Green and digital shipping corridors: AIS-informed infrastructure and operational coordination
Year: 2026
Type: article
Abstract: Green and Digital Shipping Corridors (GDSCs) require coordinated investment in alternative-fuel and digital infrastructure to support maritime decarbonization. This study proposes an AIS-informed optimization framework for coordinated green and digital infrastructure planning in the Singapore–Japan (SG-JP) and Singapore–Australia (SG-AU) corridors. Historical 2021 Automatic Identification System data are reconstructed into end-to-end vessel trajectories and corridor networks, providing the basis for estimating fuel demand and Just-in-Time fuel-saving potential. A mixed-integer linear programming model jointly optimizes LNG bunkering deployment, interoperable digital infrastructure, and LNG/HFO fuel allocation while accounting for fuel, infrastructure, carbon-emission, and methane-emission costs. Results show that the SG-JP corridor exhibits a denser and more diversified network, whereas the SG-AU corridor is more dependent on Singapore as the dominant hub. Intermediate ports outside the officially designated GDSC contribute substantially to operational coordination in the SG-JP corridor, while restricting infrastructure deployment has only a limited impact on the Singapore-Australia corridor. Joint planning achieves lower total costs than separated planning and the single-infrastructure benchmarks, but produces slightly higher GHG emissions than separated planning. Comparisons across budget ceilings reveal differences in facility locations and composition, with no further cost reduction beyond an economic investment threshold. Sensitivity analyses show that fuel prices, methane slip, vessel tank capacity, and assumed LNG service availability influence the selected portfolios. The proposed framework provides a practical decision-support tool for planning economically efficient and operationally resilient GDSCs before implementation.
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,240
OpenAlex ID: W7225427572
