Thermogravimetric analysis and kinetic study of poplar wood pyrolysis
Poplar cultivated with Short Rotation Forestry (SRF) technique could be an important source of biomass. This dedicated crop could be produced to obtain solid biofuel transformed through combustion, pyrolysis or gasification into heat and power in CHP plants. In this work a kinetic study of the slow pyrolysis process of poplar wood (populus L.) is investigated with a thermogravimetric analyzer. A comparison of selected non-isothermal methods for analyzing solid-state kinetics data is presented. The weight loss was measured by TGA in nitrogen atmosphere. The samples were heated over a range of temperature from 298K to 973K with four different heating rates of 2, 5, 10, 15Kmin−1. The results obtained from thermal decomposition process indicate that there are three main stages such as dehydration, active and passive pyrolysis. In the DTG thermograms the temperature peaks at maximum weight loss rate changed with increasing heating rate. The activation energy and pre-exponential factor obtained by Kissinger method are 153.92kJmol−1 and 2.14×1012min−1, while, the same average parameters calculated from FWO and KAS methods are 158.58 and 157.27kJmol−1 and 7.96×1013 and 1.69×1013min−1, respectively. The results obtained from the first method represented actual values of kinetic parameters which are the same for the whole pyrolysis process, while the KAS and FWO methods presented apparent values of kinetic parameters, because they are the sum of the parameters of the physical processes and chemical reaction that occur simultaneously during pyrolysis. Experimental results showed that values of kinetic parameters obtained from three different methods are in good agreement, but KAS and FWO methods are more efficient in the description of the degradation mechanism of solid-state reactions. The devolatilization process was mathematically described by first order single reaction. The results of the kinetic study can be used in modeling devolatilization process through computational fluid dynamics (CFDs) to simulate mass and energy balances.
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Volume (Year): 97 (2012)
Issue (Month): C ()
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