check the influence of extra-particle reactions on the composition of the volatile gases; for each set of test conditions, both the inert gas (nitrogen) and the steam (60% steam by volume and nitrogen) were utilized as the fluidizing medium. As shown in Figure 5, negligible changes in gas composition were detected at 650 °C, and fairly limited ones at 750 °C, thereby confirming (along with the equally weak influence of fluidizing velocity noted above) that most of the reactive processes take place inside the particles at the operating conditions chosen in this study. It is also noticeable that at 750 °C the propane equivalent concentration of all hydrocarbons in the volatiles, when the measured methane concentration has been subtracted, is close to zero, in good agreement with the findings in Figure 3, insofar as the comparatively negligible presence of tar vapors at this temperature level is concerned. We now move toward consideration of the temporal evolution of wood decomposition phenomena. Devolatilization in the presence of steam is accompanied by char gasification, which, however, occurs on a much longer time scale, as shown in Figure 6, where a prolonged tail is clearly identifiable in the H2 and CO2 concentration profiles. In this phase of the process, CO2 is most probably obtained from CO by means of the water gas shift reaction. Figure 6 reports the instantaneous yield of each gas released by the particle normalized with respect to the maximum flow rate of carbon monoxide. After about 20 min from the test starting time, the fluidizing gas is switched to air to burn off the residual char still present in the reactor, and to determine its quantity (expressed as carbon) by measuring the cumulative amount of CO2 produced. Such tests were repeated with identical procedures but with a change of the time interval of particle exposure to steam, to obtain information on the overall kinetics of char steam gasification. The weight percentage of remaining char as a function of the temporal duration of exposure to steam is reported in Figure 7 for the case of 10 mm wood particles dropped into a fluidized bed of sand at 750 °C. The char gasification time is confirmed to be much longer (more than an order of magnitude) than the devolatilization time, τdev, which we now consider in terms of the results presented below.
Figure 6. Time evolution of volatile gases during wood devolatilization and char gasification in steam atmosphere, followed by combustion with air of the remaining char.
Figure 7. Steam gasification of char formed as a result of the devolatilization process.
Figures 8 and 9 relate to most of the experimental tests performed in this study, taking into account all wood sizes adopted. Figure 8 shows temporal profiles for the release of volatile gases from the fuel particles from the instant they are dropped into fluidized beds maintained at two distinct temperature levels; also shown are variations induced by utilizing particles with an 8% moisture content (rather than previously dried particles) for a bed at 560 °C. Figure 9 illustrates the corresponding trends with time of carbon dioxide evolution during combustion at 740 °C with air of the char formed by wood particles of different size in the previous devolatilization step. A marked influence of initial particle size on both phenomena is noticeable, although with char combustion the instantaneous release of CO2 and the overall burning time tend to converge as the original particle size increases: this behavior is attributable to fragmentation, which certainly occurs during char combustion and is more pronounced for the larger original particles. As far as devolatilization is concerned, it is also worth noting that the particle moisture content, although fairly moderate, leads to an increase in the overall devolatilization time and tends
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Figure 8. Effect of bed temperature, initial wood size, and moisture content on the instantaneous yield of volatile gases during devolatilization.
to delay the release of volatiles, specifically carbon monoxide and dioxide, under otherwise identical conditions. The overall devolatilization time, τdev, observed at different temperature levels and initial particle diameters is reported in Figure 10. The solid lines have been calculated by means of the simulation model to be discussed in the following section. The regression of the experimental data indicates that at a given bed temperature the devolatilization time is more or less proportional to the diameter of the biomass particles; these findings agree with correlations published in the literature and previously obtained in our laboratory using different biomass species,19,23 which all exhibit the
mathematical form of a power law relation with exponent close to unity. Simulation Model Solid decomposition is a complex phenomenon, and its modeling has been attempted with reference to highly diversified systems of practical interest.22 Comprehensive pyrolysis models described in the literature23-26 allow for the prediction of gas, tar, and char yields under various conditions of operation; of necessity, these are numerically complex and require the knowledge of a large number of physical and kinetic parameters. Our focus is on a semiempirical approach,
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Figure 9. Carbon dioxide release as a function of time, during combustion with air of char resulting from wood particles of different sizes.
