Brightcon 2026, hackathon and courses

Highlights and Discussion Points
- Facilitating a model-based integration of Life Cycle Assessments into early product development
- Supporting the transferability of the LCA method based on an open-source, Brightway-based software tool
- Incorporating uncertainties caused by lack of data and low system knowledge to prevent unaware design choices
- Providing a comprehensible way of dynamically visualising results for non LCA-practitioners by utilisation of visual analytics

Description
Embedding environmental considerations into early product development instead of retrofitting previously designed products to meet environmental requirements is, in itself, the preferable approach. However, this introduces significant uncertainties into the environmental assessment due to a low system knowledge and lack of reliable and verified data. The composition of internal primary data, information from potential suppliers, and supplementary datasets from generic databases causes a high variance in the obtained results, decreasing the precision of derived decision support. To ensure that product developers can use the information gained from preliminary Life Cycle Assessments (LCAs) for an expansion of the comparison of design variants and general decision-making to the environmental perspective, uncertainties not only have to be included in the results but their presentation needs to be carried out in a reasonable and appropriate way.
We propose a framework that tackles the handling of uncertainties at three stages: Firstly, life cycle inventory data, design parameters, and their respective uncertainties are harmonized within the Brightway LCA model. Secondly, foreground and background uncertainties are propagated through the model and quantified during the impact assessment. Lastly, visualisation tools are used to properly communicate the results to decision-makers, enabling, e.g., the identification of environmental hotspots under uncertainties and the consideration of impact distributions without the extensive background knowledge necessary to perform the LCA itself.
A case study on a car’s underbody component illustrates how this approach not only streamlines the generation of coherent inventory data but also enables a straightforward and flexible evaluation of environmental impacts under uncertainty. The combination of parametrisation and visual analytics ensures transparent, data-driven, and reproducible decisions in product design as means to lower the threshold for integrating LCAs at an early stage of the product development process.