Carbon Emission Reduction Potential in Global Seaborne Metallurgical Coal Trade Through Supply Chain Network Optimisation

This study addresses the challenge of designing low-carbon supply chain pathways in the global seaborne metallurgical coal sector by developing an enhanced Ant Colony Optimisation (ACO) algorithm. This quantitative approach bridges operations research and sustainability science by identifying optimal supply pathways to minimise transportation-related carbon emissions. The enhanced framework incorporates coal-specific maritime logistical constraints and maintains Pareto efficiency across a comprehensive global dataset encompassing 201 mines, 11 exporting nations, and 72 destination ports in 26 importing countries. Computational analysis demonstrates that the proposed algorithm achieves a 25% reduction in transportation carbon intensity (from 38.2 to 28.6 kg CO2eq/t) relative to the 2022 baseline. To evaluate supply chain resilience, scenario analyses incorporating geopolitical disruptions, such as the Russian coal sanctions, provide quantitative insights into the trade-offs between policy interventions and emission reduction objectives. Extending projections to 2050 under various demand trajectories yields cumulative emission reductions of 35–70 Mt CO2eq (an average of 53 Mt), representing additional mitigation beyond the 230 Mt of reductions identified in prior research. These findings demonstrate that mathematical optimisation can deliver near-term environmental benefits without requiring capital-intensive technological breakthroughs, thereby supporting global climate mitigation targets.