A fast simulation method for the probabilistic assessment of emissions in cruise ship’s itinerary planning

This study employs a probabilistic methodology to forecast cruise ship emissions during the itinerary planning phase, considering environmental factors (current, waves, wind), fouling, shallow water, loading conditions, and Fresh Water (FW) production effects. Probability distributions of environmental parameters are established based on statistical data and utilized for generating deterministic scenarios through Monte Carlo sampling. The resulting scenarios are simulated to define probability distributions for carbon dioxide emissions, carbon intensity indicators, and other pertinent quantities. The simulation model is validated using data from an existing ship. To demonstrate the effectiveness of the proposed methodology in strategic itinerary planning, multiple alternatives for an existing itinerary are simulated. Specifically, a Mediterranean cruise is simulated in both the original sequence and in reverse, with and without FW production. The reverse sequence without FW production demonstrates a potential reduction of approximately 190 tCO2e/week emissions. Furthermore, in this scenario, a comparison is made between a standard Power Management System (PMS) with an equal load on all engines and an optimized PMS with optimized engine loads, resulting in an additional average reduction of 86 tCO2e. In the latter itinerary, the most probable rating according to Carbon Intensity Indicator is reduced from original E to C.