“wood conversion” (which replaces “concentration”, an unsuitable concept when it comes to considering a reacting solid); the rate constant (more properly the “conversion” rate constant) is characterized by means of an apparent activation energy and a preexponential factor. Intraparticle and external mass transfer resistances are incorporated in the overall kinetic expression.30 Endothermic and exothermic reaction steps are assumed to balance each other thermally, so that the overall devolatilization enthalpy variation may be disregarded; this hypothesis of a heat-neutral process has been applied elsewhere in the literature, even in more sophisticated models.25 When the kinetic parameters of the model are matched to the experimental data for overall devolatilization time, it will be seen that the preexponential factor is found to vary as a power function of the initial particle diameter, so that, in all three, kinetic parameters become necessary. The defining equations define the conservation of particle mass (ODE) and energy (PDE). The instantaneous temperature profile within a spherical biomass particle, after it has been dropped into a hot, fluidized sand bed, is obtained from the energy conservation equation on application of the Fourier heat conduction law as applied to an effectively homogeneous spherical fuel particle:
FCp
∂T 1 ∂ 2 ∂T ) 2 r keff ∂t ∂r ∂r r
(
)
(1)
The particle temperature is initially uniform (T ) 20 °C at t ) 0). The boundary condition at the particle surface considers, in addition to the convective and radiant heat transfer terms, heating of the volatiles from the average particle temperature up to the bed temperature across the external film surrounding the particle:
keff Figure 10. Overall devolatilization time as a function of particle size and bed temperature: experimental and calculated data.
which makes use of a reduced number of parameters that may be readily estimated from the available experimental data. It has been shown that a heterogeneous reaction model, with a single activation energy and preexponential factor, fails to describe thermal and biomass size effects over a large range of temperature and particle size conditions. To overcome this difficulty and, at the same time, maintain a tight restriction on the number of parameters, distributed activation energy models have been suggested;27 these possess the notable advantage of relating clearly to observed variations in system behavior. (Interestingly enough, it has been shown by Burnham and Braun28 that fitting to a distribution of reactivity may be identical to fitting to a pseudo nth-order rate law.) A numerical drawback of these models, however, relates to the burdensome necessity of having to carry out an integration from zero to infinity for the assumed activation energy distribution at every grid point within the particle for each time step. The approach adopted here is the much simpler one frequently adopted for applying kinetic concepts to thermally induced reactions in solids;29 it is borrowed from homogeneous kinetics and postulates a pseudo single-step overall reaction mechanism of first order in
∂T ) h(Tb - Ts) + | ∂r r)R(t) m ˘ vCpv σ(Tb4 - Ts4) (Tb - Tmean) (2) 2 1 1 + - 1 4πR(t) p d
with spherical symmetry dictating a zero radial gradient at the particle center. According to the assumptions summarized above, particle wood mass conservation may be expressed as follows:
dXw )K h G(1 - Χw) dt
(3)
where the wood conversion, Χw, is in terms of dry, ashfree (daf) biomass, mw:
Χw )
mw0 - mw(t) mw0
(4)
The product (volatiles and char) distribution is assumed to be that provided by the biomass proximate analysis, so that the instantaneous volatile mass released by the particles, appearing in eq 2, is obtained as a fraction, ν, of the reacted wood:
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m ˘ v ) νmw0
dΧw dt
(5)
The instantaneous global kinetic constant, to be utilized in eq 3, is obtained by volume averaging local values along the particle radius, calculated as a function of temperature:
K h G(t) )
3 R(t)3
∫0R(t) Ae-E
app/RT
r2 dr
(6)
As already noted, the preexponential factor appearing in eq 6 is assumed to vary with the initial biomass particle size:
A ) A*D0-R ) Ai ) A1
( ) D01 D0i
R
(7)
3
(8)
As noted in the previous section, for all biomass sizes investigated, particle volume was found to reduce to about 50% of its initial value as a result of the devolatilization process: 3
Dfin ) x0.5D0
property
symbol
values
fluidized bed temperature solid density (daf) solid specific heat volatiles specific heat solid thermal conductivity pre-exp. factor in eq 7 activation energy exponent in eq 7 heat transfer coefficient biomass particle diameter volatiles yield (volatiles/ biomass daf) Stefan-Boltzmann constant particle emissivity34 bed emissivity34
Tb F Cp Cpv keff A1 Eapp R h D0 ν
560, 675, 740 613.5 1500 2000 0.11 1.5 20 500 0.7 335 5, 10, 15, 20 0.8a
°C kg/m3 J/(kg K) J/(kg K) W/(m K) s-1 J/mol
σ p b
5.67 × 10-8 0.8 0.8
W/(m2 K4)
a
