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

Sonja Sechi, Sara Giarola and Pierluigi Leone ()
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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
Pierluigi Leone: DENERG Department of Energy “Galileo Ferraris”, Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy

Energies, 2022, vol. 15, issue 22, 1-31

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.

Keywords: industrial clusters; decarbonization; hard-to-abate sector; spatial analysis; industrial area; database; geographical information system; taxonomy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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