Dynamic Total Cost of Ownership Assessment of Methanol Dual-Fuel Container Ships in the Ningbo–Zhoushan–Valencia Green Shipping Corridor

Green methanol is widely regarded as a technically feasible low-carbon marine fuel for sustainable shipping in the medium term, but its economic viability remains constrained by fuel price and supply-scale uncertainty. This study develops a dynamic total cost of ownership (TCO) model for a methanol dual-fuel container ship with a nominal capacity of 15,000 twenty-foot equivalent units (TEUs) operating on the Ningbo–Zhoushan–Valencia green shipping corridor. The model integrates capital expenditure, operating expenditure, fuel costs, European Union Emissions Trading System (EU ETS) carbon costs, FuelEU Maritime compliance costs, and green premium revenue. It evaluates a 15-year baseline, 25- and 30-year extensions, speed scenarios, probabilistic parameter uncertainty, and purchase-versus-charter thresholds. Under baseline assumptions (carbon price of 73.5 EUR/tCO2 and green methanol price of 1500 USD/t), the 15-year present-value cost of the green methanol case is 134.4% higher than that of the very low sulfur fuel oil (VLSFO) case. Annual costs may cross in 2045, 2040, and 2037 under baseline, optimistic, and accelerated decarbonization scenarios, respectively, but cumulative discounted cost advantage is not achieved within 30 years. Across 5000 Monte Carlo simulations, the probability of cumulative methanol cost advantage is 0% at 15, 25, and 30 years; methanol price and its decline rate remain the dominant uncertainty drivers. Slower speeds reduce the absolute cost gap but do not reverse the fuel ranking. These results show that carbon pricing or green premium revenue alone cannot close the corridor-level cost gap under the tested conditions. They also provide corridor-level evidence for methanol procurement, bunkering-capacity planning, and coordination among ship operators, ports, fuel suppliers, and cargo owners. Shipowners and port planners can update the framework as fuel prices, policy parameters, and bunkering conditions change.