Streamlining Life Cycle Assessment to support Ecodesign through multi-criteria materials selection

This thesis aims to demonstrate how these issues can be solved using specific case studies as examples. The first chapter is dedicated to an introduction to the LCA methodology, in which it is also possible to find a literature review focused on the strengths and weaknesses that may characterize LCA. The second part of the chapter details the methods utilized to analyze uncertainty in LCA results, the state of the art for streamlined and predictive approaches and, finally, an overview of a multi-criteria analysis method useful for materials selection. In particular, the uncertainty analysis associated with LCA results may represent the starting point for the development of streamlined LCA approaches and possible methods of forecasting the environmental results of novel technologies. On the other hand, the multi-criteria analysis grounded in the uncertainty analysis presents a robust method of materials selection in support of Ecodesign. In the second chapter, the uncertainty analysis is used to develop a streamlined LCA method founded on the probabilistic underspecification approach, proposed to support the building design process. The case studies analyzed in this section represent a series of residential building assemblies (exterior walls, interior walls, foundations, roofs, floors, windows, doors, exterior finishes) that were used to test the streamlined method and obtain distributions of results using a cradle-to-gate approach along five phases of the building design process. The bill of materials (BOM) of a building assembly can be specified using different levels of information, which can be really generic during the concept design and fully detailed during the executive project. The low-fidelity characterization of a BOM and the uncertainty associated with these low levels of fidelity are systematically quantified through probabilistic underspecification using a hierarchical classification of materials. Quantitative environmental results, processed with uncertainty analysis, were obtained using low-fidelity categories for materials and building assemblies, demonstrating that LCA can be applied not only when a complete and detailed BOM is available but also when fewer details are known. Finally, decision-making at different stages of the design process is sustained by this approach and is based on the use of a comparison indicator. The third chapter advances the research aimed at streamlining the LCA of buildings with probabilistic underspecification and uncertainty analysis. In particular, it investigates whether LCA can be robustly streamlined through an effective and efficient triage of data collection and the consequent selected use of specific and resource-intensive information. In this context, tests were conducted with a series of building typologies (single-family detached houses and multi-family residential buildings), again analyzed with a cradle-to-gate approach. The probabilistic triage approach was tested to clarify how to use probabilistic underspecification and reduce the effort involved in specification by identifying the activities that require careful characterization. With this approach, by specifying only one part of the bill of materials to the highest level of specificity, the results proved to be both reasonably accurate and obtainable with less effort. Impacts such as global warming, acidification, eutrophication, and smog creation were assessed, and the results indicated that just 40-46% of the BOM components represent 75% of the total impacts of both single-family houses and multi-family buildings. Where the second and third chapters were devoted to the streamlined analysis of conventional products, the fourth chapter addresses the use of uncertainty analysis to forecast the environmental burden of an innovative material. Here, a scale-up protocol for an environmental impact assessment is proposed as a means to develop a streamlined ex-ante LCA approach. The novel element of this chapter consists of the adopted scale-up protocol. It does not rely on primary data collected by monitoring real industrial systems, as these data do not yet exist for the product of interest; instead, data measured in a plant at the pilot scale are used alongside data simulated from thermo-chemical considerations based on the stoichiometry of the considered reaction. The scale-up protocol is described and then applied to the case of polybutylene succinate (PBS), a biopolymer that is gaining attention (particularly as a replacement for polyolefins) and is obtained from bio-based succinic acid. Monte Carlo simulation was used to process the uncertainty data for all of the assessments, and a sensitivity analysis was performed to evaluate and compare the different renewable sources and chemical routes available for the production of bio-based succinic acid. The case study of PBS highlights how innovative products can be analyzed without the use of primary data, providing a way to forecast environmental impacts for novel technologies. The advantages of the adopted scale-up methodology consist of the ease of implementation and the possibility of strengthening the Ecodesign approach. In the fifth chapter, a multi-criteria analysis was used to complete the ex-ante LCA results for PBS. The purpose of this analysis was to compare PBS to alternative materials on the basis of more than one property and for use in a specific function. This approach led to the definition of a new concept of the system boundary of the assessment: from cradle to function. The motivation for this alternative strategy stems from the application of the LCA framework to a material to obtain an ecoprofile: the scope of the analysis is generally from cradle to the factory gate, while the unit of mass (or volume) of the material is usually taken as the functional unit for the analysis. However, these methodological choices place relevant limitations on the effectiveness of the assessment. In this chapter, a multi-criteria materials approach was tested using the PBS results to verify and validate the environmental viability of this material’s usage in packaging films. The most novel element of this research is the use of the customized ex-ante LCA and the uncertainty analysis, the latter of which is used to determine the uncertainty in material indices. The results were graphically represented with Ashby plots. When elongation at break and environmental performance were considered, PBS displayed a performance that was better than other traditional polyesters and comparable to the polyolefins considered; performance in terms of this set of properties is particularly beneficial in the case of secondary packaging. In the case of primary packaging, barrier properties acquire major relevance; in this regard, PBS presented among the best trade-offs for the simultaneous optimization of oxygen permeability, elongation at break and environmental impact. Finally, the sixth chapter is devoted to the review of the approaches that were implemented and tested to streamline LCA, highlighting the strengths and weaknesses for each analyzed system and discussing future methodological developments. In particular, the uncertainty analysis based on the Monte Carlo method was used not just to characterize the quality of results but also to develop and implement streamlined approaches. Moreover, the uncertainty analysis proved to be useful for forecasting environmental results for early-stage systems and innovative materials.