Biomass pyrolysis in a micro-fluidized bed reactor: Characterization and kinetics

Biomass pyrolysis in a micro-fluidized bed reactor: Characterization and kinetics

Chemical Engineering Journal 168 (2011) 839–847 Contents lists available at ScienceDirect Chemical Engineering Journal journal homepage: www.elsevie...

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Chemical Engineering Journal 168 (2011) 839–847

Contents lists available at ScienceDirect

Chemical Engineering Journal journal homepage: www.elsevier.com/locate/cej

Biomass pyrolysis in a micro-fluidized bed reactor: Characterization and kinetics Jian Yu, Changbin Yao, Xi Zeng, Shuang Geng, Li Dong, Yin Wang, Shiqiu Gao ∗ , Guangwen Xu ∗ State Key Laboratory of Multi-phase Complex System, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China

a r t i c l e

i n f o

Article history: Received 6 November 2010 Received in revised form 19 January 2011 Accepted 27 January 2011 Keywords: Micro-fluidized bed Reaction kinetics Gas–solid reaction analysis Biomass Pyrolysis

a b s t r a c t A micro-fluidized bed reactor (MFBR) was developed to enable (1) on-line pulse feeding and rapid heating of particle reactant, (2) effective suppression of the interfacial diffusion via fluidization, (3) minimization of intra-particle diffusion through adoption of fine solid reactants, and (4) on-line monitoring the composition of effluent product gas using, for example, process mass spectrometer. Application of the MFBR to biomass pyrolysis demonstrated that the reactor led the pyrolysis to have higher gas yield and less remaining carbon than the test in TG, and at 1173 K the reaction finished in 10 s. The time span to release an individual gas component appeared longest for H2 , shortest for CO2 and equivalent for CH4 and CO in between. Reaction kinetics was investigated with respect to the formation of individual gas component and pyrolysis gas mixture. The resulting activation energy and preexponential factor with respect to gas mixture were 11.77 kJ/mol and 1.45 s−1 , respectively. These values were obviously lower than those measured with TG and fixed bed reactors, reflecting the quick reaction nature enabled by the MFBR. A consequent comparison revealed further the factors that affect the values of the kinetic parameters. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Biomass is a widely available, renewable and CO2 -neutral energy resource, which is increasingly used as an alternative for fossil fuels [1]. Biomass pyrolysis is essentially important to the utilization of biomass energy. It provides a viable way to produce bio-oil and is also the first step of chemical reactions involved in all the other thermal conversion technologies, such as gasification. Therefore, understanding the physical and chemical characteristics of pyrolysis comprises one of the most critical issues required for development of biomass thermal conversion technologies. By far, thermogravimetric (TG) method has been generally used to characterize the biomass pyrolysis process and deduce its reaction kinetics. It is done by measuring the mass loss of a sample held in the TG cell during a specified heating program. Many researchers have reported TG-measured kinetic data of biomass pyrolysis for different biomass materials under different heating rates [2–7]. Nonetheless, testing biomass in TG suffers a serious drawback resulting from the instability of the fuel which causes the composition and structure of the fuel sample to change quickly with the temperature during heating the TG. Hence, the reaction characteristics and kinetic data obtained at relatively high temperatures are in fact not regarding the original biomass but an intermediate with certain physiochemical changes at lower temperatures. Meanwhile, the chemical processes in TG suffer seriously from the

∗ Corresponding authors. Tel.: +86 10 82544886; fax: +86 10 82629912. E-mail addresses: [email protected] (S. Gao), [email protected] (G. Xu). 1385-8947/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.cej.2011.01.097

interfacial gas diffusion between the reactor space and the solid sample inside the TG cell. Consequently, scientists designed various other reactors to study the kinetics and reaction features of biomass pyrolysis. The typical ones include the mesh reactor [8,9], self-stirred tank reactor [10], fluidized bed reactor [11,12] and fixed bed reactor [13,14] in millimeters of inner diameter. These reactors, however, do not have standardized configurations and suffer still the limitations caused by gas mixing and gas diffusion that are present inevitably in such reactors. In this study, a micro-fluidized bed reactor (MFBR) was employed to realize the isothermal reaction conditions and to minimize the interfacial diffusion limitations for gas–solid reaction analysis. The major advantages from using the MFBR were previously reported in Yu et al. [15]. Its involved fundamental idea is the use of a micro-size fluidized bed reactor to ensure the reaction’s differential feature under the superior conditions allowed by fluidization, including the minimized diffusion inhibition, on-line feed of reactant sample, quick heating for isothermal conditions, and the test at arbitrary temperatures and in various gaseous atmospheres. These features granted by the MFBR are expected to overwhelm the preceding drawbacks of TG so that the reaction analysis based on MFBR would become a newly customized approach in addition to TG. Intended to demonstrate the eligibility as well as superiority of the MFBR for analyzing various gas–solid reactions, the present article is devoted to investigating the characteristics and accompanied kinetics of biomass pyrolysis in the MFBR. Biomass mass pyrolysis represents a kind of quick reactions of unstable materials, which is inherently difficult to measure the kinetics in TG. By using the new micro-reactor and its associated reaction analysis

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Table 1 Properties of the tested beer lees (d.a.f.). Particle size

Proximate analysis (wt.%)

Ultimate analysis (wt.%)

V

A

FC

C

H

N

O+S

75–120 ␮m

79.9

3.93

16.17

48.74

6.73

4.58

39.95

d.a.f.: dry ash free basis; V: volatile; A: ash; FC: fixed carbon.

approach, it is expected to result in a deep insight into the biomass pyrolysis behavior, kinetics and mechanism. 2. Experimental 2.1. Biomass fuel Fig. 2. A schematic diagram of the experimental apparatus.

