The ‘port managing body (PMB)’ plays a central role in the development of the port. Public funding for investment projects of the port managing bodies is common in the EU as well as most other countries. This paper adds to the body of knowledge on port investments and financing challenges with an analysis of data from two surveys that were carried in 2018 and 2023. This analysis yields the following conclusions. First, the PMBs in the EU have shifted their investments, in response to changing investment drivers. The increasing relevance of the transition to a net-zero economy leads to a shift towards investments in projects that reduce environmental effects and/or allow private investments in new green activities such as the production of zero-emission fuels. Second, financial bottlenecks are the most important bottlenecks for the execution of the projects of PMBs. Third, the PMBs have high aspirations with regard to public funding, both on the EU and national level. Fourth, there is a difference between two types of PMBs: state-owned commercial port development companies and the public sector embedded port authorities; the latter execute less projects without public funding and are more oriented on national public funding than on EU funding. Finally, the societal value creation of the investments of PMBs is used to justify public funding aspirations. The PMBs indicate that the majority of their investments create societal value, often by enabling emission reductions and by reduced local negative externalities.
Hydrogen-electricity integrated multi-energy systems are promising approaches to reduce carbon emissions in ports. However, the stochastic nature of renewable energy and the imbalance between the renewable generation and load demand in ports necessitate the design of an appropriate coupled hydrogen-electricity energy storage systems (CHEESS). This paper proposes a multi-objective optimization model for CHEESS configuration in random unbalanced port integrated multi-energy systems (PIMES), aiming to minimize its life-cycle cost and carbon emissions through co-optimization of sizing and energy management. A hierarchical two-stage framework is proposed to solve the multi-objective model. The proposed optimization framework is applied to a real PIMES at the Ningbo-Zhoushan Port. The results show that the proposed method can save 10.54% of the monetary cost and 19.67% of carbon emissions over the entire life-cycle of the system. The study demonstrates that the proposed framework has the potential to generate significant economic and environmental benefits and provides a feasible solution for port authorities seeking to implement CHEESS, aiming to promote sustainability in port operations.
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.
International shipping is at a crossroads as regards decarbonization. The Paris climate change agreement in 2015 (COP21) was hailed by many as a most significant achievement. Others were less enthusiastic, and more recently American President Trump decided to take the U.S. out of the agreement. Four years earlier, the International Maritime Organization (IMO) had adopted the most sweeping piece of regulation pertaining to maritime greenhouse gas (GHG) reduction, in the name of the Energy Efficiency Design Index (EEDI). In addition, one year after COP21, the IMO adopted a mandatory data collection system for fuel consumption of ships and agreed on an initial strategy and roadmap on the reduction of GHG emissions from ships. This paper takes a critical look at the above and other recent developments and focuses on the challenges faced by the industry if a path to significant CO2 reductions is to be successful. Difficulties and opportunities are identified, and the paper conjectures that the main obstacles are neither technical nor economic, but political.
The International Maritime Organization (IMO) is a specialized United Nations (UN) agency regulating maritime transport. One of the very hot topics currently on the IMO agenda is decarbonization. In that regard, the IMO decided in 2018 to achieve by 2050 a reduction of at least 50% in maritime green house gas (GHG) emissions vis-à-vis 2008 levels. The purpose of this paper is to discuss the possible role of Market Based Measures (MBMs) so as to achieve the above target. To that effect, a brief discussion of MBMs at the IMO and the EU is presented, and a possible way forward is proposed, focusing on a bunker levy.
Global marine shipping annually accounts for about one billion tonnes of CO2 equivalent greenhouse gas emissions. Nuclear power propulsion may be an option to de-carbonise some niches of the merchant ocean fleet. This paper considers the three experimental nuclear-powered merchant ships launched and operated in the world so far; the iconic Savannah (USA), Otto Hahn (West Germany) and Mutsu (Japan). They were independently developed and operated in the 1960s and 1970s for technology demonstration and learning. A fourth ship, Sevmorput (Soviet Union/Russia, 1988–to date), is a pioneer in respect of its logistics functions and propulsion system. This paper develops a theoretical framework for the sustainability assessment of nuclear propulsion in ocean merchant shipping and presents a method for exploring nuclear propulsion, relative to flag state, ports, shipping resources and ocean transport services. The experimental ships’ transport efficiency is discussed and related to contemporary oil-fired shipping of general cargo, and to recent literature presenting possible future applications of merchant nuclear propulsion in some market niches. Insights provided include: (1) the experiments demonstrate that merchant nuclear propulsion may be technically feasible; (2) port and canal access for merchant nuclear-powered ships may be difficult and restricted; (3) the up-front costs, refuelling and end-of-life decommissioning costs of nuclear-powered ships are vast and uncertain against conventionally-powered ships; (4) because nuclear fuel is comparatively low-cost, the conventional oil-fired ship cost implications of high-speed operations do not apply.
