Uncertainty analysis focusing on the variance of energy intensity of vehicle materials

Abstract This paper serves as both a literature review and a preliminary study of the quantitative effects of temporality relating to the age of data as well as spatiality in Life Cycle Assessment. Temporality and spatiality due to age of data have not been the subject of formal analysis. In this study, temporality and spatiality is studied in relation to the input stages of manufacture as opposed to emissions-related studies. To this end, the Greenhouse gases, Regulatory Emissions, and Energy use in Transportation 2 model is used. Created by the Argonne National Laboratory, this model offers information on the life cycle of sedans, sport-utility vehicles and pick-up trucks with a variety of different power train configurations and manufacturing of materials. Historic data on net energy intensity for materials of manufacture were analyzed using Monte Carlo simulations in order to explore temporal and spatial variability which can be attributed to age of data. Subsequent analysis showed that, depending on the mix of materials used, temporal and spatial variation has quantified effects on total energy calculations for all vehicle types. However, this variation is dependent on the type of material in question and its corresponding weight. A set of variability analysis tools previously unused in Life Cycle Assessments was used to establish a platform for future analysis in this area, including previous precepts regarding the use of predefined probability distributions (normal, lognormal, etc.) in modeling. The temporal and spatial variance due to the age of data found here have significance in the inventory stage and for the robustness of Life Cycle Assessment findings. In doing so, this study brought attention to a subject which could have consequences across a wide variety of industrial manufacturing activities.

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