Beer lees from Beijing Beer Corporation was used as the biomass fuel for test, and Table 1 presents the results of proximate and ultimate analysis for this fuel (from Ref. [16]). The volatile and fixed carbon contents are about 80% and 16%, respectively. Although the fuel is rich in N, the study in the article is not closely related to this feature. Fig. 1 shows the infrared spectrum of beer lees, suggesting that through the fermentation process the beer lees become rich in O-containing groups including carbonyl, carboxyl and ether groups, which would affect the release of CO2 and CO gases in pyrolysis. Without particular specification, the fuel particle size adopted in this article was 75–120 ␮m. 2.2. Apparatus and procedure Fig. 2 shows a schematic diagram of the experimental apparatus which consists of a fuel sample feeding system, a fluidized bed reactor of 20 mm in i.d. and an effluent gas cleaning and measuring system. Quartz sand of 0.25 mm in Sauter mean diameter was used as the fluidization medium particles in the reactor. The fuel sample feeding system, driven by an electromagnetic valve that releases about 10 mL gas per single pulse, injects a fuel sample into the micro-fluidized bed reactor (MFBR) in less than 0.1 s. The pulsed gas was from a compressed gas stream at 0.2 MPa via a tube of 3 mm in i.d. The total volume of reactor and tubes were about 20 mL. The MFBR consists of two stages separated with porous plate, a lower stage to receive the fuel sample for testing at the specified temperatures, and an upper stage to catch fine sample particles escaping from the bottom stage. Previous study [17] has shown that bubbling fluidization of quartz sand prevailed in the MFBR under the tested conditions of this article. The effluent gas was cleaned in a microfilter filled with desiccant and in turn measured using an online mass spectrometer (AMETEK, American). A computer monitored

the temperatures of the furnace and inside the MFBR, pressures at the reactor inlet and outlet, carrier gas flow rate, actions of the sample feeding device and the output data from the mass spectrometer. Experiment was performed generally with a procedure described herein. Three grams of silica sand was put into each layer of the MFBR, but when testing the C balance of the reaction occurring in the reactor by using air as the fluidizing gas, the upper layer was filled with ␥-Al2 O3 particles that had the same average size and volume as the silica sand to ensure the similar fluidization conditions in both the stages. The adopted ␥-Al2 O3 particles had a BET surface area of 250 m2 /g and an average pore diameter of 7 nm. For the tests in this article argon at flow rates of 100–600 N mL/min was employed to fluidize the particles in the MFBR. The reactor was heated in fluidization state to set the temperature in the reactor to be readily at 500–900 ◦ C. Then, injecting 10–50 mg beer lees into the inside of the fluidized hot quartz sand particles initiated the desired pyrolysis reactions. After pyrolysis, combustion of residual char was carried out at 800 ◦ C by switching the fluidizing gas from argon to air. By integrating the measured CO2 concentration diagram the C amount in the residual char was estimated. The C balance for the reaction in the MFBR was measured by collecting all the effluent gas during the reaction time using a gas bag and in turn analyzing the gas composition in a micro-GC (Agilent 3000). Pyrolysis kinetics analysis was based on the measured time-dependent effluent gas concentration diagrams, and the analysis approach was detailed in the section “Pyrolysis Kinetics Analysis”.

3. Pyrolysis behavior characterization 3.1. Carbon balance verification

Fig. 1. Functional groups of beer lees identified by infrared spectrum.

The approach measuring only the effluent gas (flow rate and composition) makes it difficult to detect the mass balance of the reaction occurring in the MFBR. Thus, air combustion of the fuel at, for example, 800 ◦ C was conducted to analyze the carbon balance of the reaction in the reactor. In this case, the upper layer of the micro-fluidized bed (MFB) was loaded with high-surface area mesoporous ␥-Al2 O3 to capture large molecules and thereby to minimize the formation of tar [18], which could ensure the carbon in the biomass fuel (beer lees) to be completely converted into CO2 and CO to allow an accurate quantification. The result shows that the released C via the gaseous product (combustion flue gas) from the MFBR reached 97 wt.% to 105 wt.% of the C supplied into the reactor via fuel. Table 2 summarizes some experimental data for this justification, indicating essentially the good stability and reproducibility of the measurement in the MFBR.

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Table 3 Product distribution with respect to tested beer lees at different temperatures.

