RISK-INFORMED NET-ZERO PATHWAYS FOR CONTAINER VESSELS

Kurzfassung

The maritime industry is in the midst of an unprecedented challenge: delivering a goal of netzero greenhouse gas emissions by 2050, while maintaining economic competitiveness in the face of profound uncertainty in fuels, technology, and changing regulatory environments. Current investment studies are based primarily on deterministic lifecycle cost models, which produce single-point estimates, not addressing the downside risk exposure for operators making multi-decade capital investment commitments. This thesis fills this knowledge gap with the development of a probabilistic Monte Carlo simulation methodology for the evaluation of four decarbonization strategies: Conventional MDO Efficiency (A), LNG Transitional (B), Hybrid Electric (C), and Methanol as Fuel (D), for a fleet of six Neo-Panamax container vessels on a Singapore to Rotterdam route over a 15-year period from 2025 to 2040. The results of this research demonstrate that Pathway C: Hybrid Electric results in the least negative NPV and the minimum LCOT for all six vessels, showing First-Order Stochastic Dominance over all alternative pathways for all vessels. Pathway D: Methanol results in the highest expected cost and worst downside risk under the assumed green fuel price uncertainties. Sensitivity analysis indicates that fuel price uncertainties, rather than CAPEX uncertainties, dominate the uncertainties in the NPV results for all pathways, while the EU ETS carbon pricing was found to be universally relevant in the second position. The proposed framework contributes to the investment decision-making in maritime decarbonisation investments in that deterministic cost projections are replaced with risk-disaggregated pathway results, providing risk-averse maritime operators, financiers, and policymakers with relevant decision-support information