where the preexponential factor value corresponding to the smallest particle size investigated experimentally (D01 ) 5 mm) has been assumed as the reference value for the calculation of Ai for other initial particle diameters, D0i. The devolatilization progress in turn determines a corresponding shrinkage of the particle diameter with time; with the assumption of a linear relation for the reduction of particle volume with wood conversion (and with the mass of volatiles released), we have
D(t) ) 2R(t) ) xD03 - (D03 - Dfin3)Χw
Table 1. Physical Quantities and Kinetic Parameters Utilized in the Simulation Runs
(9)
The energy conservation equation for the temperature field in the solid domain has been solved using a secondorder explicit finite difference algorithm, implemented using MATCAD plus 2000. The volume-averaged global kinetic rate is thereby calculated, and the mass loss, new particle diameter, flow rate, and heat capacity of the volatiles are determined. Particle shrinkage is taken into account in progressive integration steps by the appropriate correction of the dimensional time constant. From 60 to 80 spatial grid points were chosen to provide good spatial resolution of the steep temperature gradients encountered. The ratio between time and spatial grid amplitudes is chosen to be one tenth, which guarantees good stability for the explicit method of solution. A two-step fitting procedure was adopted for homing on to the best values for the kinetic parameters: with reference to the smallest wood particle diameter, D01, the apparent activation energy, Eapp, and the preexponential factor, A1, were determined by minimizing the differences between calculated and observed values of the devolatilization time at all three bed temperature levels investigated experimentally. The exponent R appearing in eq 7 was then fixed by matching the model predictions to the devolatilization time observed for the largest particle diameter, D04, at the corresponding bed temperatures. As a check on the general applicability of the evaluated kinetic parameters, they were used to predict devolatilization for the two intermediate wood
units
W/(m2 K) mm
Value obtained from the wood proximate analysis.
particle sizes, D02 and D03, for comparison with experimentally determined values. In the numerical simulations, it has been assumed that the devolatilization process is complete when 98% of the initial wood mass has been converted (Χw ) 0.98). Table 1 summarizes the system properties and operating parameters which appear in the model equations, the respective symbols, and the values adopted in the mathematical calculations. For sake of simplicity, constant particle properties, averaged between those for virgin biomass and char, have been assumed; although the effect of temperature on these quantities is certainly important, the convenient observation of Larfeldt et al.,31 that the increases with temperature of specific heat and effective thermal conductivity effectively compensate for each other, to result in a constant thermal diffusivity, has been adopted. The convective heat transfer coefficient at the particle surface has been estimated from correlations reported by Kunii and Levenspiel,32 with the assumption that the biomass particles are at least 10 times larger than the particles in the fluidized bed inventory. The solid lines reported in Figure 10 give a clear indication of the ability of this simple model to describe the observed trends of devolatilization time as a function of fluidized bed temperature and initial wood particle size. As noted in the previous section, the experimental trend of devolatilization time versus particle size is well approximated by a linear dependency on the initial fuel particle diameter. The model is able to capture this trend by means of the combined influence of particle size on both the intraparticle instantaneous temperature distribution and the global kinetic constant. The simple model accounts well for the simultaneous occurrence of chemical reaction and mass transfer within the fuel particles, their combined effect determining the devolatilization rate. This is also confirmed by the relatively low apparent activation energy, in comparison with “true” chemical values reported in the literature.5,6 Figure 11 shows three different sets of data, experimental and calculated, for the examined case of the largest wood particle (D0 ) 20 mm) dropped in the fluidized bed at the lowest temperature level. The curves show, respectively, the dynamic pressure signal in the freeboard of the reactor (low pass filtered (0.7 Hz) to eliminate the noise caused by the passage of bubbles), the measured cumulative flow of volatiles, and the instantaneous yield of volatiles calculated by the simulation model. To assist with the comparison, normalized
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Figure 11. Release of volatiles as a function of time: comparison between experimental data (dynamic pressure and gas analysis measurements) and calculated values; D0 ) 20 mm, Tb ) 560 °C.