The maritime industry is a crucial hard-to-abate sector that is expected to depend on high-energy density renewable liquid fuels in the future. Traditionally, decarbonization pathways have been assessed assuming exogenous cost trajectories for renewable liquid fuels based on an exogenous learning curve. While past studies have looked at the impact of endogenizing learning curves for a specific technology utilizing linear approximation, a fully endogenous direct non-linear implementation of learning curves in a detailed sectoral model (maritime industry) that explores dynamics concerning sensitive parameters does not yet exist. Here, we apply an open-source optimization model for decarbonizing the maritime industry and further develop the model by encompassing a nonconvex mixed-integer quadratically constrained programming approach to analyze the impact of endogenized learning curves for renewable fuel costs following an experience curve approach. We find that global greenhouse gas emissions are significantly lower (up to 25% over a 30 year horizon) when utilizing endogenously modeled prices for renewable fuels compared to commonly used exogenous learning frameworks. Furthermore, we find that conventional modeling approaches overestimate the cost of climate mitigation, which can have significant policy implication related to carbon pricing and fuel efficiency requirements. In a broader context, this emphasizes the potential opportunities that can be achieved if policymakers and companies accelerate investments that drive down the costs of renewable technologies efficiently and thus trigger endogenous experience-based learning in real life.
Global climate change, which is largely attributed to human activity, is one of the foremost challenges of the 21st century. In recent times, there have been notable alterations in the Earth's climate, resulting in profound impacts on ecosystems and biodiversity. These alterations are caused by greenhouse gas, such as carbon dioxide, methane, and nitrous oxide. Greenhouse gas emissions are caused by practices such as deforestation, industrial operations, and the combustion of fossil fuels in vehicles, vessels, aircraft, and manufacturing facilities. The maritime and aviation industry is currently responsible for approximately 6% of global greenhouse gas emissions. Due to logistical and economic constraints, these industries are heavily reliant on liquid fuels, making direct electrification options unavailable for large parts of these sectors. As a result, these sectors are considered ‘hard to abate’. Understanding the future climate mitigation challenges associated with the maritime and aviation sectors is crucial in shaping effective policy measures, avoiding stranded assets, and preserving the chance to meet Paris Agreement-compatible emission reduction pathways.
This thesis identifies three main challenges and proposes modelling approaches to address them when modelling decarbonization pathways for the aviation and maritime sectors. From these challenges, research gaps have been identified that this PhD thesis aims to fill. Three models have been developed for the thesis: a maritime optimization model, a maritime demand model, and an aviation demand model. The modelling landscape and methodology vary across models, ranging from econometrics and data science to mathematical optimization.
To overcome the challenges and fill in the research gaps, three corresponding modelling approaches have been successfully applied:
1. Developing a holistic decarbonization modelling landscape. This includes life-cycle representations of technology costs and emissions, the upscaling of bottleneck technologies, the availability of sustainable biomass, and consideration of competing demand from other industries, as well as representations of policy levers such as carbon pricing or improvements to fuel efficiency.
2. Developing demand models that interpret the underlying scenario narrative consistently (SSP framework).
3. Improving the representation of technological learning for low-carbon technologies in energy system models.
The findings acquired by applying these three modelling approaches are valuable for energy modellers, climate scientists, and policymakers and offer unique insights into the inherent system dynamics associated with decarbonization of hard-to-abate sectors. Utilizing this modelling landscape reveals that current decarbonization efforts for hard-to-abate sectors are insufficient.
This report is a background report to the MarE-Fuel project financed by the Maritime Fund and the Lauritzen Fund. Partners of the project has been DTU, Anker Invest, Mærsk Line, Copenhagen Economics, OMT and DFDS. In the report, potential decarbonization roadmaps or pathways for the maritime industry are presented, as well as the methodology of deriving them. Different future fuels and their emissions are highlighted. In addition, biomass availability plays an essential role in climate mitigation efforts towards net-zero by 2050, and thus we examined different biomass availability scenarios alongside greenhouse-gas emissions cap scenarios. The assumptions related to the underlying emissions can be found in the first chapter of the report. Besides the underlying emissions for a decarbonized maritime industry, the ship stock and the underlying transport demand play an essential role for a future decarbonized maritime industry. In the second chapter of the report, we address this issue by explaining how ship stock and shipping demand have been incorporated into the model. Finally, we present the optimization ship stock model developed to generate roadmap scenarios. We show the objective function and the underlying constraints of the model. The results of this work are presented and discussed. We also show some sensitivity analysis, which will shed light on the relevant parameters for the futureof the maritime industry. Our main findings can be found in the end of the report.
Adopting green vehicles in the transport sector is a highly effective policy for mitigating the sector’s carbon footprint. Moreover, the EU transport policy acknowledges the pivotal role of inland waterways (IWW) in decarbonizing Europe, with a strategic objective to enhance its modal share through the transition from road to IWW. This paper investigates the potential of electric autonomous Roll-on Roll-off (RoRo) ships to enhance the competitive edge of IWW as compared to road transport. This paper examines the impact of this innovative transport system on sustainability by analyzing Key Performance Indicators (KPIs) across economic and environmental dimensions using a comparative case study approach and quantitative analysis data. The main result is that implementing electric autonomous RoRo ships can lead to a 45 % reduction in OPEX (operational expenditure), with profitability expected after about 3.5 years. Emissions decrease by more than 60 %, and by 2030, CO2 emissions in the Well-to-Wake (WTW) cycle are projected to reduce by approximately 77,000 tonnes, aligning with EU transport and environmental policies.