Table 2 Test of carbon balance via combustion of beer lees in MFBR. Sample mass (mg)

Gas flow rate (N mL/min)

Yield (C%)

20.5 23 30 20 25 30

100 200 300 400 500 600

103 105 97 101 98 99

Temperature [◦ C] 600

700

800

900

H2 [%] CO [%] CO2 [%] C1–C3 [%] Total gas yield [%]

0.10 7.45 6.22 4.71 18.48

0.32 19.90 7.81 11.64 39.67

0.75 23.70 9.10 11.68 45.23

1.67 31.32 8.01 10.49 51.49

Remaining carbon [%]

10.23

9.49

6.40

5.84

3.2. Pyrolysis characterization in fixed bed

3.3. Pyrolysis characterization in MFBR

Both fixed bed and micro-fluidized bed reactors were used to investigate the pyrolytic characteristics of beer lees. The test in a quartz fixed bed reactor of 10 mm in inner diameter was carried out in an argon atmosphere under gradual heating to 900 ◦ C at 10 ◦ C/min. The mass of beer lees was 0.5 g and the carrier gas flow rate was 500 N mL/min. The effluent gas product was analyzed using a GC with the plot-Q and molecule-5A columns. As shown in Fig. 3, the evolution of gas components manifested some distinctive features. Carbon dioxide (CO2 ) released early starting from 200 ◦ C and reached a peak amount at about 300 ◦ C. This was followed by the release of CO starting at about 280 ◦ C and with two peak concentrations at about 350 ◦ C and 850 ◦ C, respectively. Then, the release of CH4 was started at 400 ◦ C and reached its peak around 520 ◦ C. These gas releasing characteristics can be explained in terms of the biomass structure and composition [19,20]. The main constituents of beer lees are lignin, hemicellulose and cellulose [21,22]. Lignin has a very complex aromatic structure, while hemicellulose is a kind of polymer composed of 5- and 6-carbon sugars and cellulose is a kind of polymer of glucose [23]. These different components in the fuel have different decomposition temperatures according to TG test [21,23,24], leading thus to the observed different release profiles for different gas species. The released gas amount appeared more for CO2 , and this might be related with the abundant oxygencontaining groups in beer lees (see the FTIR spectrum in Fig. 1). Hydrogen was released at rather higher temperatures comparing to the other gas components because it was formed basically via cracking the released volatiles which requires surely higher temperatures. In fact, there was not significant release of H2 before 500 ◦ C and the peak release of H2 exhibited at 700 ◦ C approximately. The span for H2 release was also longer than for all the other gas species. Furthermore, one can find that the remaining carbon (16.57 wt.%) was nearly equal to the fixed carbon content of the fuel (16.17 wt.%) shown in Table 1.

The pyrolysis of beer lees in the MFBR was performed at given temperatures varying in 600–900 ◦ C. The flow rate of the fluidizing gas (argon) was 300 N mL/min. The release patterns of the major gas components are noticeably different from that shown in Fig. 3 for the fixed bed reactor test at a slower heating rate (10 ◦ C/min). As shown in Fig. 4, the time for completing the pyrolysis reaction was greatly shortened in comparison with that in the fixed bed reactor, and it decreased obviously with elevating the temperature. For different gas components there was a difference in the time to start or end the gas release, but the difference was negligible in comparison with that in Fig. 3. From Fig. 4 one can still identify that CO2 started to release first and at low temperatures, verifying mutually the measurements in the tested two reactors. The data in Fig. 4 suggest that in the MFBR the heating rate, which was shown to be 1000–10000 ◦ C/s for fine particles in ␮m at temperatures of 500–900 ◦ C [15], was much higher than in the tested fixed bed reactor. This caused in turn the lignin, hemicellulose and cellulose in the fuel to pyrolyze almost simultaneously [25]. At temperatures over 800 ◦ C, the pyrolysis reaction in the MFBR finished in 10 s, and this completion time was much shorter than the experimental data from fluidized bed reactors in diameters of about 80 mm [26,27,29]. Hence, there was surely a fast differential pyrolysis reaction in the MFBR, a result from the allowed high heating rate and minimized mixing and diffusion inhibitions in the reactor. The gas yield (in mass against fuel) was determined by sampling the produced gas in the entire reaction time and in turn analyzing the gas via a Micro-GC 3000. Table 3 shows the results obtained, and it is obvious that the total gas yield increased from 18.48 wt.% to 51.49 wt.% corresponding to the temperature rise from 600 ◦ C to 900 ◦ C. The yield of CO, which took about 50% of the total gas product, possessed a larger extent of increase with raising the temperature. The yield of CO2 varied little and remained in 8 wt.% or so in the temperature range of 700–900 ◦ C, indicating that the carboxyl or ester functional groups present in the fuel (see Fig. 1) could decompose completely at temperatures above 700 ◦ C. The yields of hydrocarbons (C1–C3) increased from 4.71 wt.% at 600 ◦ C to 11.68 wt.% at 800 ◦ C, but it further decreased to 10.49 wt.% at 900 ◦ C. This feature of variation indicates that raising temperature promoted the cracking of tar to form hydrocarbons. The decomposition or cracking of hydrocarbons also increased, especially at temperatures over 800 ◦ C, to increase the yield of hydrogen with elevating temperature. Overall, there was a much higher total yield of pyrolysis gas mixture for the reaction in the MFBR than that in the fixed bed reactor characterized in Fig. 3. This is surely related to the much higher heating rate and more efficient mass transfer in the micro-fluidized bed reactor. The remaining carbon after pyrolysis at different temperatures was measured through combustion realized by switching the gas entering the reactor from Ar to air at 800 ◦ C. The amount of C was calculated from the released CO and CO2 . Table 3 shows that the remaining carbon decreased from 10.23 to 5.84 wt.% corresponding to the temperature rise from 600 ◦ C to 900 ◦ C. These amounts

Fig. 3. Pyrolysis gas releasing characteristics in a fixed bed reactor.

