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Identification of emission characteristics under global shipping decarbonization pathways

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  • Xu, Lang
  • Li, Lele
  • Chen, Jihong
  • Yan, Ran
  • Zhang, Yang

Abstract

Maritime shipping is central to global trade and climate mitigation. We propose an interpretable generative modeling framework to characterize shipping carbon dioxide (CO2) emissions and analyze shipping decarbonization pathways via 1,202 scenarios from the IPCC AR6 database. Climate categories are consolidated into three mitigation groups, and 50 shipping-related variables are converted into cumulative-change features. We then train three generative models to produce synthetic mitigation scenarios and evaluate their performance through bidirectional random-forest (RF) label-transfer tests, distributional realism and structural consistency checks. The results suggest that shipping CO2 emissions are associated with the joint variation in demand heterogeneity, energy-system conditions, policy stringency, and fuel substitution. The synthetic scenarios further demonstrate that higher carbon prices, greater power electrification, and lower oil-based fuel dependence are consistently associated with lower-emission shipping pathways. These findings offer a data-driven basis for identifying CO2 emission characteristics and supporting long-term shipping decarbonization strategies.

Suggested Citation

  • Xu, Lang & Li, Lele & Chen, Jihong & Yan, Ran & Zhang, Yang, 2026. "Identification of emission characteristics under global shipping decarbonization pathways," Transportation Research Part A: Policy and Practice, Elsevier, vol. 213(C).
    • Handle: RePEc:eee:transa:v:213:y:2026:i:c:s096585642600354x
    DOI: 10.1016/j.tra.2026.105213
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