A predictive PBM-DEAM model for lignocellulosic biomass pyrolysis

Pyrolysis is a promising and attractive way to convert lignocellulosic biomass into low carbon-emission energy products. To effectively use feedstock with size distribution produce biofuels, comprehensive kinetic model of the process, occurring at particle level, important. In this study, population balance (PBM)-distributed activation (DAEM) coupled first time developed predict pyrolysis. The Population used present variable solid, decomposed from virgin porous char. Two different models are embedded conservation equations mass energy. They compared demonstrate prediction performance heating-up during pyrolysis process normal distribution. It found that non-isothermal kinetics without DEAM capture intra-particle temperature There noticeable difference between single distributed size.