Life Cycle Assessment (LCA) of Light-weight Eco-composites

Abstract

The environmental profiles of novel wheat based foam materials were investigated in this thesis using Life Cycle Assessment (LCA) methods. The LCAs were developed using primary data collected from industrial sources combined with new laboratory experiments supplemented with secondary data from publicly available sources. Laboratory research was conducted to obtain important missing data on WBFs for the LCA modelling, including physico-chemical parameters, biodegradability and energy recovery under anaerobic digestion conditions. Contribution analysis suggested that the emissions evolved from the wheat agro-ecosystem and PVOH production, together with the energy and infrastructure involved in WBF production were the major contributors to the environmental burdens of the WBF life cycle in most impact categories. The atmospheric emissions resulting from WBF degradation at the end-of-life also emerged as another important contributor to environmental impact. Amongst the diverse 'end-of-life‘ scenarios examined, AD and home composting were suggested to be the optimum choices for WBF waste treatment. To address the question 'is there a general environmental advantage for WBFs over petrochemical polymers', case studies were applied to compare the performance of WBFs with HDPE/LDPE/EPS in various applications. Further exploration of potential biopolymer foam materials was undertaken by study of two additional foams derived from potato and maize starches. The results suggested that this group of starch-PVOH blended biopolymers offer environmentally superior options to LDPE in thermal packaging applications. However, this is not the case for other applications, where the outcome of comparisons between starch-PVOH biopolymers and HDPE/EPS varied with the specific application examined. A hierarchy of critical parameters for LCA-based decision-making on WBFs is suggested as a general outcome of this research. This research discusses two N2O modelling approaches and presents a method to expand the system boundary by integrating the process-oriented model DNDC for field emissions into the LCA. Sensitivity analysis suggests that the environmental profiles of agricultural products are influenced substantially by the system boundary definition. Furthermore, it suggests that the 'general rule‘ in LCA practice by applying an empirical model or a default emission factor (EF) could deliver unreliable LCA findings. This study also evaluated the sensitivity of the LCA results to methodology and data variations and quantified the uncertainties in the LCA outcomes arising from uncertainty in the inventory and data variability. This has led to an increase in confidence in the LCA findings. At the same time it indicates the areas where improvements in data or methods are needed in order for robust conclusions to be drawn and unbiased information to be delivered e.g. the methodological rigidity of characterization models, the IPCC Tier 1 EF uncertainty range.