values are reported on the vertical axis, obtained by dividing by the corresponding maximum value; also, lag times, between the pressure signal and the responses of the gas analysis, have been retained, the latter having been corrected for dispersion in the reactor freeboard. This figure indicates a very good agreement between pressure overshoot in the freeboard, caused by the release of volatiles, and their measured flow rates, revealing the strict interconnection between both observation methods and the useful complementary information that they furnish. In addition, the simplified model appears able to describe the trend with time of the yield of volatiles with reasonable accuracy, particularly in the initial and final phases of the devolatilization process. It should be pointed out that the experimental cumulative flow of volatiles has been calculated by summing the flows of each component, as obtained from the records of the analytical equipment (Figure 8). This has two major consequences that are discussed below. As is clear from Figure 8, for each compound released by the particle, the time corresponding to its maximum yield is different, so that the cumulative maximum in Figure 11 is the result of adding together different temporal profiles, making it difficult to relate it accurately to a global wood conversion model. On the other hand, the available analytical records neglect heavy condensable organic compounds, thereby preventing their inclusion in the cumulative instantaneous yield of volatiles; as noted in the previous section, the overall mass balance enables an estimate of this tar quantity to be made for each experimental run, but a corresponding flow rate as a function of time is not available. Further features of the simulations results are reported in Figures 12 and 13: temperature profiles within the particles and averaged global kinetic constants, both at Χw ) 0.50 and Tb ) 740 °C. It is clear from Figure 12 that with the smallest biomass particles the model predicts most of the devolatilization to occur at local and average temperature levels much closer to the bed temperature than is the case with the largest particles, as is to be expected. Figure 13 also shows, as functions of initial wood particle diameter, conversion rate constants utilized in the model (solid line marked with black circles); the corresponding quantities when the entire particle is assumed to be at the fluidized bed
Figure 12. Temperature profiles inside the particles at Χw ) 0.50, and corresponding volume-averaged values.
Figure 13. Volume-averaged global kinetic constant versus initial particle size; influence of disregarding the particle temperature profile and the variation of the preexponential factor.
temperature (solid line marked with squares); and these same quantities calculated on the basis of the intraparticle temperature profile predicted by the model, but keeping the preexponential factor equal to that for the smallest particle size (dashed line marked with empty circles). It is clear from this figure that both factors, temperature and initial particle size, determine corrections of comparable magnitude that need to be made to the global kinetic constant to match experimental results. A model sensitivity analysis has been performed with regard to the effects on devolatilization time and maximum flow of released mass resulting from a reduction or increase of 30% of each of the major physical properties (effective particle thermal conductivity, particle and volatiles specific heat, convective heat transfer coefficient in the film layer surrounding the particle) and of the kinetic parameters. The results are reported in the bar charts of Figure 14, with reference to the largest particle at the highest fluidized bed temperature level (740 °C). It has been also found that a good correlation always exists between the increase (or
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Figure 15. Predictive capability of the numerical simulations.
Figure 14. Results of a parameter sensitivity analysis of the computational model.
reduction) of the maximum yield of volatiles and shortening (or lengthening) the corresponding time interval needed for it to occur. The decision to assign average values to the physical properties, neglecting their temperature and conversion variations, is well justified by these numerical calculations, which clearly show low sensitivity of the model to these quantities as compared to the effect of equivalent relative variations of the kinetic parameters. Expressing the governing equations in dimensionless form yields the following characterizing dimensionless groups:
Bi0 )
[
]
D0 h σTb3 + 1 keff 2 1 + -1 p d
(10)
h G(Tb,D0) D02FCpK 4keff
(11)
νCpv Cp
(12)
Φ)
Cn )
Under the experimental operating conditions, Bi0 assumes values spanning the thermally thick (0.2 < Bi0 < 10) and the thermal wave (Bi0 > 10) devolatilization regimes; the heat transfer rate reduction, linked to volatiles flow in the particle external film, moves the systems toward the thermally thick regime. Equivalently, the devolatilization modulus, Φ (the ratio of chemical kinetics to intraparticle heat diffusion effects), varies from order 1 (smallest particle, lowest temperature) to order 10 (largest particle, highest temperature).
