Decarbonization Pathways in EU Manufacturing: A Principal Component and Cluster Analysis
Abstrak
This study assesses decarbonization progress in the European Union manufacturing sector between 2015 and 2023, using harmonized Eurostat indicators. The dataset covers emission intensity, energy intensity, renewable energy use, and structural markers of value added. After standardization, variables are reduced through principal component analysis (PCA). The resulting scores are then clustered with k-means, with the number of clusters chosen using elbow and silhouette diagnostics and validated through hierarchical clustering, representing a methodological innovation over existing typological studies. The results highlight persistent heterogeneities across member states. A group of frontrunners combines low intensities with a high share of RES; efficiency-centric groups advance mainly through energy intensity reductions but lag in fuel-switching, while structurally constrained groups remain hindered by energy mix limitations and outdated capital stocks. Dynamically, moderate convergence is observed along the main transition dimension, but persistent divergence remains in structural composition. These patterns justify differentiated policy approaches: accelerating fuel substitution where efficiency gains have already been achieved and integrated packages of modernization and infrastructure in structurally constrained economies. The novelty of this study lies in providing a harmonized, EU-wide, and reproducible typology of industrial decarbonization trajectories, enabling systematic cross-country comparison. Policy relevance is reinforced by linking the typology to current EU instruments such as the Emissions Trading System (ETS), the Carbon Border Adjustment Mechanism (CBAM), the Innovation Fund, and the Net-Zero Industry Act. The integration of PCA with clustering provides an evidence-based that is valuable for prioritizing European industrial policies in line with the Green Deal.
Penulis (3)
Cătălin Gheorghe
O. Panazan
N. Stelea
Akses Cepat
- Tahun Terbit
- 2025
- Bahasa
- en
- Total Sitasi
- 1×
- Sumber Database
- Semantic Scholar
- DOI
- 10.3390/su17188154
- Akses
- Open Access ✓