At the 79 th Marine Environment Protection Committee in December 2022, it was discussed to combine regulatory measures and market-based measures (MBMs) for decarbonization in the international maritime transport. In this study, the evaluation of Feebate is focused on, which is an MBM proposed by Japan. This institute has the challenge that the carbon dioxide (CO2) emissions to be reduced are not definitive, and it is not easy to make accurate future projections by top-down simulation. In this study, therefore, future CO2 emissions from the international maritime transport with Feebate are simulated by multi-agent simulation to help the policy maker effectively reduce the emissions. Furthermore, it is analyzed what kind of agent behavior affects the CO2 emissions. The simulator developed in this study is a multi-agent simulator that uses multiple agents to imitate the decision-making processes of real shipping companies. Feebate is modeled as the differences of fuel prices among heavy fuel oil (HFO), liquified natural gas (LNG) and ammonia, and as the ratio of fuel consumptions among these fuels. Case studies are conducted by varying the degree of the fee for the fossil fuels, and the starting year of Feebate. The simulation results suggests that Feebate encourages shipping companies to switch from HFO-fueled vessels and LNG-fueled vessels to ammonia-fueled vessels, and the slow start of Feebate makes it difficult to reduce CO2 emissions, even with a stronger fee, which causes unnecessarily cut into shipping companies' profits.

The International Maritime Organization (IMO) is pursuing reductions in greenhouse gas (GHG) emissions from international maritime transport. This paper presents a comprehensive review of simulation studies on IMO’s GHG measures, summarizing their simulation models and key components used. Our analysis reveals that these studies frequently rely on diverse assumptions that are often insufficiently documented, making it challenging to compare simulation results across studies. To address this critical issue, we propose a harmonized framework for maritime simulation models based on the review and findings. This framework provides structured variables and normalized units across domains, including demand, port operations, vessel characteristics, and fuel types, which the reviewed articles often assumed. The proposed framework is validated by an application example showing comparable tables of assumptions adopted by two different simulation studies. We anticipate that this framework will enable researchers to clearly present structured assumptions in their manuscripts, thereby enhancing readers’ understanding of assumptions and facilitating more efficient comparisons of simulation results across the field.