Maritime transportation is an essential pillar of modern societies, serving as the backbone of global trade. The shipping industry relies heavily on fossil fuels, significantly impacting the environment and contributing to climate change. The International Maritime Organization (IMO) has introduced a strategy to reduce greenhouse gas emissions from international shipping and decarbonize the industry to combat this issue. This strategy aims to accomplish energy efficiency gains, transition to alternative fuels, and implement market-based measures.
Various energy efficiency indicators are in use to monitor the performance of ships, both from technical and operational perspectives. Building upon previous research that identified shortcomings in these indicators, this thesis investigates alternative methods of assessing the energy efficiency of ships. Emphasizing the importance of a benchmarking tool, the primary objective of this thesis is to contribute to the policy debate on reducing emissions in international shipping by developing a comprehensive carbon intensity indicator.
The thesis comprises four articles addressing various approaches to monitoring ship carbon emissions. The first article focuses on the influence of weather conditions on a ship’s energy efficiency, thereby contributing to the ongoing discussion on weather correction factors. Using model-based machine learning techniques, this article illustrates the diverse sea conditions encountered, their impact on energy efficiency, and the necessity of accounting for this diversity through multiple correction factors.
The second and third articles introduce and develop the concept of operational cycles for maritime transportation, drawing inspiration from the driving cycles employed in the automotive industry. The second article describes the process of generating operational cycles for the maritime sector as a novel concept. It validates this concept using real-world data obtained from a fleet of container ships. Building upon this foundation, the third article extends the concept by elaborating more comprehensive cycles that better represent real-world indicators.
The fourth article explores voluntary reporting frameworks in the shipping industry. It focuses on the Clean Cargo case and investigates the needs and interests of its members regarding this private initiative and related reporting framework. The discussion revolves around the role of these voluntary frameworks as complementary approaches to regulatory frameworks towards maritime decarbonization.
Based on the methodology developments and analysis through the thesis, the following key findings and recommendations are presented:
• The weather impact on ships’ fuel consumption prevents an accurate and real assessment of ships’ efficiency. Multiple weather correction factors for energy efficiency indicators introduce a novel approach.
• Inspired by the automotive industry, maritime operational cycles improve the assessment of technical and operational aspects of a ship’s energy efficiency. The cycles reduce the variability inherent to energy
efficiency indicators and are suitable as benchmarking tools.
• Although the IMO regulatory framework remains at the core of the maritime decarbonization strategy, regional regulatory frameworks and private initiatives have demonstrated their capacity to enhance industry
practices and facilitate regulatory developments.
This thesis contributes to enhancing carbon emissions monitoring in the maritime industry by introducing new methodologies and assessments. The resulting proposals are designed to enrich ongoing discussions within the IMO and complement the existing regulatory frameworks.
Policy makers often need support for evaluating transportation and logistics system performance, and for understanding the long-term effects and relationships between transportation investments, system performance and economic growth, both at the regional and national levels (Banister and Berechman, 2001; Laird and Venables, 2017). The economic evaluation of system performance, risks and barriers come paradigmatically together during the processes of transport systems investment choice decision
Manufacturing companies who ship goods globally often rely on external Logistics Service Providers (LSPs) to manage the containerization and transportation of their freight. Those LSPs are usually required to follow rules when deciding how to mix the goods in the containers, which complicates the planning task. In this paper, we study such a freight containerization problem with a specific type of cargo mixing requirements recurrently faced by an international LSP. We show that this problem can be formulated as a Multi-Class Constrained Variable Size Bin Packing Problem: given a set of items that all have a size and a fixed number of classes for which they can take certain values, the objective is to pack the items in a minimum-cost set of bins while ensuring that the size capacity and maximum number of distinct values per class are not exceeded in any of the bins. We propose two adapted and one novel greedy heuristics, as well as an Adaptive Large Neighborhood Search (ALNS) metaheuristic, to find feasible solutions to the problem. We also provide a pattern-based formulation that is used to obtain lower bounds using a Column Generation approach. Using three extensive datasets, including a novel one with up to 1000 items and 5 classes reflecting real industrial cases, we show that the novel greedy heuristic outperforms the adaptations of the existing ones and that our ALNS yields significantly better solutions than a commercial solver within a mandatory 5-minute time limit. Practical insights are given about the solutions for the industrial benchmark.
