Lignocellulosic biomass (LCB) has the potential to replace fossil fuels, thanks to the concept of biorefinery. This material is formed mainly by cellulose, lignin, and hemicellulose. To maximize the valorization potential of this material, LCB needs to be pretreated. Milling is always performed before any other treatments. It does not produce chemical change and improves the efficiency of the upcoming processes.

Ulva rigida seaweed is constituted by ulvan, which is a sulfated polysaccharide with uses in a wide variety of applications. After the ulvan-oriented extraction process, a crystalline and recalcitrant residue, the so-called pulp, appears. In this work, this residue was valorized through a multiple-stage process. The total processing of the algae consists of hot water extraction, acid hydrolysis, ABE fermentation, and distillation in order to obtain not only ulvan but also butanol and bioethanol to be used as biofuels by simulating two third-generation algae-based biorefineries in Aspen Plus v10 software. Third-generation plants do not compete with food and algae biomass, and they do not require delignification nor pretreatment steps, which are usually the bottleneck of second-generation plants. A plant producing butanol as biofuel together with diluted ulvan, acetone, and ethanol as byproducts was modelled in Aspen Plus software. Regarding the profitability of the investment, the plants producing bioethanol and butanol were economically feasible. The economic parameters for the bioethanol and butanol plants were as follows: NPV equal to 27.66 M$ and 16.67 M$, and IRR equal to 46% and 37%, respectively. The discounted return period was acceptable for these types of plants, which were 4.11 and 3.16 years for the ABE biorefinery and the bioethanol biorefinery, respectively.

Energy demand is the major drawback to using mechanical treatments within the biorefinery context. These treatments use energy to reduce particle size and crystallinity and, as a result, increase the accessibility of cellulose. However, the study of energy demand in milling needs to be more noticed. Therefore, this study aims to study how operational variables affect particle size and energy demand on one of the most used milling technologies: ball milling. The variables considered were mass of biomass, mass of balls and time. It was found that time is the most affecting variable for particle size and energy demand. Additionally, it was possible to optimise milling regarding energy demand and particle size. Furthermore, it was found that from the three traditional laws of comminution Bond was the one that gave the best results in terms of accuracy.