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Fig. 4. Pyrolysis gas releasing characteristics in MFBR.

of remaining carbon were much smaller than those shown for the fixed bed test (Fig. 3) or the fixed carbon content of the tested biomass (FC in Table 1). The result complies with the release of more volatiles disclosed above and demonstrates again that there was better mass transfer and higher heating rate in the MFBR to facilitate the pyrolysis reaction and the release of volatiles. 3.4. Parametric investigation in MFBR Herein the progress of the pyrolysis reaction is analyzed in terms of the conversion defined against the volume of the produced pyrolysis gas mixture. Thus, the conversion at the end of gas release was 100%. Fig. 5 shows the variation of the conversion with reaction time at different fluidizing gas flow rates that were below the terminal velocity of the employed silica sand. The time to finish the

Fig. 5. Total gas conversion versus reaction time in MFBR at different flow rates.

reaction decreased with increasing the flow rate and reached 10 s at flow rates exceeding 300 N mL/min at 800 ◦ C. The reaction rate can be calculated from the slope of the conversion curve in Fig. 5, showing that the rate varied little when the flow rate was above 300 N mL/min. This critical gas flow rate represents actually the gas velocity necessary to minimize the external diffusion inhibition on reaction rate. Fig. 6 shows the total pyrolysis gas yield as a function of the gas flow rate at different temperatures (600–800 ◦ C). The gas yield increased with raising the reaction temperature and was affected by the fluidizing gas flow rate. For instance, at 600 ◦ C, the gas yield was merely 3.38 wt.% at 100 N mL/min but this yield increased to 16.92 wt.% at 200 N mL/min. Similar to the demonstration in Fig. 5, the gas yield varied little with the fluidizing gas flow rate when the rate was above 300 N mL/min. The plausible reason for the result was that silica sand particles in the MFBR were not fully fluidized at 100 N mL/min and 600 ◦ C, thus leading to slow heating to the

Fig. 6. Product yields versus gas flow rates in MFBR.

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adopting small fuel particles, but the influence becomes indistinctive as the particle size was below 120 ␮m, implicating that the influence of the intra-particle diffusion would be negligible for the fuels with sizes below 120 ␮m. 4. Pyrolysis kinetics analysis The pyrolysis kinetics of beer lees in the MFBR was analyzed on the basis of the release characteristics of individual gas components and the pyrolysis gas mixture measured at temperatures of 500–900 ◦ C for fuels with sizes of 75–120 ␮m. The adopted flow rate of fluidizing gas (Ar) into the MFBR was fixed at 300 N mL/min to ensure the minimized external and internal diffusion limitations. The conversion X of beer lees in pyrolysis was estimated by

t

Fig. 7. Influence of fuel particle size on the pyrolysis gas conversion.

X(%) =

 tt0e t0

fuel particles and having in turn the low gas yield (the corresponding superficial gas velocity being 0.014 m/s, below the minimum fluidization velocity of 0.022 m/s). At rather higher temperatures (such as 800 ◦ C), the little variation of gas yield with gas flow rate reveals actually that the influence of fluidizing gas velocity, which represents the fluidization conditions, on the gas yield surrounded to the dominant effect of the reaction temperature. Fig. 6 shows also the remaining carbon measured by analyzing the released CO2 in combusting the remaining carbon. At 800 ◦ C the remaining carbon decreased to 5.62 wt.% from 8.50 wt.% in response to the increase in the fluidizing gas flow rate from 100 to 500 N mL/min. This shows that raising the gas velocity in the MFBR facilitated the release of volatiles, lowering consequently the remaining carbon. Fig. 7 shows the influence of fuel particle size on the pyrolysis gas conversion. The reaction completion time was shortened via

Ci × udt Ci × udt

× 100,

(1)

where Ci denotes the concentration of gas species i or the pyrolysis gas mixture, u refers to the flow rate of the effluent gas from the MFBR, and t0 , t and te represent the different stages of pyrolysis at time 0, t and the reaction end, respectively. The kinetic parameters of biomass pyrolysis in isothermal process, as widely reported in the literature [9,11–14], were calculated generally using the shrinking core model. This model suggests that the reaction rate be subject to the un-reacted surface area or remaining amount of reactant, which is expressed with dX = k(T ) × (1 − X)n , dt

ln

 dX  dt

= ln(k(T )) + n ln(1 − X),

(2)

where n is the reaction order and k(T) is the reaction rate constant defined by the Arrhenius equation according to ln(k(T )) = ln(A) −

E RT

Fig. 8. Gas conversion versus reaction time in MFBR at different temperatures for individual gas component.

