DescriptionConsidering environmental impacts in the early stage of product design gets increasingly essential. This is because degrees of freedom in the early design stage are greater than in a later stage of design. On the other hand, uncertainty decreases throughout technology development as decisions are taken, and the observed process becomes clearer and more data is available. In order to provide data in an early design stage and scale this data to a future point in time, upscaling schemes are needed to fill data gaps. A method for upscaling are so-called learning curves. Learning curves can examine historic development rates of technologies and can be extrapolated into the future to estimate technology learning effects. This approach has already been used in economics to analyze the correlation between production and costs and preliminary to the development of environmental impacts. In this work, different versions of the LCI database ecoinvent are used to derive scaling factors. Each of these databases is analyzed using the Brightway 2.5 LCA framework by calculating the environmental impacts of each process. Via mapping processes producing the same reference product in the same geographical location of each database, the environmental impacts of each process can be compared throughout the databases. Following this approach, it can be concluded that, for example, the GWI is by 0.5 % when comparing ecoinvent 3.1 with ecoinvent 3.8. The results show the applicability of the method and indicate potential technology learning over time based on LCI databases. These findings will be helpful in the application of prospective LCA. However, product- or sector-specific scaling factors could lead to an even more insightful analysis.
|19 May 2022
|SETAC Europe 32nd Annual Meeting: Towards a Reduced Pollution
|Degree of Recognition