PYROLYSIS AND CO-PYROLYSIS OF ALTERNATIVE FUELS: KINETIC CHARACTERIZATION

P. BONELLI; M. CASSANELLO; A. L. CUKIERMAN

HONG KONG, CHINA

Congreso; Seventh Asia-Pacific International Symposium on Combustion and Energy Utilization; 2004

THE HONG KONG POLYTECHNIC UNIVERSITY

Kinetics of pyrolysis of an Argentinean subbituminous coal, sawdust from poplar (Populus deltoide) wood, and of a blend composed by both fuels (50% wt) is characterized from ambient temperature up to 1100 K by nonisothermal thermogravimetric analysis at two different heating rates. Weight losses for both fuels are consistent with their volatile matter contents, as assessed by proximate analyses. The blend undergoes a similar pyrolytic behavior as the sawdust at low temperatures, up to 500 K. For higher temperatures, it follows the coal pyrolytic behavior, attaining finally an intermediate weight fraction between those determined for both fuels. Thermogravimetric curves and thermal degradation rates profiles for the individual fuels are properly described by a model which assumes an infinite number of parallel, first-order reactions through a distribution of activation energies that follows the Weibull function. The sum of distribution functions for each constituent, weighed by their proportion in the blend and volatile matter content, enables a fairly well prediction of the fuels co-pyrolysis.Populus deltoide) wood, and of a blend composed by both fuels (50% wt) is characterized from ambient temperature up to 1100 K by nonisothermal thermogravimetric analysis at two different heating rates. Weight losses for both fuels are consistent with their volatile matter contents, as assessed by proximate analyses. The blend undergoes a similar pyrolytic behavior as the sawdust at low temperatures, up to 500 K. For higher temperatures, it follows the coal pyrolytic behavior, attaining finally an intermediate weight fraction between those determined for both fuels. Thermogravimetric curves and thermal degradation rates profiles for the individual fuels are properly described by a model which assumes an infinite number of parallel, first-order reactions through a distribution of activation energies that follows the Weibull function. The sum of distribution functions for each constituent, weighed by their proportion in the blend and volatile matter content, enables a fairly well prediction of the fuels co-pyrolysis.