Improving automated Life Cycle Assessment with Life Cycle Inventory model constructs

Global warming is a global and critical challenge and car manufacturers pledge to reduce their carbon footprint. It is mandatory to assess the carbon footprint of current and upcoming vehicles to achieve these self-set and quantified targets. Life Cycle Assessment (LCA) is a standardized and scientifically acknowledged method to quantify a product's or company's environmental impact. Due to the complexity of a vehicle's cradle-to-gate phase, automation of LCAs is a suitable simplification strategy by importing product information and auto-matically assign them to pre-defined life cycle inventory (LCI) models. The data acquisition is a recognized issue, but the LCI modelling is hardly discussed in the literature for automated LCAs even though it has a significant influence on their accuracy. This paper presents an approach to elaborate an LCI model construct that enables consistent and efficient automated LCA while maintaining defined accuracy and applicability in commercial LCA software. Such an LCI model construct and its derivation are presented in this paper for automotive aluminium components considering sheet components, casting components and extrusion profiles. It is mandatory for a precise calculation to take the most influencing parameters into consideration. Grid points for each of these parameters are elaborated dependent on the characteristic if the parameter is continuously or discretely variable. The resulting LCI model construct makes this most influencing parameters customizable in an automated LCA. A generic method for the design of such an LCI model construct based on the findings of the use case was derived in this paper. The application of this methodology is not limited for vehicle's LCAs and carbon footprint, but other complex products and impact categories to enable efficient, consistent, and accurate LCA results for complex products.