(3)

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Fig. 9. Correlation of ln(dX/dt) and ln(1 − X) for individual components in MFBR.

4.1. For individual gas component Fig. 8 shows the pyrolysis gas conversion X of major gas components (H2 , CH4 , CO and CO2 ) versus reaction time at different reaction temperatures. Here, the conversion 100% corresponds to the largest gas yield at the end of pyrolysis. The reaction rate defined from the slope of the conversion curve increased with increasing temperature, but the degree of increment in the reaction rate was different for each individual gas component (i.e., the difference in the slope of the curve). It was largest for H2 , and then CH4 , CO and CO2 in succession. These results indicate that the reaction temperature significantly affected the formation of pyrolysis gaseous products, especially for hydrogen. Fig. 9 converts the data of Fig. 8 into the correlation of ln(dX/dt) with ln(1 − X). The entire curve for a given temperature can be divided into three parts denoting three reaction stages (taking the curve at 800 ◦ C as an example). The part (I) refers to the sample heating stage, and as it would be, there was little difference among the tested different temperatures. In this stage, the pyrolysis reaction, if occurred, was mainly on the particle surface. The pyrolysis on the surface would form a layer of carbon and ash on the biomass particle, while the fuel particle could reach a steady temperature via this stage. The pyrolysis reaction then shifted into the second stage (II), the major phase to implement the decomposition. The higher the reaction temperature, the deeper the pyrolysis was, leading to a wider stage II in Fig. 9. In this stage, the reaction was mainly controlled by chemical kinetics because the fuel particles tested were in 75–120 mm that allowed diffusion effect to be negligible. In this stage the reaction rate varied more or less with time (see Fig. 9), and this should be mainly due to the dynamic change in the reaction surface area. Once the pyrolysis was nearly completed, the curve in Fig. 8 tends to be horizontal, suggesting that the reaction rate decreased to its minimum to denotes the entry into the third reaction stage (III).

The data of the stage II in Fig. 9 were analyzed according to Eq. (2) to define the reaction order n and the rate constant k(T). Table 4 summarizes the linear correlation coefficient R for all the gas components, showing that it was above 0.99 for all the curves. The reaction order was mainly between 1.4 and 1.7 at the tested temperatures (except for H2 ). For CO2 and CO it was concentrated on 1.7 and 1.6, whereas for H2 the order at 500 ◦ C was much different Table 4 Reaction order and rate constant of different gas components. Gas

T (◦ C)

ln(k(T))

n

R

H2

500 600 700 800 900

−2.43 −1.67 −1.43 −1.13 −0.86

2.42 1.59 1.65 1.53 1.60

0.99 0.98 0.99 0.99 0.99

CH4

500 600 700 800 900

−1.53 −1.40 −1.14 −1.01 −0.89

1.54 1.33 1.34 1.26 1.46

1.00 0.99 0.99 0.99 0.99

CO

500 600 700 800 900

−1.39 −1.32 −1.08 −0.91 −0.76

1.56 1.75 1.52 1.65 1.71

0.99 0.99 0.99 0.99 0.99

CO2

500 600 700 800 900

−2.01 −1.40 −1.21 −1.10 −1.01

1.71 1.53 1.72 1.71 1.85

1.00 0.99 0.99 0.99 1.00

Pyrolysis gas mixture

500 600 700 800 900

−1.47 −1.22 −1.07 −0.98 −0.82

1.86 1.62 1.62 1.52 1.62

1.00 0.99 0.99 0.99 0.99

J. Yu et al. / Chemical Engineering Journal 168 (2011) 839–847

Fig. 10. Linear fitting of ln(k(T)) and 1/T for individual gas components in MFBR.

from the others and reached 2.42. These suggest that different gas components have different formation mechanisms in the pyrolysis. Fig. 10 re-correlates the rate constants k(T) in Table 4 to define the activation energy (E) and frequency factor (A) for the gas components H2 , CH4 , CO and CO2 . The obtained parameters were listed in Table 5. All the correlation curves in Fig. 9 have good linearity above 0.97, and the resulting apparent activation energy E fell into a range of 10–30 kJ/mol. The activation energy represents the difficulty for forming the gas component. For H2 it has the largest activation energy and this justifies that it was more difficult to generate H2 in pyrolysis. In comparison, the formation of CO2 is obviously easier for it has the lowest activation energy. 4.2. For pyrolysis gas mixture

845

Fig. 12. Correlation of ln(dX/dt) and ln(1 − X) for pyrolysis gas mixture in MFBR.

reaction order n and reaction rate constant k(T) from this figure (i.e., the stage II) according to Eq. (2) were listed up also in Table 4. The reaction order for the pyrolysis gas mixture varied around 1.62, suggesting a good repeatability of the measurement in the MFBR. The reaction orders in Table 4 for both individual gas components and gas mixture clarify that the biomass pyrolysis reactions in the MFBR do not follow the first-order model, although this kind of model is generally proposed by the kinetic measurements in TG [2–5]. The apparent activation energy E and frequency factor A were also estimated for the pyrolysis gas mixture. Fig. 13 shows the Arrhenius plot, exhibiting a good linear fitting of ln(k(T)) and 1/T with a correlation coefficient above 0.99. The derived E and A are 11.77 kJ/mol and 1.45 s−1 , respectively. These two values, as discussed further below, are lower than many literature-reported values obtained mainly in TG [28,31–33] but close to those from the tests in a relatively large-size CFB pyrolyzer [29,30].

