Slow steaming is being practised in many sectors of the shipping industry. It is induced principally by depressed shipping markets and/or high fuel prices. In recent years the environmental dimension of slow steaming has also become important, as ship emissions are directly proportional to fuel burned. The purpose of this chapter is to examine the practice of slow steaming from various angles. In that context, a taxonomy of models is presented, some fundamentals are outlined, the main trade-offs are analysed, and some decision models are presented. Some examples are finally presented so as to highlight the main issues that are at play.
This paper explores the potential of using green, autonomous ships in revitalizing inland shipping in Europe against the backdrop of declining market share and the dominance of "economy-of-scale" in waterborne freight transportation. It assesses the economic and environmental viability of converting freight from road to waterborne modalities in broader business ecosystems, specifically along the Rotterdam-Ghent corridor. The analysis leverages operational and commercial insights from logistics firms, ports and terminal operators, combined with data on European goods flows by road, and accounts for operational, financial and environmental variables including realistic scenario building and ecosystem implications. Findings indicate that inland shipping in general and green, autonomous shipping in particular offer both economically and environmentally viable alternatives to road transport. The study calls for further research into green, autonomous ships from an ecosystem perspective as a potential solution to current challenges in sustainable freight transportation.
Maritime transport carries around 80% of the world’s trade. It is key to the economic development of many countries, it is a source of income in many countries, and it is considered as a safe and environment friendly mode of transport. Given its undisputed importance, a question is what does the future hold for maritime transport. This chapter is an attempt to answer this question by mainly addressing the drive to decarbonize shipping, along with related challenges as regards alternative low carbon or zero carbon marine fuels. The important role of maritime policy making as a main driver for change is also discussed. Specifically, if maritime transport is to drastically change so as to meet carbon emissions reduction targets, the chapter argues, among other things, that a substantial bunker levy would be the best (or maybe the only) way to induce technological changes in the long run and logistical measures (such as slow steaming) in the short run. In the
long run this would lead to changes in the global fleet towards vessels and technologies that are more energy efficient, more economically viable and less dependent on fossil fuels than those today. In that sense, it would have the potential to drastically alter the face of maritime transport in the future. However, as things stand, and mainly for political reasons, the chapter also argues that the adoption of such a measure is considered as rather unlikely.
This report presents the results of Activity 3.2-2 of the Scandria®2Act project. It investigates the sensitivity of the Ro-Ro services along the Scandria® corridor to fuel cost fluctuations, anticipates the adverse effects of a possible fuel price hike and discusses potential mitigating measures.
Among the 77 Ro-Ro services that include at least one direct connection between two Baltic ports, the Finland-Germany connections were selected for further examination mainly because this is where the ScanMed and NSB core network corridors meet providing two major alternatives, each of which offer at least two options. In terms of abatement options available to the Ro-Ro operators, the study considers only the switching from Heavy Fuel Oil (HFO) to the compliant but more expensive Marine Gas Oil (MGO), which happens to be the only feasible solution in the short-run that does not require a substantial capital investment.
The study deployed two different approaches in meeting its objectives. The first one looked at the problem from the macro-level perspective and the analysis was based on aggregate annual statistics of the ports serving the Finland-Germany connections. A multiple regression model estimated the sensitivity of cargo flows to fuel price fluctuations. Although most of the cargo volumes exhibit a statistically significant sensitivity to fuel price, in all cases this is below 1.0, indicating a rather inelastic
behaviour. The results show that an increase in fuel price penalises the volume of lorries on the longdistance Helsinki-Germany route in favour of the shorter Helsinki-Tallinn and Hanko-Germany options. The trailer (unaccompanied) traffic exhibit a different behaviour that might relate to the pricing policies of the Ro-Ro operators in relation to this market segment.
The Belt and Road Initiative (BRI) entails investments to improve overland (rail) transport between Europe and China. This paper introduces a microscopic Multi-Commodity Flow Service Selection Problem for freight transport under the BRI and provides a decision tool for shippers to make door-to-door service plans. The minimizing objective function considers transportation costs, in-transit inventory costs, and carbon emissions. A series of sampled data of each provincial region of China are collected from Chinese multimodal transport operators. Results show that inland regions are strongly attracted to the rail mode for shipments to Europe. However, the “last mile” (including “first mile”) transport from the shipper to the long-haul transport terminal strongly influences this choice, and carbon emissions are strongly influenced by the available last mile transport links. Under the dual impact of in-transit inventory and carbon emission costs, regions that prefer rail to maritime are much further east than suggested by previous literature.
This paper addresses the fleet renewal problem and particularly the treatment of uncertainty in the maritime case. A stochastic programming model for the maritime fleet renewal problem is presented. The main contribution is that of assessing whether or not better decisions can be achieved by using stochastic programming rather than employing a deterministic model and using average data. Elements increasing the relevance of uncertainty are also investigated. Tests performed on the case of Wallenius Wilhelmsen Logistics, a major liner shipping company, show that solutions to the model we present perform noticeably better than solutions obtained using average values.