Lignin, the most abundant aromatic biopolymer on Earth, shows immense potential as a platform for generating biobased chemicals due to its aromatic structure. The oxidative depolymerization of lignin represents an eco-friendly method to transform complex lignin structures into valuable aromatic compounds. In the present study, the optimization of oxidative depolymerization of hardwood lignin (HWL), extracted via aldehyde-assisted fractionation, was achieved through a Box-Behnken design (BBD) quadratic regression model to enhance monomer yields. The model exhibited excellent predictive accuracy, showing significant correspondence between predicted and actual data, which signifies its robustness in optimizing reaction conditions. The main operating parameters, i.e., temperature (170–210 °C), pressure (5–15 bar O2), and residence time (5–25 min) were methodically varied, and the optimal conditions for monomer yield were determined. Under optimal conditions, the primary monomers produced were syringaldehyde and vanillin, along with lesser amounts of acetosyringone, acetovanillone, syringol, and guaiacol. The reducing ability of the produced monomers was examined through density functional theory computations, in which electron, hydrogen atom, and hydride donating abilities were calculated. Size-exclusion chromatography verified the effective degradation of lignin, showing clear distinctions between the blank and oxidatively depolymerized samples. This research underlines the efficiency of controlled oxidative depolymerization in converting HWL into valuable aromatics, with the BBD model being essential for optimizing the process toward efficient lignin valorization.
