Ind. Eng. Chem. Res. 2006, 45, 3791-3799
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Pyrolysis and Combustion Characteristics of Biomass and Waste-Derived Feedstock George Skodras,†,‡ Panagiotis Grammelis,*,‡,§ Panagiotis Basinas,† Emmanuel Kakaras,‡,§ and George Sakellaropoulos† Chemical Process Engineering Laboratory, Department of Chemical Engineering, Aristotle UniVersity of Thessaloniki, Thessaloniki, Greece, Institute for Solid Fuels Technology and Applications/Centre for Research & Technology Hellas, Ptolemais, Greece, and Laboratory of Steam Boilers and Thermal Plants, Thermal Engineering Section, Mechanical Engineering Department, National Technical UniVersity of Athens, 9 Heroon Polytechniou AVenue, 15780 Zografou, Greece
The trend for material and energy recovery from wastes along with the need to reduce greenhouse gases has led to an increased interest in the thermal exploitation of biomass and/or wastes. In this work, the pyrolysis and combustion behavior of 10 biomass and waste materials was investigated in a nonisothermal thermogravimetric analyzer (TA Q600) at ambient pressure and 150-250-µm particle size. The effect of the heating rate (5, 20, 50, and 100 °C/min) was also considered. The independent parallel first-order reaction model was elaborated for the kinetic analysis of the pyrolysis results. The thermal degradation of the biomass/ waste samples was modeled assuming three or four parallel reactions. At increased heating rates, enhanced pyrolysis rates were achieved. As a result, a slight decrease in total weight loss was observed, accompanied by a systematic increase in pyrolysis starting temperature and an almost linear increase in maximum pyrolysis rate from 5% to 90%/min. Increased combustion reactivity was found for olive kernel and willow, followed by forest residue. The catalytic effect of mineral matter on char oxidation was pronounced in the MBM (meat and bone meal) sample, leading to a reaction rate decrease and shifting the DTG curve to lower temperatures between 300 and 400 °C. Introduction The need for energy recovery from renewable sources along with the necessity for emissions reductions have resulted in increased interest in the thermal conversion of biomass and/or wastes. Combustion constitutes one of the most important thermal treatment methods for biomasses and/or wastes. It combines the anticipation of replacing the landfilling option along with energy recovery. Thus, the factors that affect the combustion procedure should be well understood and studied in detail, toward the design and effective performance of industrial applications. The effect of mineral matter content in combustion and pyrolysis processes has also been investigated and identified as one of the key research areas.1 Numerous separate studies have dealt with pyrolysis of biomass and lignocellulosic materials, and other researchers have investigated the pyrolysis of waste components. Madorsky et al., Kilzer and Broido, and Chaterjje and Conrad set the basis of the modern kinetic models.2 Heikkinen et al. studied the devolatilization behavior of about 50 different wastes. To calculate the devolatilization rates of the samples, they assumed that the thermal degradation curve is obtained as a sum of the contributions of the corresponding pseudocomponents and found that this assumption holds for cellulosic samples.3 Many different mechanisms have been considered, for instance, the model proposed by Manya et al.,4 who studied waste wood and sugarcane bagasse samples for kinetic evaluations. Waste wood pyrolysis was modeled assuming three independent parallel * To whom correspondence should be addressed. Tel.: +302107722865. Fax: +30-2107723663. E-mail:
[email protected]. † Aristotle University of Thessaloniki, Thessaloniki, Greece. ‡ Institute for Solid Fuels Technology and Applications/Centre for Research & Technology Hellas. § National Technical University of Athens.
