The purpose of this paper is to assess the status and prospects of the decarbonization of maritime transport. Already more than two years have passed since the landmark decision of the International Maritime Organization (IMO) in April 2018, which entailed ambitious targets to reduce greenhouse gas (GHG) emissions from ships. The paper attempts to address the following three questions: (a) where do we stand with respect to GHG emissions from ships, (b) how is the Initial IMO Strategy progressing, and (c) what should be done to move ahead? To that effect, our methodology includes commenting on some of the key issues addressed by the recently released 4th IMO GHG study, assessing progress at the IMO since 2018, and finally identifying other issues that we consider relevant and important as regards maritime GHG emissions, such as for instance the role of the European Green Deal and how this may interact with the IMO process. Even though the approach of the paper is to a significant extent qualitative, some key quantitative and modelling aspects are considered as well. On the basis of our analysis, our main conjecture is that there is not yet light at the end of the tunnel with respect to decarbonizing maritime transport.
The literature on liner shipping includes many models on containership speed optimization, fleet deployment, fleet size and mix, network design and other problem variants and combinations. Many of these models, and in fact most models at the tactical planning level, assume a fixed revenue for the ship operator and as a result they typically minimize costs. This treatment does not capture a fundamental characteristic of shipping market behavior, that ships tend to speed up in periods of high freight rates and slow down in depressed market conditions. This paper develops a simple model for a fixed route scenario which, among other things, incorporates the influence of freight rates, along with that of fuel prices and cargo inventory costs into the overall decision process. The objective to be maximized is the line’s average daily profit. Departing from convention, the model is also able to consider flexible service frequencies, to be selected from a broader set than the standard assumption of one call per week. It is shown that this may lead to better solutions and that the cost of forcing a fixed frequency can be significant. Such cost is attributed either to additional fuel cost if the fleet is forced to sail faster to accommodate a frequency that is higher than the optimal one, or to lost income if the opposite is the case. The impact of the line’s decisions on CO2 emissions is also examined and illustrative runs of the model are made on three existing services.