Wood devolatilization

Analysis of Chemical and Physical Processes During Devolatilization of a Single, Large Particle of Wood... 

Models of wood pyrolysis and combustion have been developed to aid in fire safety and have treated various physical and chemical phenomena (3-9). Several studies have determined volatiles composition from rapid pyrolysis of small particles (10-13) However, few studies have combined modeling of heat transfer effects and detailed experimental resultsOJ). To our knowledge, no study has measured volatiles composition as a function of time from devolatilizing large particles of wood. 

Branca C, Di Blasi C, Elefante R. Devolatilization and heterogeneous combustion of wood fast pyrolysis oils. Ind Eng Chem Res. 2005 44 799-810. 

Biomass feedstocks contain a high proportion of volatile material, 70 to 90% for wood compared to 30 to 45% for typical coals. A relatively large fraction of most biomass feedstocks can be devolatilized rapidly at low to... 

Our methods and experiments (UW) previously addressed composition effects in pyrolysis of RDF (Lai, et al 1993) and wood (Krieger-Brockett, et al 1997). In those papers and this one, even minor components are shown to alter pyrolysis slate when appropriate statistical methods are used. This paper briefly summarizes our work on pyrolysis product slates resulting from large- or macro-particle devolatilization (in which heat transfer is a slow process) of native biomass compositions in under-utilized species. The method has general applicability and owing to the limited scope of this article, the reader is referred to Somasundaram (1990), Lai (1991) and Rodriguez (1996) for details and extensive literature reviews with only a few relevant articles mentioned here,... 

ABSTRACT The radiative pyrolysis of wood (thick cylinders and chip beds) has been investigated experimentally for external radiative heat fluxes in the range 28-80kW/m, resulting in maximum sample temperatures of 600-950K. Radial temperature profiles, product yields and composition, and devolatilization rates have been measured. The influences of wood variety (hardwoods and softwoods) on the pyrolysis characteristics are discussed and comparisons are made with biomass (agricultural residues). 

Figures 2A-2B also show that the lowest residues are detected for beech, whereas the highest solid residues are obtained for the other hardwood variety, chestnut. Though at low temperatures the solid residue is high for all the softwoods, as soon as temperatures become sufficiently high, pine wood residues are significantly lower (and practically coincide with those of beech wood for very high temperatures) than those of the other two softwoods. Finally, the conversion times, defined as the time when the devolatilization rate lowers to I/IO of the maximum value, show the shortest values for the two hardwoods. Times are significantly longer for all the softwoods. Hence, contrary to the trends shown by the solid residues, close similarity exists between the hardwoods, on one side, and the softwoods, on the other.

The critical issues associated with manipulating this mechanism include volatile yield in the combustor (the distribution between volatile matter and char), devolatilization kinetics, and char oxidation kinetics. In the management of emissions formation (e.g., NO emissions), manipulation of specific mechanisms becomes important. Fuel particle size, heating rate, and combustor temperature influence the proportional distribution between volatile matter and char. The chemical structure of the fuel—various coals, coal waste, petroleum coke, wood waste. 

DTR experiments were carried out in an argon atmosphere at ten ratures from 400 C to 17(K) C (750TP to 3090 F) in order to determine the devolatilization reactivity of both sawdust and urban wood waste. Using the equaticms shown in Giapter 2, Arrhenius equations were then determined. It slmuld be noted that these are reactivity measurements based upon bulk furnace temperatures rather than particle temperatures. These measurements provide tiie data necessary for computational fluid dynamics (CFD) modeling. 

Figures 4-1 through 4-3 show the devolatilization or pyrolysis reactivity profiles of sawdust and urban wood waste note that there is a two-stage devolatilization for tiie sawdust this is not true for the urban wood waste where the matmal has been subjected to drying and weathering. The low temperature devolatilization is largely convicted before the urban wood becomes a fuel. The consequence of tfiis phenomenon is that the fresh sawdust has an even greater potential for NOx reduction than the urban wood waste.

Figure 4-5. Devolatilization Reactivity of Urban Wood Waste...

Another direct measure of reactivity is the determination of maximum volatile yield from pyrolysis or devolatilization of any fuel. Figure 4-5 compares the maximum volatile yield of urban wood waste and sawdust to the maximum volatile yield of Black Thunder and Pittsburgh 8 coal. Note that the maximum volatile yield for both woody biomass samples exceeded 90 percent. This is in direct contrast to the coals, and to the petroleum coke as shown in Chapter 2. 

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