reactions, corresponding to the decomposition of three pseudocomponents: linked hemicellulose, cellulose, and lignin. Along the same lines, Caballero2 tested two biomass samples including olive kernel and almond shell. He found that, with a model involving three independent parallel reactions, the agreement between calculated and experimental data was excellent. More recently, Gronli et al.5 investigated the devolatilization behavior of several hardwoods and softwoods. They found that the devolatilization dynamics of the wood species of the study could be described well by a simple model consisting of five parallel first-order reactions for the amounts of the volatile fractions associated with the two extractive components. As Fisher et al.6 and Gronli et al.5 report, all of these derived kinetic parameters depend on the specific pyrolysis conditions, including the temperature, the heating rate, the pressure, the particle size, the ambient gas environment, and the presence of ash or mineral matter deposits. Therefore, the presence of several components and the catalytic role of the inorganic matter affect the kinetic parameters. In the past two decades, extensive studies have been performed in this field of investigation by many researchers. Raveendran et al.7 examined the mineral matter of various biomass samples and reported that their main elements are Si, Ca, K, Na, and Mg, followed in percentages by S, P, Fe, Mn, and Al. Serious research efforts have also been performed on the combustion procedure, indicating that the presence of oxygen causes many complexities. Bilbao et al.8 studied the thermal decomposition of cellulose and pine saw dust in an oxidative atmosphere and found that the degradation of the material at low temperatures causes the occurrence of gas-phase reactions between the released volatiles and oxygen and promotes the combustion of the char generated in the early stages of the solid degradation. Along these lines, Conesa et al.9 supported the idea that a later decomposition stage occurs only when oxygen is
10.1021/ie060107g CCC: $33.50 © 2006 American Chemical Society Published on Web 05/02/2006
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Table 1. Proximate and Ultimate Analyses of the Selected Fuels sample olive kernel almond shell forest residue MDF saw dust waste wood willow demolition wood straw MBM demin MBM a
proximate analysis (wt %, as received) moisture VMa FCb ash 18.1 9.7 21.3 6.5 14.3 5.63 11.3 8.6 7.9 1.35 0.52
60.8 66.9 63.7 74.4 73.3 69.53 71.47 70.69 58.54 79.66 79.83
18.5 20 13.7 17.9 11.96 16.08 16.1 18.8 15.8 8.61 19.36
2.6 3.36 1.2 1.1 0.44 8.76 1.14 1.92 17.74 10.38 0.29
C 51.6 49.6 51 47 51 45.99 44.7 44.5 36.4 55.67 52.87
ultimate analysis (wt % db) H N S 8.5 6.4 7.9 6.4 7.9 5.67 5.7 5.6 4.8 8.03 7.8
1.08 0.6 0.3 4.6 0.3 3.82 0.2 1.1 0.9 7.15 7.34
0 0 0 0 0 0.05 0.03 0.09 0.29 0.05 0.79
Oc
C/H ratio
gross H value (MJ/kg)
38.82 43.4 40.8 42 40.8 35.44 48.21 46.52 37.03 29.1 31.2
0.506 0.646 0.538 0.612 0.538 0.676 0.653 0.662 0.632 0.578 0.565
29.86 26.21 28.82 25.29 28.82 23.91 16.97 17.87 14.88 30.64 29.42
Volatile matter. b Fixed carbon. c By subtraction
present, which was maintained also by Zheng et al.,10 who extensively investigated the combustion procedure. Because alternative fuels, i.e., biomass, wastes, etc., are currently of great importance, it is vital to understand deeply their behavior under pyrolysis and combustion. However, sufficient data are not available, particularly for nonconventional fuels such as MBM (meat and bone meal) and wastes. To cover this need, in this work, the pyrolysis and combustion behaviors of agricultural residues, wood-processing byproducts, straw, and MBM are examined by thermogravimetry. The behaviors of the biomass/waste components in inert and oxidative atmospheres are compared. Kinetic parameters are calculated using a model of independent parallel first-order reactions, and the pyrolytic behaviors at the various heating rates are simulated according to the determined parameters. The kinetic constants such as the activation energies and preexponential factors calculated for both pyrolysis and char combustion could be useful for studying the processes taking place in combustors. Incorporating the obtained kinetic parameters in detailed computational codes contributes to the simulation of the real processes, allowing for the calculation of burn-out times and related parameters that are involved in such large systems.11 The effect of mineral matter present in biomass and waste and the role of feedstock properties in pyrolysis are also examined. Material and Method Materials. The materials tested include two agricultural residues, referred to as almond shell and olive kernel, and six wood-processing byproducts denoted MDF, saw dust, willow, waste wood, forest residue, and demolition wood. Meat and bone meal and straw were also included in the test matrix. The initial samples were milled and sieved, and the selected particle size fraction was in the range of 150-250 µm. Prior to the thermogravimetric experiments, the samples were dried in an oven at 105 °C in N2 atmosphere for 3 h. To investigate the influence of mineral matter on the thermal degradation of MBM, this specific sample was washed with three different acid solutions (5 N HCl, 22 N HF, and 12 N HCl). Eighteen grams of sample was added to 120 mL of each acid, and the mixtures were stirred for 1 h at 25 ( 2 °C. The samples were then washed with distilled water, filtered, and dried. The selected fuels were subjected to proximate analysis according to the standard ASTM D 3172-89 method. Ultimate analyses for all samples including determinations of calorific values were carried out in a Flash 1112 Series EA Thermo Finnigan CHNS elemental analyzer. Proximate and ultimate analysis results are presented in Table 1. The analysis of heavy metals in the ash sample was performed by inductively coupled plasma-atomic emission spectroscopy (ICP-AES).
