Ind. Eng. Chem. Res. 2004, 43, 901-906
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Further Applications of a Revisited Summative Model for Kinetics of Biomass Pyrolysis Claudia J. Go´ mez, Joan J. Manya` , Enrique Velo, and Luis Puigjaner* Department of Chemical Engineering, Universitat Polite` cnica de Catalunya, ETSEIB, Avenida Diagonal 647, E-08028 Barcelona, Spain
The thermal decomposition of wood chips (pine and beech samples) and an energy crop (thistle) is studied using thermogravimetric analysis. Assuming the addition of three independent parallel reactions, corresponding to three pseudocomponents linked to the hemicellulose, cellulose, and lignin, the weight loss associated with the pyrolysis process is simulated. The kinetic constants are based on the assumption of an irreversible, single-step, first-order process for each pseudocomponent, except for the third pseudocomponent, for which a kinetic model of third order is applied. The weight loss evolution simulated by means of the summative model has been compared with the experimental data. This summative nth-order model has been able to reproduce the experimental results satisfactorily and has evidenced the influence of the biomass composition on the pyrolysis process. Introduction In practical terms, the description of biomass pyrolysis kinetics by rationally based models that do not represent the detailed physicochemical mechanism of the process but predict the overall yield might be extremely useful. According to this, the mechanisms of global weight loss based on the thermal decomposition of pure cellulose, by means of an irreversible, singlestep, and first-order reaction, present promising results.1,2 These mechanisms have been applied to the primary decomposition of each main polymeric biomass component (cellulose, hemicellulose, and lignin) at a low heating rate, and the total weight loss associated with the pyrolysis process has been simulated assuming the addition of three independent parallel devolatilization reactions.3-8 Results show a good agreement between simulated and experimental data. However, the description of the hemicellulose and lignin pyrolysis still needs further investigation. Kinetic parameters of these polymer decompositions by first-order reactions are excessively contradictory between data published by different authors and could not be modeled with acceptable errors by means of simple reactions.3,4,9-11 While most work has been carried out on wood, a few pyrolysis studies using energy crops have been reported.12-14 These studies are now mainly focused on the improvement of the possibilities of commercialization considering their economic and energy potential. The specific aim of this work is to evaluate, at low heating rates and dynamic regime, the predictive capacity of the revisited summative model previously proposed by this laboratory9 in the thermal decomposition of a softwood (pine), a hardwood (beech), and an energy crop sample (thistle). The model contemplates three biomass pseudocomponents (a fraction of each main component that decomposes at a certain temperature range) through application of the addition principle2 and is based on the assumption of a one-stage process for each pseudocomponent, following the Arrhenius law and * To whom correspondence should be addressed. Tel.: 343-4016678. Fax: 34-3-4017150. E-mail:
[email protected].
assuming first-order reaction, except for the third one (linked to lignin), for which an approach of third order is used. This model was previously applied for the kinetic evaluation of sugarcane bagasse and waste wood9 samples coming from a heterogeneous source and with a considerable amount of mineral matter and extractives (nonstructural components). Despite this, predictions from the model proposed reproduced correctly the experimental TG curves. These results have justified the interest in applying the same model to describe the global mass loss during pyrolysis of other biomasses of practical interest and classical composition (like pine and beech). An experimental study using thermogravimetric analysis has been carried out in order to characterize the kinetics of the slow pyrolysis of beech, pine wood, and thistle samples. A water-wash procedure coupled with a partial extractive removal has allowed one to identify the influence of mineral matter and extractives on weight loss dynamics by comparison with samples after treatment. Two parameter estimation methodologies have been coupled in a simulation tool to obtain the best-fit kinetic parameters for the global model. Experimental Section The wood samples under study (pine and beech) were taken from Barcelona’s carpentry residuals. The thistle (Cynara cardunculus) came from a specialized crop, developed for investigation in the Spanish province of Soria. The selected fraction of particle size was in the range of -0.5 to +0.1 mm in all cases. All biomasses under study were washed with hot water at 80 °C during 2 h, according to the procedure suggested by several authors.2,4 All resulting biomass samples were extracted with ethyl alcohol, for about 24 h in a Soxhlet apparatus, following a standard methodology for the determination of extractives in biomass.10 The proximate analysis, elemental composition, and extractive contents are shown in Table 1. The thermogravimetric equipment was the same as that previously used by this laboratory for kinetic analysis of sugarcane bagasse and waste wood samples.9
10.1021/ie030621b CCC: $27.50 © 2004 American Chemical Society Published on Web 01/20/2004
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Ind. Eng. Chem. Res., Vol. 43, No. 4, 2004
Table 1. Biomass Sample Analysis
Table 2. Kinetic Study of Avicel Cellulose Pyrolysis at 5 K/min
proximate (% by weight) biomass
moisture
volatile matter
fixed carbon
ash
untreated pine washed pine untreated beech washed beech untreated thistle washed thistle
7.53 3.29 7.03 2.35 11.10 2.43
71.63 77.98 73.62 79.05 63.39 70.79
19.84 18.14 19.11 18.41 17.41 22.01
1.00 0.60 0.24 0.20 8.10 4.77
ultimate (% by weight; dry ash-free samples) biomass
C
H
N
O
untreated pine washed pine untreated beech washed beech untreated thistle washed thistle
46.56 43.37 45.68 47.43 40.45 45.04
6.48 6.68 6.52 6.55 6.07 6.70
