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Carbon trade biases and the emerging mesoscale structure of the European Emissions Trading System network

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  • Andrea Flori

    (Politecnico di Milano)

  • Alessandro Spelta

    (University of Pavia)

Abstract

The European Union Emissions Trading System (EU ETS) is designed to promote cost-effective carbon emission reductions through allowance trading. However, observed trade patterns suggest potential inefficiencies. This study conducts a province-level analysis of the EU ETS trade network of allowances, demonstrating that trades predominantly occur between entities within the same country and sector, even in recent phases of the system. To systematically examine the mesoscale structure of the trade network while accounting for geographical and sectoral homophily, we introduce a community detection framework based on the gravity model and optimal transport theory. By disentangling home and sectoral biases, we identify trade communities that align with cultural dimensions. Our findings reveal a complex interplay between geographical, economic, and cultural factors that shape carbon allowances trade patterns. These findings contribute to a deeper understanding of structural constraints within the EU ETS trade network and inform strategies for improving its cost-effectiveness.

Suggested Citation

  • Andrea Flori & Alessandro Spelta, 2025. "Carbon trade biases and the emerging mesoscale structure of the European Emissions Trading System network," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59913-w
    DOI: 10.1038/s41467-025-59913-w
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