Life Cycle Assessment (LCA) of Light-Weight Eco-composites [Hardcover]

Miao Guo's PhD thesis provides scientific insights into the environmental issues related to biocomposites based on starch-polyvinyl alcohol (PVOH) blends. The author contributes significantly to the methodological issues underlying the Life Cycle Assessment (LCA) modelling approach. As well as presenting complete LCA inventories using primary data from a variety of sources, Guo develops a new modelling approach incorporating the process-oriented biogeochemistry model Denitrification-Decomposition (DNDC) into site-specific LCA studies to simulate carbon and nitrogen dynamics in the wheat agro-ecosystem. This thesis addresses important LCA data quality issues by using comprehensive sensitivity and uncertainty analyses and has resulted in a large number of publications in internationally renowned journals.This book reviews environmental issues related to biocomposites, and offers a new modeling method incorporating process-oriented Denitrification-Decomposition into site-specific LCA studies, to simulate carbon and nitrogen dynamics in the wheat agro-ecosystem.Materials and Methods.- LCA of Wheat Agro-Eco-Systems.- LCA Case Studies of Starch-Based Foam.- End of Life Scenarios.- LCA of WBF Products Over Whole Life Cycles.- Sensitivity and Uncertainty Analysis.- General Discussion and Conclusions.Miao Guo's PhD thesis provides scientific insights into the environmental issues related to biocomposites based on starch-polyvinyl alcohol (PVOH) blends. The author contributes significantly to the methodological issues underlying the Life Cycle Assessment (LCA) modelling approach. As well as presenting complete LCA inventories using primary data from a variety of sources, Guo develops a new modelling approach incorporating the process-oriented biogeochemistry model Denitrification-Decomposition (DNDC) into site-specific LCA studies to simulate carbon and nitrogen dynamics in the wheat agro-ecosystem. This thesis addresses important LCA data quality issues by using comprehensivlS