Thermogravimetric tests were performed in a TA Instruments Q600 simultaneous TGA-DSC apparatus. The weight precision of the instrument is 0.1 µg. Small samples, about 10 or occasionally 20 mg, were placed in an open alumina sample pan, to reduce the effects of eventual side reactions and heatand mass-transfer limitations. High-purity helium and respal air (80/20 in N2/O2) were used at a constant flow rate of 100 mL/ min. Before the heating program was initiated, the system was purged for 10 min at 400 mL/min to ensure that the desired environment was established. The weight loss and rate of weight loss were continuously recorded during a linear temperature increase from 30 to 1000 °C. Devolatilization tests were conducted at three and, in some cases, four heating rates, i.e., 5, 20, 50, and 100 °C/min. Both pyrolysis and combustion experiments at the heating rate of 20 °C/min were replicated, at least twice, to determine their reproducibility, which was found to be very good. Kinetic Modeling. The pyrolysis of biomass and/or waste is a complex phenomenon and proceeds through multiple parallel or even competitive reactions. Thus, it is not possible to describe the entire process with a single reaction. In contrast, DTG curves obtained upon pyrolysis of biomass and waste samples can essentially be described by a relatively simple model of independent parallel reactions. More specifically, it is assumed that each component reacts independently, so that the thermal behavior of a sample can be described as the sum of the behaviors of its individual components. This approach has been successfully applied by many authors in earlier studies.4,5,12-17 In this work, the pyrolysis of biomass and waste samples was modeled by assuming three or four independent parallel firstorder reactions. The individual conversion rates for N reactions are described by
dai ) Ai‚exp(-Ei/RT)‚f(ai), i ) 1, ..., N dt
(1)
where Ai and Ei are the preexponential factor and activation energy, respectively, of component i; R is the gas constant; T is the temperature; and ai is the separate conversion of component i, which is expressed as
ai )
m0,i - mi m0,i - mchar,i
(2)
where m0,i, mi, and mchar,i are the initial dry sample mass, the actual sample mass, and the final char yield, respectively, of component i. Assuming a first-order reaction, one can write
f(a) ) 1 - a
(3)
Ind. Eng. Chem. Res., Vol. 45, No. 11, 2006 3793
Figure 1. Weight loss and rate of weight loss as a function of temperature for several biomass samples.
The overall conversion rate is described by
-
dm
)
dt
dai
∑i ci dt ,
Results and Discussion
i ) 1, ..., N
(4)
The contribution of each partial process to the overall weight loss is expressed by the coefficient ci, which essentially represents the fraction of volatiles produced by the ith component:
ci ) m0,i - mchar,i
(5)
The minimization of the objective function was used to identify the optimum kinetic parameters, as follows: N
OFDTG )
∑ i)1
[( ) ( ) ] dm dt
exp
-
i
dm dt
calc 2
(6)
i
The estimation of the best-fit kinetic parameters was achieved through the deviation between the experimental and calculated DTG curves, as a percentage of the maximum experimental value (dm/dt):
DEV1 (% ) )
xOFDTG/(Z - M) × 100
max[(-dm/dt)calc]
(7)
where M is the number of the model parameters (Ai, Ei, and ci) and Z is the number of the measured data points. Also, the deviation between the observed and calculated char fractions can be used:
[
DEV2 ) abs
]
(mchar)exp - (mchar)calc (mchar)exp
× 100
(8)
where (mchar)exp and (mchar)calc are the experimental and calculated values, respectively, of the residual mass. As already reported, the latter arise from computed values of the optimized preexponential factor and activation energy.
