Effect and Optimization of Process Conditions during Solvolysis and Torrefaction of Pine Sawdust Using the...

Understanding optimal process conditions is an essential step in providing high-quality fuel for energy production, efficient energy generation, and plant development. Thus, the effect of process conditions such as the temperature, time, nitrogen-to-solid ratio (NSR), and liquid-to-solid ratio (LSR) on pretreated waste pine sawdust (PSD) via torrefaction and solvolysis is presented. The desirability function approach and genetic algorithm (GA) were used to optimize the processes. The response surface methodology (RSM) based on Box-Behnken design (BBD) was used to determine the effect of the process conditions mentioned above on the higher heating value (HHV), mass yield (MY), and energy enhancement factor (EEF) of biochar/hydrochar obtained from waste PSD. Seventeen experiments were designed each for torrefaction and solvolysis processes. The benchmarked process conditions were as follows: temperature, 200-300 °C; time, 30-120 min; NSR/LSR, 4-5. In this study, the operating temperature was the most influential variable that affected the pretreated fuel's properties, with the NSR and LSR having the least effect. The oxygen-to-carbon content ratio and the HHV of the pretreated fuel sample were compared between the two pretreatment methods investigated. Solvolysis pretreatment showed a higher reduction in the oxygen-to-carbon content ratio of 47%, while 44% reduction was accounted for the torrefaction process. A higher mass loss and energy content were also obtained from solvolysis than the torrefaction process. From the optimization process results, the accuracy of the optimal process conditions was higher for GA (299 °C, 30.07 min, and 4.12 NSR for torrefaction and 295.10 °C, 50.85 min, and 4.55 LSR for solvolysis) than that of the desirability function based on RSM. The models developed were reliable for evaluating the operating process conditions of the methods studied.