Patterns and Predictions In Recycling: A Time-Series Clustering Study of Recycling Rates In The European Union

Sustainability, circular economy and solid waste management play a crucial role in mitigating environmental impacts, promoting the efficient use of resources and the transition to more resilient and sustainable economic models. Time-series clustering algorithms were applied to evaluate the evolution of recycling rates in 25 European Union countries. This application made it possible to identify patterns and evaluate the behavior of the various European countries. Results highlight the economic and political implications of recycling efficiency, with high-performing countries benefiting from strong policies and R\&D investments, while low-performing nations face economic and regulatory challenges. Findings reinforce the need for targeted interventions, harmonized policies and infrastructure investments to advance the EU circular economy agenda. Additionally, inconsistencies in reporting standards and missing data underscore the necessity for improved data harmonization. The study expands upon prior research by integrating dynamic clustering methods, offering a more comprehensive understanding of recycling trends over time.