Elucidating kinetic mechanisms of lignin and biomass pyrolysis by distributed activation energy model with genetic algorithm

Lignocellulosic biomass pyrolysis usually involves multiple overlapping sub-processes, which leads to some difficulties in the determination of kinetic model parameters. This study focused on the applicability of the genetic algorithm in solving a multi-extreme value optimization problem and analyzing a simulated chemical reaction process, and studying the kinetics of lignin and palm kernel shell pyrolysis using the distributed activation energy model (DAEM). The results showed that the genetic algorithm was effective and accurate in parameter estimation for kinetic analysis of chemical reaction processes. The activation energies of lignin pyrolysis were peaked at 238.4 kJ mol−1, spreading a wide range (125–350 kJ mol−1). The double DAEM with the optimal parameters could effectively deconvoluted the overall process of palm kernel shell pyrolysis into two overlapping sub-processes. The first sub-process was the predominant mechanism in palm kernel pyrolysis, occurring within a relatively narrow activation energy range of 140–210 kJ mol−1, which corresponds to the thermal decomposition of holocellulose. While the second sub-process occurs over a broader activation energy range of 100–325 kJ mol−1, corresponding to the thermal decomposition of lignin contained in palm kernel shell.