Fig. 11 shows the pyrolysis gas conversion calculated for the gas mixture. As it should be, the completion time of pyrolysis reduced with increasing temperature, and comparing to Fig. 7 for individual gas components the variation of the conversion curve with temperature appeared more regular in Fig. 11. This shows in fact a kind of compensative or coupling effect among the formation reactions for different individual gas components. For example, the slow formation of H2 is compensated by the quick formations of CO and CO2 to have thus the improved regularity of gas yield variation with the reaction temperature. Fig. 12 shows the correlation of ln(dX/dt) and ln(1 − X) for the pyrolysis gas mixture, and three reaction stages are similarly obvious as in Fig. 9 for the individual gas component. The derived

In order to clarify why the MFBR leads to the low values of E and A shown above, Table 5 compares such two parameters from a few literatures using different reactors and under different heating rates. In comparison with in TG, the tests of this work in MFBR, Lv et al. [29] in a large-size CFB reactor and Zabaniotou et al. [31] using a wire mesh reactor refer definitely to the quick heating conditions and the measurement at preset temperatures (isothermal approach). Their heating rates were above 1000 ◦ C/s for the fluidized bed reactors (this work and [29]) and 100–240 ◦ C/s for the wire mesh reactor. The resulting E and A were thus in the same

Fig. 11. Conversion based on pyrolysis gas mixture in MFBR.

Fig. 13. Kinetic parameters and linear fitting of ln(k(T)) and 1/T in MFBR.

4.3. Kinetic data comparison

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Table 5 Kinetic parameters measured in the MFBR and comparison with literature report. Method

Source

Fuel

This study

Heating rate

Gas



Beer lees

1000–10,000 C/s

Olive wood

1000–10,000 ◦ C/s

At given T (fast heating) Lv et al. [29]a b

Programmed heating (varied T)c a b c

Zabaniotou et al. [31]

Pine sawdust Cellulose

100–240 C/s

Wang et al. [32]

Sawdust

5–20 ◦ C/min

Sonobe et al. [33]

Rice husk corncob

5–20 ◦ C/min



H2 CH4 CO CO2 Mixture CO Mixture Weight loss

Weight loss

T [◦ C]

500–900

700 250–400 200–600 200–600

E [kJ/mol]

A [1/s]

28.25 12.49 12.36 10.91 11.77 24.45 15.12 17.90 11.14

7.92 1.47 1.60 1.32 1.45 4.81 0.71 862 99

160–200 120–200 120–250

4.5E5−4.5E13 E12−E15 E12−E19

In a large-size fluidized bed reactor. In an electrically heated mesh reactor. With commercial TG.

order, with E varying in 10–20 kJ/mol and A in 1–100 s−1 . The data of this work and that from Lv et al. were in particularly good consistence, supporting that both these studies used the same-type reactor (fluidized bed) and had the equal heating rate. The wire mesh reactor [31] resulted in slightly higher E and also the larger A, but they are in the same order with those from the fluidized bed. Thus, the higher E and A for the mesh reactor should be related to its lower heating rate (than in fluidized bed) and the reactor itself which suffered more inhibitions from the gas diffusion than in the fluidized bed reactors. The pyrolysis tests in TG have to be via programmed heating method, and the heating rate is generally below 50 ◦ C/min (usually 5–20 ◦ C/min), much lower than the preceding rates realized in the isothermal measurements. In Table 5, the reported E and A for the TG tests were distinctive high, with E in 120–250 kJ mol−1 and A in orders of 105 –1015 s−1 . Comparing to the other measurements in Table 5 at preset temperatures and with high heat rates of hundreds of ◦ C/s, we can suggest that the kinetic data of biomass pyrolysis be subject to serious influences of the heating rates and the measurement approach, which is either isothermal (at preset temperatures) or non-isothermal (programmed heating). While the isothermal approach at heating rates of hundreds of ◦ C/s lead to the activation energy E in 10–20 kJ/mol and the frequency factor A of 1–100 s−1 , the programmed heating at low rates of 10–20 ◦ C/min would result in much higher E and A which are possibly valued to about 200 kJ/mol and 105 –1015 s−1 , respectively. Table 5 clarifies also that both E and A compensatively vary to make small A correspond to low values of E. The activation energy represents essentially the difficulty to start a reaction, while the frequency factor A indicates the occurred effective collision of reactant molecules. When a lower E denotes a reaction that is easier to start and occur, less collision of reactant molecules should thus be entailed to allow a small A. For MFBR, its low activation energy and frequency factor demonstrate that the biomass pyrolysis is easier to occur than in TG. This is in consistence with the features of the MFBR that there are high-rate heating to fuel particles and minimized diffusion inhibition on the reaction. Furthermore, the tested biomass fuel sample is in micrometers and micro-grams to maintain the differential characteristics of the reaction. Consequently, the MFBR, in comparison with TG, would be a viable reactor that enables the isothermal differential analysis of gas–solid reactions, especially the fast reactions like pyrolysis for investigating the reaction characteristics and estimating the kinetics. Benefiting from its features of quick heating, minimized diffusion inhibition and differential isothermal conditions, the measured reaction kinetics in MFBR should be closer to the intrinsic chemical kinetics of the tested reaction, while the clarified reaction characteristics may reveal the true reaction mechanisms.

