(661c) Air Classification of Forestry Residues for Fast Pyrolysis | AIChE

(661c) Air Classification of Forestry Residues for Fast Pyrolysis

Authors 

Saha, N. - Presenter, Idaho National Laboratory
Klinger, J., Idaho National Laboratory
Bhattacharjee, T., Idaho National Laboratory
Xia, Y., Idaho National Laboratory
Thompson, V., Idaho National Laboratory
Oyedeji, O., University of Tennessee
Parks, J. E., Fuels, Engines and Emissions Research Center, Oak Ridge National Laboratory
Shahnam, M., National Energy Technology Laboratory
Xu, Y., WVURC
Understanding critical biomass attributes through efficient fractionation is crucial for advancing sustainable pyrolysis for renewable energy and chemical production. This study investigates the intricate relationship between biomass preprocessing and pyrolysis product yields, employing the air classification technique for the treatment of loblolly pine residues with varying moisture content. A comprehensive exploration of the physicochemical properties of air-classified loblolly pine informs a sophisticated pyrolysis simulation model. Given the complex and multifaceted nature of biomass pyrolysis, operating across diverse temporal and spatial scales, a pyrolysis kinetics-based CFD–DEM simulation method is employed to predict product yields. Results showed that the elevated moisture content amplifies particle adhesiveness, necessitating augmented air velocities for effective separation, thereby influencing the efficiency of the separation process. While carbon and hydrogen contents exhibit relative stability across diverse moisture contents and blower frequencies, the oxygen content undergoes noticeable changes. For example, the oxygen contents were measured as 29.2 and 38.6 wt% in the light fraction of 30% moisture content sample at blower frequencies of 10 and 20 Hz, respectively. An intriguing finding emerges from pyrolysis simulation, indicating that a lower blower frequency in air classification moderately enhances bio-oil yield and significantly improves its quality, particularly in terms of water content. For instance, the water content in the bio-oil was about 1.5% and 10% in the heavy and light fractions, respectively from 10% moisture sample under 15 Hz blower frequency.