The overarching goal of our work is to optimize the AqSO biorefinery by making it more resource efficient and capable of producing lignin with structural properties tailored to specific applications in lignin valorization. Our first step is to use BO to obtain surrogate models that relate the key AqSO processing conditions, namely the hydrothermal pretreatment temperature and reaction severity, to multiple experimental targets. These consist of the yield of the extracted lignin and the content of various structural properties obtained using 2D nuclear magnetic resonance (NMR) characterization. For the latter, we focus on the β-O-4 content, the ratio of syringyl and guaiacyl (S/G) units, and the content of carbohydrates present as lignin-carbohydrate complexs (LCCs). To accomplish our stated goal, we then apply a Pareto front analysis to the surrogate models, which allows us to simultaneously maximize the lignin yield and optimize structural properties for selected applications. By ensuring that the lignin yield is maximized, we achieve better resource efficiency in the AqSO process.