These results show that the experiments performed cover the range from chemical kinetics and internal heat transfer control, to full internal heat transfer control. Finally, the predictive capability of the simulation tool is tested in Figure 15, where additional experimental data on devolatilization time, in addition to those obtained in this study, are compared to values calculated by the model when the corresponding operating conditions are taken into account. The first set of data relates to the conversion of ground almond shells of very small size (average diameter in the range 0.5-1.5 mm): these data were obtained some years ago19 utilizing a different fluidized bed bench plant, and over a slightly wider bed temperature range (500-800 °C); only dynamic pressure records were utilized for these measurements. As found by Di Felice et al.,23 the devolatilization time is practically independent of the particle diameter for particles smaller than 1 mm; therefore, these data are representative of the limit where the process becomes entirely controlled by chemical kinetics: the figure shows that the model is able to capture this limit, at least so far as the order of magnitude is concerned. Because of the scarcity of published devolatilization results in fluidized beds, data obtained under different conditions are also considered, obtained in a properly modified thermobalance, which allows for the dropping of particles in a muffle maintained under isothermal conditions;14 although the mechanism of heat transfer to the particle (radiation and convection by means of an inert gas flow) is certainly different from that in a fluidized bed, on the basis of the modest sensitivity shown by the model to the convective heat transfer coefficient, these experiments could relate to the present work and serve the purpose of testing the simulation predictions up to higher temperature levels (950 °C). Again, Figure 15 shows the predictions to be well in line with experimental observations, suggesting the general capability of this model to extend beyond purely interpolative applications. Conclusion A wide experimental investigation, relating to the design and operational issues of biomass gasification, has been performed into the devolatilization of wood particles in a fluidized bed reactor at high temperature. Devolatilization is relatively rapid in comparison with
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char gasification phenomena, but the study of its kinetics is important for quantifying the dynamics of the release of a considerable amount of volatile material, corresponding to an overall flow rate comparable to that of the fluidizing medium and, as a consequence, having an important impact on the fluid dynamic behavior of the reactor as a whole. These process conditions affect the composition of primary gas and vapors released by the particles, so that this additional information allows for a better choice of operating parameters, including gasification agents and catalytically active substances needed to condition the product quality in relation to the desired application. The data illustrated and discussed in this paper allow for quantitative estimations of the important effect of bed temperature and fuel particle size on devolatilization time, cumulative product distribution, instantaneous flow rate, and composition of volatile gases. The influence of a moderate moisture content also has been examined. It has been found that the results are only marginally affected by the fluidization severity and the presence of steam in the fluidizing medium, indicating that the experimental conditions are such as to minimize extra-particle reaction processes. An attempt has been made to describe the devolatilization experimental results by means of a simplified, single-step kinetic model, utilizing a reduced number of physical properties and requiring only simple numerical procedures. Once the global conversion rate parameters have been fixed by matching the empirical values of the devolatilization time corresponding to the smallest and largest particle size, the model is able to predict important features of this phenomenon over a fairly wide range of operating conditions. The