In this study, the viability of acetylation in cellulose fibers waste (CFW) from pulp and paper mill sludge was investigated in comparison to bleached cellulose fibers (BCF). Four acetylation methodologies were applied. The inorganic ash composition of the CFW was determined by Energy Dispersive X-ray Spectrometry (EDS). The Degree of substitution (DS) of the acetylated fibers and their characterization using Fourier Transformed Infrared (FT-IR), X-ray diffraction (XRD), Thermogravimetric analysis (TGA), and Scanning electronic microscopy (SEM) were carried out. Results showed that the different acetylation methods are not effective for the esterification of CFW largely due to a high mineral content in their composition. The acetylation promoted the removal of the inorganic content in the CFW resulting in low efficacy levels. In BCF, higher efficiency levels were achieved, varying according to the methods. The different acetylation methods showed an efficiency range from 0.02 to 1.76 depending on the type of fiber.

This article addresses the optimization of the quality of wood—plastic composites (WPC) designed for outdoor uses such as decking, taking into account the environmental impact during the life cycle of the product, from production to end of life (from ground to ground). In a context where several conflicting objectives must be satisfied simultaneously in the design process, meta-heuristic approaches provide efficient methods for optimization. Multi-objective particle swarm optimization (MO-PSO) has been chosen here to solve a complex problem in which physical properties such as creep and duration of load, water absorption and swelling, need to be improved with a limited impact on environment. This requires to get reliable information on material properties as related to its composition, environmental impacts through life cycle analysis (LCA), and to implement relevant information such as exhaustion of fossils resources through analytical or probabilistic models in the PSO algorithm in order to obtain a set of optimal solutions for the composite. This article shows the feasibility of this approach, which can be generalized in the design of any type of composite structures, provided objective functions can be specified.

Biorefineries have many possible designs and therefore, present varied benefits in regards to sustainable development. Evaluating these biorefineries is central for the domain, and, as small-scale biorefineries (SSB) are commonly opposed to the large ones, specifying the concept of scale of a biorefinery is essential as well. However, there is no consensual definition of the “scale”, and the meaning of the term changes with the context. This paper presents a methodology to specify the concept of scale by grouping various biorefineries processing lignocellulosic biomass according to factors related to feedstock, process, economy and mobility of the facility, without any predetermined pattern. Data from 15 operational biorefineries are analyzed using a multivariate analysis combined with a hierarchical clustering. The classification obtained categorizes biorefineries into four design classes: smallest, small, hybrid and large scale. Small-scale biorefineries are characterized by a small investment cost (less than 2 M€), a low processing capacity (less than 100 t/day) and a low process complexity, while the end-products’ added value is variable. The mobility of the plants is a sufficient, but not necessary, criterion to have a small-scale biorefinery. Finally, the designs of the investigated biorefineries can be explained by two main trade-offs: one between the mobility and the processing capacity-investment cost, and the other between the process complexity and the added value.