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.