5. Conclusions The so-called micro-fluidized bed reactor (MFBR) was used to investigate the pyrolysis of beer lees. The reactor (20 mm in i.d.) allowed instantaneous feed of 10–50 mg fuel sample in ␮m at a preset temperature to enable the occurrence of the so-called isothermal differential reaction. For comparison the pyrolysis was also conducted in a micro-fixed bed reactor. It was shown that the pyrolysis in the MFBR finished in about 10 s at 800 ◦ C, indicating a quicker pyrolysis than in the literature reports using fluidized beds having diameters of tens of millimeters. The pyrolysis gas yield in the MFBR was much higher than that in the micro-fixed bed reactor. The time to start and end the release of pyrolysis gas was also distinctively different in the micro-fixed bed and fluidized bed. While the time shared obvious difference for gases H2 , CO, CO2 and CH4 in the fixed bed pyrolysis, there was little difference for the tests in the MFBR. The pyrolysis kinetics was analyzed on the basis of the pyrolysis gas releasing characteristics for both individual gas component and pyrolysis gas mixture. The estimated kinetic parameters included activation energy, frequency factor and reaction order. These parameters were different for different gas components, indicative of the different mechanisms involved in forming the different gas species. The overall pyrolysis kinetics based on formation of the pyrolysis gas mixture was analyzed in terms of the shrinking core model, leading to a reaction order of 1.62, an activation energy of 11.77 kJ/mol and a frequency factor of 1.45 s−1 , respectively. Against the measurements in TG and fixed bed reactors, the values of these kinetic parameters were obviously lower, indicating the quick pyrolysis reaction in the MFBR. A consequent comparison on the kinetic data of biomass pyrolysis obtained in different reactors revealed that the values of activation energy and frequency factor are subject to the heating rate and the test approach, either isothermal at present temperatures or non-isothermal via programmed heating. The isothermal test with heating rate of hundreds of K/s leads to low activation energy and frequency factor in order of tens to hundreds, whereas the non-isothermal test in TG may result in activation energy larger by 10–30 times and frequency factor high as 105 –1015 . These demonstrate that the MFBR, which minimizes the gas diffusion inhibition, realizing quick heating and offering isothermal differential characteristics, enabled the isothermal differential analysis of gas–solid reactions, especially the fast reactions like pyrolysis for investigating the reaction characteristics and estimating the kinetics. Acknowledgements Financial support of National Natural Science Foundation of China (20606034, 20776144), National High-Tech Research

J. Yu et al. / Chemical Engineering Journal 168 (2011) 839–847

and Development Program (863 program, No. 2009AA02Z209) and Chinese Academy of Sciences (Y2005014, GJHZ200824, 0829011198), are greatly appreciated. Acknowledgements would be also extended to Ms. Jianhong Zhu for their helps in experiments. References [1] G. Grassi, G. Gosse, G. Dos-Santos, Biomass for Energy and Industry, Elsevier Applied Science, London, 1990. [2] M.G. GrØnli, G. Varhegyi, C. Di Blasi, Thermogravimetric analysis and devolatilization kinetics of wood, Industrial Engineering Chemistry Research 41 (2002) 4201–4208. [3] P.T. Williams, S. Besler, The pyrolysis of rice husks in a thermo gravimetric analyzer and static batch reactor, Fuel 72 (1993) 151–159. [4] H. Teng, H.C. Lin, J.A. Ho, Thermogravimetric analysis on global mass loss kinetics of rice hull pyrolysis, Industrial Engineering Chemistry Research 36 (1997) 3974–3977. [5] J. Reina, E. Velo, L. Puigjaner, Thermogravimetric study of the pyrolysis of waste wood, Thermochimica Acta 320 (1998) 161–167. [6] T. Fisher, M. Hajaligol, B. Waymack, D. Kellogg, Pyrolysis behavior and kinetics of biomass derived materials, Journal of Analytical Applied Pyrolysis 62 (2002) 331–349. [7] P. Stolarek, S. Ledakowicz, Pyrolysis kinetics of chitin by non-isothermal thermogravimetry, Thermochimica Acta 433 (2005) 200–208. [8] A.R. Fraga, A.F. Gaines, R. Kandiyoti, Characterization of biomass pyrolysis tars produced in the relative absence of extraparticle secondary reactions, Fuel 70 (1991) 803–809. [9] A. Zabaniotou, T. Damartzis, Modelling the intra-particle transport phenomena and chemical reactions of olive kernel fast pyrolysis, Journal of Analytical Applied Pyrolysis 80 (2007) 187–194. [10] S. Baumlin, F. Broust, M. Ferrer, N. Meunie, E. Marty, J. Lédé, The continuous self stirred tank reactor: measurement of the cracking kinetics of biomass pyrolysis vapours, Chemical Engineering Science 60 (2005) 41–55. [11] J.J. Saastamoinen, Simplified model for calculation of devolatilization in fluidized beds, Fuel 85 (2006) 2388–2395. [12] Z.Y. Luo, S.R. Wang, K.F. Cen, A model of wood flash pyrolysis in fluidized bed reactor, Renewable Energy 30 (2005) 377–392. [13] M. Ayllón, M. Aznar, J.L. Sánchez, G. Gea, J. Arauzo, Influence of temperature and heating rate on the fixed bed pyrolysis of meat and bone meal, Chemical Engineering Science 121 (2006) 85–96. [14] J.J. Manyà, J. Arauzo, An alternative kinetic approach to describe the isothermal pyrolysis of micro-particles of sugar cane bagasse, Chemical Engineering Journal 139 (2008) 549–561. [15] J. Yu, Z. Liu, J.H. Zhu, L. Dong, G.W. Xu, Kinetics and mechanism of solid reactions in a micro fluidized bed reactor, AIChE Journal 56 (2010) 2905–2912.