In this study, the periodic train timetabling problem is formulated using a time-space graph formulation that exploits the properties of a symmetric timetable. Three solution methods are proposed and compared where solutions are built by what we define as a dive-and-cut-and-price procedure. An LP relaxed version of the problem with a subset of constraints is solved using column generation where each column corresponds to the train paths of a line. Violated constraints are added by separation and a heuristic process is applied to help to find integer solutions. The passenger travel time is computed based on a solution timetable and Benders’ optimality cuts are generated allowing the method to integrate the routing of the passengers. We propose two large neighborhood search methods where the solution is iteratively destroyed and repaired into a new one and one random iterative method. The problem is tested on the morning rush hour period of the Regional and InterCity train network of Zealand, Denmark. The solution approaches show robust performance in a variety of scenarios, being able to find good quality solutions in terms of travel time and path length relatively fast. The inclusion of the proposed Benders’ cuts provide stronger relaxations to the problem. In addition, the graph formulation covers different real-life constraints and has the potential to easily be extended to accommodate more constraints.
In the European Union, Maritime Spatial Planning (MSP) has been regarded as a means of promoting the sustainable growth of the blue economy. Consequently, where the planning outcomes affect the business operations in marine areas, commercial and industry stakeholders should have an important role in the planning process. However, the business perspective in MSP has gained little attention in stakeholder involvement literature. The aim of this study is to elaborate on the business sector's interest and involvement in MSP in the Baltic Sea region. The findings are based on the first-hand experiences of MSP authorities and experts. Furthermore, perspectives from two sea-use sectors, maritime transport and marine tourism, have been investigated using online questionnaires to discover their views. The study focuses on the questions of who to involve and what are the driving forces promoting business sector involvement. Even though MSP is a form of broad-scale planning, the results indicate that all spatial and organizational scales from local to international and from small enterprises to umbrella organizations should be considered when designing approaches to business stakeholder participation. The planning authorities need to consider what are the benefits and challenges of involving different types of business stakeholders. Planners often rely on organizations that represent business stakeholders and individual companies. It is resource effective to interact with representatives as they are considered to have a broad and general knowledge of the respective sector's interests. However, in some cases it is beneficial to also integrate individual companies, especially in local or regional contexts.
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.
This report provides public recommendations for waterborne transport to West Coast of Norway, with the focus on the specified transport system in use case A in the AEGIS project. The complete background for this report is only achieved by reading all the other deliverables related to the use case, however these are confidential. Therefore, it is recommended to read the ICMASS 2022 paper "Development of an advanced, efficient and green intermodal system with autonomous inland and short sea shipping – AEGIS"1 to get a better overview of the project and specifically use case A. The transport system of use case A consists of mother vessel(s) together with one or more daughter vessels, connected by several ports. The mother vessel transports containers from Rotterdam via Hitra Kysthavn and into ports in the Trondheimsfjorden. The rationale for this use case is to enable a more flexible and cost-efficient waterborne transport solution for fjords and smaller ports.
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.
Studies have indicated that transportation noise is associated with higher cardiovascular mortality, whereas evidence of noise as a risk factor for respiratory and cancer mortality is scarce and inconclusive. Also, knowledge on effects of low-level noise on mortality is very limited. We aimed to investigate associations between road and railway noise and natural-cause and cause-specific mortality in the Danish population. We estimated address-specific road and railway noise at the most (LdenMax) and least (LdenMin) exposed façades for all residential addresses in Denmark from 1990 to 2017 using high-quality exposure models. Using these data, we calculated 10-year time-weighted mean noise exposure for 2.6 million Danes aged >50 years, of whom 600,492 died from natural causes during a mean follow-up of 11.7 years. We analyzed data using Cox proportional hazards models with adjustment for individual and area-level sociodemographic variables and air pollution (PM2.5 and NO2). We found that a 10-year mean exposure to road LdenMax and road LdenMin per 10 dB were associated with hazard ratios (95% confidence intervals) of, respectively, 1.09 (1.09; 1.10) and 1.10 (1.10; 1.11) for natural-cause mortality, 1.09 (1.08; 1.10) and 1.09 (1.08; 1.10) for cardiovascular mortality, 1.13 (1.12; 1.14) and 1.17 (1.16; 1.19) for respiratory mortality and 1.03 (1.02; 1.03) and 1.06 (1.05; 1.07) for cancer mortality. For LdenMax, the associations followed linear exposure-response relationships from 35 dB to 60–<65 dB, after which the function levelled off. For LdenMin, exposure-response relationships were linear from 35 dB and up, with some levelling off at high noise levels for natural-cause and cardiovascular mortality. Railway noise did not seem associated with higher mortality in an exposure-response dependent manner. In conclusion, road traffic noise was associated with higher mortality and the increase in risk started well below the current World Health Organization guideline limit for road traffic noise of 53 dB.