Pyrolysis of Samples. Several characteristics of the thermal degradation of the samples were used to evaluate their behavior, such as the initial pyrolysis temperature, maximum pyrolysis rate and corresponding temperature, total conversion, and contribution of various temperature intervals to the total weight loss. The weight loss and the rate of weight loss are presented in Figures 1 and 2 for wood-based biomasses and waste samples, respectively. From the TG curves, it can be seen that pyrolysis starts at about 200 °C and is essentially completed at 500 °C. The DTG curve of almost every biomass and waste sample presents a narrow peak between 330 and 375 °C, which is similar to the results found by other authors.3 As an exception to this behavior, the MBM sample exhibits a maximum pyrolysis rate at 410 °C. Taking into account the inverse relationship between the reactivity and the temperature corresponding to peak height, olive kernel seems to be the most reactive among the samples. In contrast, straw and MBM present the lowest peak heights and the highest peak temperatures. The main devolatilization occurs between 250 and 400 °C in all test cases except for MBM, where the main degradation stage is completed at approximately 450 °C. Significant variations of the total weight loss are observed, which are approximately between 65% and 85% and are in accordance with the results of previous studies.18 The derivatives of the weight loss for the pyrolysis of olive kernel at specific heating rates (5, 20, 50, and 100 °C/min) are presented in Figure 3. As is clearly illustrated by the DTG curves, pyrolysis is completed in approximately the same temperature range for all heating rates. At higher heating rates, a slight increase in the char yield was observed in previous studies. This has been attributed to competitive reactions that are affected by the increased heating rate.16 An increase of the residual char between 1.3% and 5.7% is obtained, which is so small that it can be assumed to be essentially unaffected by the heating rate. Figure 4 clearly shows that an almost linear increase in maximum pyrolysis rate occurs. Sample particles are heated faster at increased heating rates, resulting in significantly higher DTG peaks that are shifted to enhanced temperatures. At even higher heating rates, the temperature increases in shorter time intervals. This can be ascribed not only to the effect of the heat-
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Figure 2. Weight loss and rate of weight loss as a function of temperature for several biomass and waste samples.
Figure 3. Effect of heating rate on the devolatilization of olive kernel.
transfer phenomena occurring during the different heating histories, but also to the temperature lag of the sample. The sample presents a delay in reaching this temperature increase because of the heat-transfer resistance presented by its particles. As a consequence, the DTG curves are shifted to higher temperatures. Kinetics. Detailed reaction mechanisms are available for the kinetic evaluation of the pyrolysis of biomass and/or wastes. It is also adequate to take into account only the basic characteristics of the degradation process with a simplified mechanism. A relatively simple approximation for determining the kinetics of the thermal decomposition consists of assuming that TG/DTG curves can be divided into three or more zones, each of which can be considered independently. Lignocellulosic materials are considered to devolatilize through the degradation of their major constituents, such as cellulose, hemicellulose, and lignin. The two different weight loss regions observed in wood pyrolysis are identified as a combination of the devolatilizations of hemicellulose and cellulose. More accurately, the peak at the lower temperatures is attributed to the degradation of hemicellulose, and the second peak corresponds to the degradation of cellulose, or vice versa. Lignin is decomposed throughout the entire pyrolysis temperature range. Therefore, biomass samples
can be modeled by assuming a three-step mechanism for each pseudocomponent. The first pseudocomponent is hemicellulose; the second, cellulose; and the third, lignin. A fourth reaction is necessary to simulate the decomposition of hemicellulose. Because the three components are devolatilized in different temperature ranges, several energy supplements are necessary for the activation of the corresponding reactions. Also the preexponential factor is highly dependent on the temperature, and thus the differences among hemicellulose, cellulose, and lignin are expected to be significant. Previous studies15-17 of the independent thermal degradations of the three main biomass components established the existence of marked differences. As Heikkinen et al.3 proposed, lignin and xylan start to decompose at lower temperatures than cellulose. Lignin decomposes over a wide temperature range with a long tailing section. In the literature, data are reported for xylan rather than hemicellulose. Because many of the significant errors in kinetic estimations are derived from this assumption, hemicellulose was employed to evaluate the kinetics of the biomass samples. Figure 5 shows the pathway for willow pyrolysis that was modeled by assuming four independent parallel reactions and using the DTG curve. The calculated kinetic parameters are listed in Table 2. MBM and four biomass samples were modeled
Ind. Eng. Chem. Res., Vol. 45, No. 11, 2006 3795
Figure 4. Maximum pyrolysis rate of olive kernel and temperature at maximum pyrolysis rate as a function of the heating rate.
