Prospective Life Cycle Assessment of Recycled Carbon Fibres from a Solvolysis Process and their Potential Applications in the Transport and Building Sector

Kurzfassung

Due to the high energy input and consumption of non-renewable resources for the production of today’s virgin carbon fibres (vCF) based on Polyacrylonitrile (PAN), their multiple use in a potential circular economy seems desirable from economic and ecological point of view. The EDISON-rCF project demonstrates the potentials of a recycling process chain for carbon fibre reinforced polymers (CFRP). One- and two-dimensional semi-finished products for subsequential use in the transport and construction sectors were developed and tested based on recycled carbon fibres (rCF) obtained from an improved Solvolysis process. In a Life Cycle Assessment (LCA) for CFRP based lightweight systems the modelling and interpretation of a future cascading product system is a challenge because of Life Cycle Inventory (LCI) data quality and allocation methods. The availability of reliable data for the virgin carbon fibre production is limited and literature data shows considerable scattering of energy consumption and incompleteness regarding the covered phases of the production. Particularly in the recycling of high-performance materials such as carbon fibres, attention must be paid to potential performance losses (downcycling) and corresponding influence on their applicability. An important factor for the establishment of recycling routes is the creation of incentives for the recycling including a useful application of such materials. The allocation of potential environmental impacts based on different EoL Formulas plays a crucial role here. The presentation sheds a light on the preliminary results for the use of rCF in two potential use-cases, a bicycle transport box and rebars for carbon concrete. For this, the whole process chain rom a cradle-to-gate perspective was modeled using foreground and background data with different level of completeness. Therefore, the uncertainty of this prospective LCA is high and shows the potential shortcomings of incomplete data based on missing information and low technology readiness level.