Kinetic Behavior of Torrefied Biomass in an Oxidative Environment

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• 作者：Dhruv Tapasvi ; Roger Khalil ; G谩bor V谩rhegyi ; 脴yvind Skreiberg ; Khanh-Quang Tran ; Morten Gr酶nli
• 刊名：Energy & Fuels
• 出版年：2013
• 出版时间：February 21, 2013
• 年：2013
• 卷：27
• 期：2
• 页码：1050-1060
• 全文大小：534K
• 年卷期：v.27,no.2(February 21, 2013)
• ISSN：1520-5029

文摘

The combustion of four torrefied wood samples and their feedstocks (birch and spruce) was studied at slow heating programs, under well-defined conditions by thermogravimetry (TGA). Particularly low sample masses were employed to avoid the self-heating of the samples because of the huge reaction heat of the combustion. Linear, modulated, and constant reaction rate (CRR) temperature programs were employed in the TGA experiments in gas flows of 5 and 20% O₂. In this way, the kinetics was based on a wide range of experimental conditions. The ratio of the highest and lowest peak maxima was around 50 in the experiments used for the kinetic evaluation. A recent kinetic model by V谩rhegyi et al. (V谩rhegyi, G.; Sebesty茅n, Z.; Cz茅g茅ny, Z.; Lezsovits, F.; K枚ncz枚l, S. Energy Fuels 2012, 26, 1323鈭?335) was employed with modifications. This model consists of two devolatilization reactions and a successive char burnoff reaction. The cellulose decomposition in the presence of oxygen has a self-accelerating (autocatalytic) kinetics. The decomposition of the non-cellulosic parts of the biomass was described by a distributed activation model. The char burnoff was approximated by power-law (n-order) kinetics. Each of these reactions has its own dependence upon the oxygen concentration that was expressed by power-law kinetics too. The complexity of the applied model reflects the complexity of the studied materials. The model contained 15 unknown parameters for a given biomass. Part of these parameters could be assumed common for the six samples without a substantial worsening of the fit quality. This approach increased the average experimental information for an unknown parameter by a factor of 2 and revealed the similarities in the behavior of the different samples.