overall conversion rate is a function of temperature and biomass size, indicating a dependency on both chemical reactions and mass transfer phenomena. In the presence of a significant convective flux of volatiles, transport resistances may be linked to the process of formation of cracks and porelike paths in the originally more compact structure of the wood. Alternatively, these transport resistances may be attributable to diffusion of volatiles from the production sites toward the middle of the particle occurring simultaneously with the outward flow through the outer particle shells, and promoting wood pyrolysis reactions; this latter hypothesis appears compatible with the functional dependencies of the global kinetic constant, characterized by a fairly low apparent activation energy and a preexponential factor varying inversely with particle size, both being typical of simultaneous diffusion and reaction processes.33 Finally, this simple model is suitable for including devolatilization kinetics into comprehensive dynamic models of fluidized gasification reactors, as a means for describing simply and reliably the time evolution of biomass particles in the fluidized bed inventory. Acknowledgment This work was funded in part by the European Commission (Contract ENK5-CT2000-00314) and by the Italian Ministry for Research (MIUR). We are grateful to G. Antonelli for his assistance in the experimental tests. Nomenclature Bi0 ) overall Biot number (defined in eq 10) Cn ) thermal capacity number (defined in eq 12)
D ) instantaneous wood particle diameter (m) K h G ) volume-averaged global devolatilization kinetic constant (s-1) mw ) wood particle mass, dry and ash-free (kg) mw0 ) initial wood particle mass, dry and ash-free (kg) m ˘ v ) instantaneous mass flow rate of evolved volatiles (kg/ s) P ) piezometric pressure (Pa) Q ) volumetric flow rate of volatile gases (Nm3/s) r ) distance from wood particle center (m) R ) instantaneous wood particle radius (m) R0 ) initial wood particle radius (m) U ) superficial gas velocity (m/s) Umf ) minimum fluidization velocity (m/s) t ) time (s) T ) local wood particle temperature (°C) Tmean ) volume-averaged wood particle temperature (°C) Ts ) surface temperature of wood particles (°C) τdev ) overall devolatilization time (s) Φ ) devolatilization modulus (defined in eq 11) Χw ) wood conversion (defined in eq 4)
Literature Cited (1) Bridgwater, A. V. The technical and economic feasibility of biomass gasification for power generation. Fuel 1995, 74, 631. (2) Beenackers, A. A. C. M.; Maniatis, K. Gasification technologies for heat and power from biomass. Proceeding of the 9th European Bioenergy Conference, Copenhagen, Denmark, June 24-27, 1996; Paper O.C2.21. (3) Rapagna`, S.; Jand, N.; Foscolo, P. U. Catalytic gasification of biomass to produce hydrogen rich gas. Int. J. Hydrogen Energy 1998, 23, 551-557. (4) Hofbauer, H.; Rauch, R.; Foscolo, P. U.; Matera, D. Hydrogen rich gas from biomass steam gasification. Proceeding of the 1st World Conference on Biomass for Energy and Industry, Sevilla, Spain, June 5-9, 2000; Paper V8.167. (5) Di Blasi, C.; Branca, C. Kinetics of primary products formation from wood pyrolysis. Ind. Eng. Chem. Res. 2001, 40, 5547. (6) Rath, J.; Staudinger, G. Cracking reactions of tar from pyrolysis of spruce wood. Fuel 2001, 80, 1379-1389. (7) Milne, T.; Agblevor, F.; Davis, M.; Johnson, D. A review of the chemical composition of fast pyrolysis oils from biomass. In Advances in Thermochemical Biomass Conversion; Bridgwater, A. V., Boocock, D. G. B., Blackie, A. P., Eds.; 1997; p 409. (8) Bryden, K. M.; Hagge, M. J. Modeling the impact of moisture and char shrinkage on the pyrolysis of a biomass particle. Fuel 2003, 82, 1633. (9) Rapagna`, S.; Jand, N.; Kiennemann, A.; Foscolo, P. U. Steam-gasification of biomass in a fluidized-bed of olivine particles. Biomass Bioenergy 2000, 19, 187-197. (10) Rapagna`, S.; Provendier, H.; Petit C.; Kiennemann, A.; Foscolo, P. U. Development of catalysts suitable for hydrogen or syn-gas production from biomass gasification. Biomass Bioenergy 2002, 22, 377-388. (11) Corella, J.; Caballero, J. A.; Aznar, M. P.; Brage, C. Two advanced models for the kinetics of the variation