Figure 5. Modeling of the pyrolysis of willow using four independent parallel reactions.
by assuming four reactions, whereas the rest of the samples were efficiently modeled through three pseudocomponents. It is worth mentioning that hemicellulose contributes in higher percentages when two hemicellulose peaks are used to model accurately the thermal degradation of samples. On the other hand, cellulose is higher in samples where three independent parallel reactions are used, and lignin presents the lowest values. The average value of the activation energy for hemicellulose decomposition in biomass is 103.7 kJ/mol. This is in accordance but still lower than the values calculated by Gronli et al.17 and Sorum et al.,12 which are 133.5 and 110.3 kJ/mol, respectively. Correspondingly, the first reaction for meat and bone meal presents a lower value (57.9 kJ/mol). The activation energy for the thermal degradation of lignin was calculated to be 53 kJ/ mol for the lignocellulosic materials and 31.7 kJ/mol for MBM. As found from the kinetic attributions, the preexponential factor values depend on the heating rate. An increase of the heating rate results in increased A values, as was also shown by Bilbao et al.8
The calculated lignin content was evaluated with respect to the fixed carbon content. Previous studies on charcoal production from biomass19-21 suggest that a correlation between lignin and fixed carbon content exists. Figure 6 shows that relationship for the biomass samples tested. It is evident that the lignin and fixed carbon contents are proportional in all biomass samples. Antal et al.20 proposed a statistical t-test to ascertain the calculated trend of the substrates, suggesting that a p value lower than 0.05 would be significant for the existence of a trend. The calculated values for R2 and p, namely, 0.8 and 1.6 × 10-6, respectively, are within the ranges, reflecting a linear correlation between the fixed carbon and lignin contents. Experimental conditions such as the heating rate and sample size affect the kinetic parameters. For this reason, a number of different activation energies and preexponential factors have been calculated in previous studies. It is widely accepted that an increase in particle size results in a slight rise of the maximum devolatilization rate and the temperature at which it occurs. The results of this study refer to low hearing rates, on the order of
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Table 2. Calculated Kinetic Parameters for the Pyrolysis of Biomass Samples at Heating Rate 20 °C/min hemicellulose 1 sample olive kernel
hemicellulose 2
A (1/min)
E (kJ/mol)
c (%)
1.7 × 1010
108.9
9.5
-
24.3
3.1 ×
9.1
-
8
4.3 ×
25.3
-
26.3
-
14.9
3.9 ×
1015
6.9
3.8 ×
1014
forest residue 1.9 ×
1011
128.5
A (1/min)
E (kJ/mol)
A (1/min)
E (kJ/mol)
-
1.6 × 1011
130.8
65.1
6.7 ×
106
-
1.1 ×
107
24.7
2.15 ×
-
-
3.3 ×
103
-
-
1.7 ×
1018
47.9
1.28 ×
63.2
1.1 ×
1010
-
2.8 ×
1015
20
third reaction 2.4 × 1014 188.1
1015
191.2
almond shell
9.3 ×
106
MDF
8.5 ×
108
saw dust
2.6 ×
1011
waste wood
6.2 ×
1010
straw
1.2 ×
1012
willow
2.1 ×
1013
demol wood
3.5 ×
108
99.5
34.3
-
MBM
first reaction 5.6 × 104 57.9
20.7
second reaction 3.7 × 1012 146.9
75.4 96.9 131.1 124.3 128 144.4
1011
cellulose
132.7
183.6 179.9 -
c (%)
20 °C/min. At elevated heating rates, e.g., 100 °C/min, the effect of particle size on devolatilization is more pronounced. The greater the particle size, the higher the effect of the heating rate on the pyrolysis. Because the average particle sizes investigated are within the range of 150-250 µm, use of finer particles, e.g.,
