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Taxonomy for Industrial Cluster Decarbonization: An Analysis for the Italian Hard-to-Abate Industry

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  • Sonja Sechi

    (DENERG Department of Energy “Galileo Ferraris”, Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy)

  • Sara Giarola

    (School of Management, Polytechnic of Milan, 20156 Milan, Italy
    European Institute on Economics and the Environment, Via Bergognone 34, 20144 Milan, Italy
    Chemical Engineering Department, Imperial College London, London SW7 2AZ, UK)

  • Pierluigi Leone

    (DENERG Department of Energy “Galileo Ferraris”, Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy)

Abstract

The share of industry in final global energy consumption was more than 30% in 2020, of which, the hard-to-abate sectors accounted for almost 60% of total final consumption in industry. Similarly, in Europe, industry accounts for around 25% of final energy consumption. In order to reduce the impact of industry in energy consumption and greenhouse gas emissions, Europe has set many policies that support and regulate the sector, including pricing carbon emissions in a cap-and-trade scheme called the European Emission Trading Scheme (EU ETS). According to the EU ETS, in 2021 the verified emissions of all stationary installations were around 1.3 billion tons of carbon dioxide equivalent emissions. In 2021, the total allocated allowances amounted to around 1 billion tons of carbon dioxide equivalent emissions, half of which were freely allocated. After reviewing the existing modeling approaches for industrial clusters and the available datasets, and assessing the energy consumption and carbon dioxide emissions at plant level using a geographical information system approach (GIS), a taxonomy for industrial cluster decarbonization was introduced. This taxonomy shows that describing industry as sets of clustered installations rather than based on the conventional sectoral economic classification provides more insights into energy transition. First, the cluster description provides a more accurate techno-economic assessment based on a finer characterization of economies of scale compared to traditional energy systems models. Second, the industrial clustering approach may more realistically show the feasibility, in addition to the costs and benefits from coupling industry with transport (e.g., industrial fleets and logistics) or buildings (e.g., city scale), due to a more detailed representation of the energy sources and sinks.

Suggested Citation

  • Sonja Sechi & Sara Giarola & Pierluigi Leone, 2022. "Taxonomy for Industrial Cluster Decarbonization: An Analysis for the Italian Hard-to-Abate Industry," Energies, MDPI, vol. 15(22), pages 1-31, November.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8586-:d:974753
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    References listed on IDEAS

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    Cited by:

    1. Nienke Dhondt & Francisco Mendez Alva & Greet Van Eetvelde, 2024. "Introducing Industrial Clusters in Multi-Node Energy System Modelling by the Application of the Industry–Infrastructure Quadrant," Sustainability, MDPI, vol. 16(6), pages 1-20, March.
    2. Massimo Beccarello & Giacomo Di Foggia, 2023. "Review and Perspectives of Key Decarbonization Drivers to 2030," Energies, MDPI, vol. 16(3), pages 1-13, January.

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