of the tar composition in its catalytic elimination in biomass gasification. Ind. Eng. Chem. Res. 2003, 42, 3001. (12) Conesa, J. A.; Marcilla, A.; Caballero, J. A.; Font, R. Comments on the validity and utility of the different methods for kinetic analysis of thermogravimetric data. J. Anal. Appl. Pyrolysis 2001, 58-59, 617-633. (13) Gronli, M. G.; Varhegyi, G.; Di Blasi, C. Thermogravimetric analysis and devolatilization kinetics of wood. Ind. Eng. Chem. Res. 2002, 41, 4201. (14) Rath, J.; Steiner, G.; Wolfinger, M. G.; Staudinger, G. Tar cracking from fast pyrolysis of large beech wood particles. J. Anal. Appl. Pyrolysis 2002, 62, 83. (15) Winter, F.; Prah, M. E.; Hofbauer, H. Temperature in a fuel particle burning in a fluidised bed: the effect of drying,
Ind. Eng. Chem. Res., Vol. 44, No. 14, 2005 5089 devolatilization and char combustion. Combust. Flame 1997, 108, 302-314. (16) Di Blasi, C.; Branca, C. Temperatures of wood particles in a hot-sand bed fluidized by nitrogen. Energy Fuels 2003, 17, 247. (17) de Diego, L. F.; Garcı`a-Labiano, F.; Abad, A.; Gaya`n, P.; Ada`nez, J. Coupled drying and devolatilization of nonspherical wet pine wood particles in fluidized beds. J. Anal. Appl. Pyrolysis 2002, 65, 173. (18) Jand, N.; Foscolo, P. U. Pyrolysis and Gasification Kinetics of Biomass Particles of Different Size in a Fluidised Bed. In Chemical Engineering Transaction, Proceedings of the 6th Italian Conference on Chemical and Process Engineering, Pisa, Italy, June 8-11, 2003; Vol. 3, pp 51-56. (19) Jand, N. Gassificazione di biomasse in letto fluidizzato per la produzione di idrogeno o gas di sintesi. Ph.D. Thesis, Universita` di Napoli Federico II, Napoli, Italy, 1998. (20) Pfeifer, C.; Hofbauer, H.; Rauch, R. In-Bed Catalytic Tar Reduction in a Dual Fluidized Bed Biomass Steam Gasifier. Ind. Eng. Chem. Res. 2004, 43, 1634-1640. (21) Chen, Z.; Gibilaro, L. G.; Foscolo, P. U. Two-dimensional voidage waves in fluidised beds. Ind. Eng. Chem. Res. 1999, 38, 610-620. (22) Yoon, I. S.; Yang, Y.; Dudukovic, M. P.; Kardos, J. L. The devolatilization of polyimide fiber composites: model and experimental verification. Polym. Compos. 1994, 15, 184-196. (23) Di Felice, R.; Coppola, G.; Rapagna`, S.; Jand, N. Modeling of biomass devolatilization in a fluidized bed reactor. Can. J. Chem. Eng. 1999, 77, 325. (24) Di Blasi, C. Modelling intra- and extra-particle processes of wood fast pyrolysis. AIChE J. 2002, 48, 2386-2397. (25) Wurzenberger, J. C.; Wallner, S.; Raupenstrauch, H.; Khinast, J. G. Thermal conversion of biomass: comprehensive reactor and particle modeling. AIChE J. 2002, 48, 2398-2411.
(26) Adanez, J.; Gayan, P.; de Diego, L. F.; Garcia-Labiano, F.; Abad, A. Combustion of Wood Chips in a CFBC. Modeling and Validation. Ind. Eng. Chem. Res. 2003, 42, 987-999. (27) de Diego, L. F.; Garcı`a-Labiano, F.; Abad, A.; Gaya`n, P.; Ada`nez, J. Modeling of the devolatilization of nonspherical wet pine wood particles in fluidized beds. Ind. Eng. Chem. Res. 2002, 41, 3642. (28) Burnham, A. K.; Braun, R. L. Global kinetic analysis of complex materials. Energy Fuels 1999, 13, 1-22. (29) Vyazovkin, S. Kinetic concepts of thermally stimulated reactions in solids: a view from a historical perspective. Int. Rev. Phys. Chem. 2000, 19, 45-60. (30) Kulkarni, M. S.; Dudukovic, M. P. Dynamics of gas phase and solid-phase reactions in fixed bed reactors. Chem. Eng. Sci. 1996, 51, 3083-3088. (31) Larfeldt, J.; Leckner, B.; Melaaen, M. C. Modelling and measurements of heat transfer in charcoal from pyrolysis of large wood particles. Biomass Bioenergy 2000, 18, 507-514. (32) Kunii, D.; Levenspiel, O. Fluidization Engineering; Butterworth-Heinemann: Woburn, MA, 1991. (33) Smith, J. M. Chemical Engineering Kinetics, 3rd ed.; McGraw-Hill: New York, 1981. (34) Palchonok, G. I.; Dikalenko, V. A.; Stanchits, L. K.; Borodulya, V. A.; Werther, J.; Leckner, B. Kinetics of the main stages of fluidized bed combustion of a wet biomass particles. In Proceedings of the 14th International Conference on Fluidized Bed Combustion; Preto, F. D. S., Ed.; Fairfield, NJ, 1997; Vol. 1, pp 125-133.
Received for review June 3, 2004 Revised manuscript received October 11, 2004 Accepted October 12, 2004 IE040170A
