Modelling the shipping transition: Forecasting merchant fleet emissions to 2050

Arnaud Garnier (), Pierre Marty and Rodica Loisel ()
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Arnaud Garnier: LHEEA - Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique - CNRS - Centre National de la Recherche Scientifique - Nantes Univ - ECN - NANTES UNIVERSITÉ - École Centrale de Nantes - Nantes Univ - Nantes Université
Pierre Marty: LHEEA - Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique - CNRS - Centre National de la Recherche Scientifique - Nantes Univ - ECN - NANTES UNIVERSITÉ - École Centrale de Nantes - Nantes Univ - Nantes Université
Rodica Loisel: LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - Nantes Univ - IAE Nantes - Nantes Université - Institut d'Administration des Entreprises - Nantes - Nantes Université - pôle Sociétés - Nantes Univ - Nantes Université

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Abstract: The pathway towards decarbonisation of shipping is unclear, as many technical, economic, and regulatory challenges remain. This study builds a bottom-up model to forecast the merchant fleet vessel composition and CO2 emissions by 2050. A 35,000 vessel fleet is modelled based on technical and operational data, on the population pyramid and historical fleet evolution triggered by trade demand. The emissions forecast in a ‘no-action' scenario shows that even low-growth traffic scenarios will largely deviate from the carbon neutrality objectives. It highlights fleet heterogeneity as a key point in understanding and considering global decarbonisation strategy. Fleet renewal analysis revealed technical and planning issues due to the tendency towards larger vessels and high building rates up to 2000 vessels per year from 2040 onwards. Alternatively, retrofitting could significantly contribute to carbon neutrality, concerning up to 40% of the shipping tonnage if the strategy of decarbonisation is not integrated early in shipyard industry planning.

Keywords: Energy consumption model; Shipping decarbonisation; Bottom-up approach; Fleet renewal inertia; Traffic demand scenarios; Emission forecast; AIS data (search for similar items in EconPapers)
Date: 2026-09
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Published in Transportation Research Interdisciplinary Perspectives, 2026, 39, pp.102142. ⟨10.1016/j.trip.2026.102142⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05692446

DOI: 10.1016/j.trip.2026.102142

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