847

[16] J.H. Hu, X.H. Liu, Z. Liu, Y. Wang, D.G. Jiang, G.W. Xu, Characterization of biomass decoupling gasification in a laboratory two-stage fixed bed reactor, in: International Symposium on Gasification and Application, Shanghai, 2008. [17] X.H. Liu, G.W. Xu, S.Q. Gao, Micro fluidized beds: wall effect and operability, Chemical Engineering Journal 137 (2008) 302–307. [18] K. Matsuoka, T. Shinbori, K. Kuramoto, T. Nanba, A. Morita, H. Hatano, Y. Suzuki, Mechanism of woody biomass pyrolysis and gasification in a fluidized bed of porous alumina particles, Energy Fuels 20 (2006) 1315–1320. [19] J.F. González, J.M. Encinar, J.L. Canito, E. Sabio, M. Chacón, Pyrolysis of cherry stones: energy uses of the different fractions and kinetic study, Journal of Analytical Applied Pyrolysis 67 (2003) 165–190. [20] P.T. Williams, S. Besler, The influence of temperature and heating rate on the slow pyrolysis of biomass, Renewable Energy 7 (1996) 233–250. [21] C.D. Blasi, G. Signorelli, C.D. Russo, G. Rea, Product distribution from pyrolysis of wood and agricultural residues, Industrial Engineering Chemistry Research 38 (1999) 2216–2224. [22] M. Stenseng, Pyrolysis and combustion of biomass, PhD Thesis, DTU, Technical University of Denmark, 2001. [23] R.R. Bassilakis, M. Carangelo, M.A. Wójtowicz, TG-FTIR analysis of biomass pyrolysis, Fuel 80 (2001) 1765–1786. [24] H.P. Yang, R. Yan, H.P. Chen, C.G. Zheng, D.H. Lee, D.T. Liang, In-depth investigation of biomass pyrolysis based on three major components: hemicellulose, cellulose and lignin, Energy Fuels 20 (2006) 388–393. [25] C.D Blasi, Modeling chemical and physical processes of wood and biomass pyrolysis, Progress Energy Combustion Science 34 (2008) 47–90. [26] G.W. Xu, T. Murakami, T. Suda, T. Matsuzawa, H. Tani, Gasification of coffee grounds in dual fluidized bed: performance evaluation and parametric investigation, Energy Fuels 20 (2006) 2695–2704. [27] F. Thurner, U. Mann, Kinetic investigation of wood pyrolysis, Industrial & Engineering Chemistry Process Design and Development 20 (1981) 482–488. [28] E. Ranzi, A. Cuoci, T. Faravelli, A. Frassoldati, G. Migliavacca, S. Pierucci, S. Sommariva, Chemical kinetics of biomass pyrolysis, Energy Fuels 22 (2008) 4292–4300. [29] P.M. Lv, J. Chang, T.J. Wang, C.Z. Wu, N. Tsubaki, A kinetic study on biomass fast catalytic pyrolysis, Energy Fuels 18 (2004) 1865–1869. [30] X.W. Dai, C.Z. Wu, H.B. Li, Y. Chen, The fast pyrolysis of biomass in CFB reactor, Energy Fuels 14 (2000) 552–557. [31] A.A. Zabaniotou, G. Kalogiannis, E. Kappas, A.J. Karabelas, Olive residues (cuttings and kernels) rapid pyrolysis product yields and kinetics, Biomass and Bioenergy 18 (2000) 411–420. [32] G. Wang, W. Li, B. Li, H. Chen, TG study on pyrolysis of biomass and its three components under syngas, Fuel 87 (2008) 552–558. [33] T. Sonobe, N. Worasuwannarak, Kinetic analyses of biomass pyrolysis using the distributed activation energy model, Fuel 87 (2008) 414–421.