Pressure-aware multi-modal CO2 transport planning for industrial decarbonization: A case study of Germany's steel sector to 2050

Multi-modal CO 2 transport networks involve coupled decisions on operating pressure, mode-switching equipment, and infrastructure deployment timing, yet existing optimization studies typically treat the associated compression, liquefaction, and heat exchange as post-processing assumptions. This study develops a pressure-aware mixed-integer linear programming framework for multi-modal CO 2 transport planning that couples mode selection with pressure-state-dependent conditioning, allowing pressure regimes and mode transitions to be optimized jointly. The framework integrates phased deployment across three time horizons (2030, 2040, 2050) under three decarbonization pathways, carbon pricing for uncaptured emissions, and selective reuse of existing pipelines within a single optimization. Seven mode-pressure variants are considered, with mode-transition costs derived from a 49-transition simulation matrix. The framework is applied to twelve major German steel emitters connected to the Northern Lights offshore storage site via three candidate ports. The cost-optimal network shifts from truck-and-rail logistics in the early, low-volume stage to a dense-phase pipeline backbone as captured volumes grow. Unit transport costs remain within 15–18 €/tCO 2 across the scenarios. The marginal cost of expanding transport and conditioning capacity stabilizes at 13–14 €/tCO 2 from 2040 onward. These figures indicate that transport is not the binding economic constraint on scaling up capture ambition, rather than that CCUS as a whole is inexpensive. Existing pipeline reuse is found to be capacity- and stage-dependent: sufficiently large reused assets can reduce new-build requirements. The framework offers a transferable approach for cleaner industrial logistics design, supporting the transition to low-carbon hard-to-abate sectors in Europe and beyond.