Life cycle assessment is a popular approach for evaluating the environmental impact of technologies. However, one application to new solvents, Ionic Liquids, exposes its many weaknesses and shortcomings. This work focuses on developing new methods, new data, and solving existing problems to complement and improve conventional LCA methodology. Ecological goods and services are benefits mankind obtains from nature. Many holistic approaches including LCA, energy and exergy analysis ignore this crucial contribution from nature. This work develops “Ecologically-Based LCA” that accounts for the contribution of ecosystem goods and services to industrial activities. Besides minerals and fossil fuels, ecological resources include water use, soil erosion, pollination, and bio-geo-chemical cycles. Inventory data are available in diverse units, which are difficult to combine. This is solved by developing a hierarchy of metrics. Normalized raw data form the finest scale to identify the most important resources for the selected product. Aggregate metrics form the middle layer to capture key features. Here, various physical methods such as mass, energy, exergy are explored for the proposed aggregation. At the top level are three sustainability metrics: cumulative resource consumption, renewability and efficiency.
Life cycle inventory can be assembled by process model-based and economic model-based approaches. A significant outcome of this work is an Eco-LCA model of the 1997 U.S. economy. This integrated economic-ecological model augments the U.S. EIO model with information about ecosystem goods and services relevant to each sector. Many existing approaches connecting ecological flows to monetary flows are examined. It is proved that these approaches derived from different perspectives are theoretically identical, and the use of physical, monetary, or mixed units gives consistent results. The richness of this IO-based Eco-LCA dataset enables many types of exploration and research topics. Some of the features are illustrated via a case study comparing the life cycles of four kinds of cups. Regression analysis of resource consumption, emissions, and impact are performed, which can overcome the difficulty of applying LCA to emerging technologies. Finally, the uncertainties in the IO-based dataset are assessed and improvement methods are proposed.