Utilisation des données d'une plateforme de traçabilité blockchain pour l'amélioration des ACV

The environmental emergency that humanity is facing, with critical issues such as global warming or the loss of biodiversity, must be considered with the greatest attention by industrial companies facing at the same time the toughening of environmental regulations and increased expectations from consumers about the sustainability of the products they buy. To measure and communicate about the environmental impact of their products, industrial companies mostly use the Life Cycle Assessment (LCA) methodology, which makes it possible to assess the impact of products on their entire value chain. However, this methodology is highly dependent on the specificity of the data it takes into account to provide a reliable and representative impact result. The difficulty of collecting production data from different stakeholders in a value chain is thus its main limitation. At the same time, the applications of blockchain technology for product traceability and industrial data registration have recently boomed thanks to its immutability, its integrity, and the persistence of data on the network that guarantee transparency and trust between stakeholders. This research paper focuses on the opportunities of blockchain traceability systems to improve the LCA of industrial products. For the moment, few articles link LCA and blockchain traceability and those who do simply propose an integration framework and a general architecture without detailing the business processes and the stakeholders concerned in an implementation project. A methodology for implementing blockchain-LCA systems divided in 8 main business processes has thus been developed and evokes the activities, stakeholders, milestones and deliverables needed to carry out such a project. An experiment was then conducted on wool top lots to assess the contribution of this methodology. Two main results were obtained: the environmental impact of the wool top lots can vary drastically depending on their composition and the origin of the wool (up to +118% on the overall environmental impact between two batches of different compositions) and the specific data provided by traceability strongly changes the perception of the impact of wool top lots compared to generic data for a fixed wool composition (+36% of calculated impact on the processing step with specific data). These results justify the use of blockchain traceability to refine the LCA calculation of environmental impact at the level of product batches. The limitations of these results and future research perspectives are then presented to complement the methodological tool developed in this paper.