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.
The activities and emissions from leisure boats in the Baltic Sea have been modeled in a comprehensive approach for the first time, using a new simulation model leisure Boat Emissions and Activities siMulator (BEAM). The model utilizes survey data to characterize the national leisure boat fleets. Leisure boats have been categorized based on their size, use and engine specifications, and for these subcategories emission factors for NOx, PM2.5, CO, non-methane volatile organic compounds (NMVOCs), and releases of copper (Cu) and zinc (Zn) from antifouling paints have been estimated according to literature values. The modeling approach also considers the temporal and spatial distribution of leisure boat activities, which are applied to each simulated leisure boat separately. According to our results the CO and NMVOC emissions from leisure boats, as well as Cu and Zn released from antifouling paints, are significant when compared against the emissions originating from registered commercial shipping in the Baltic Sea. CO emissions equal 70 % of the registered shipping emissions and NMVOC emissions equal 160 % when compared against the modeled results in the Baltic Sea in 2014. Modeled NOx and PM2.5 from the leisure boats are less significant compared to the registered shipping emissions. The emissions from leisure boats are concentrated in the summer months of June, July and August and are released in the vicinity of inhabited coastal areas. Given the large emission estimates for leisure boats, this commonly overlooked source of emissions should be further investigated in greater detail.
In this work, three-dimensional computational fluid dynamics (CFD) studies of sulphur oxides (SOx) and sulphuric acid (H2SO4) formation processes in a large, low speed two-stroke marine diesel engine are carried out. The current numerical study aims to investigate the conversion of sulphuric dioxide (SO2) to sulphuric trioxide (SO3) and the possibility of H2SO4 condensation which are the prerequisites to better understand the corrosion-induced wear phenomenon. This is achieved with the aid of the implementation of a multicomponent surrogate model, which comprises a skeletal n-heptane mechanism and a reduced sulphur subset mechanism. In the present work, performance of the coupled CFD-chemical kinetic model is evaluated using both qualitative and quantitative methods. The modelling results show that the temporal and spatial evolutions of SOx predicted by the skeletal model are similar to those by the base mechanism. Predictions of the variations of SOx and the associated SO2 to SO3 conversion in response to the change of fuel sulphur content, swirl velocity, start of injection, scavenge pressure and humidity qualitatively agree with numerical and experimental results from the literature. The model is further evaluated using the measured SO2 to SO3 conversion levels in a low load, low scavenge pressure case and a low load, high scavenge pressure case. The absolute values of simulated and measured conversion levels are close, although the former appear to be higher. The current results show that the flame impinges at the cylinder liner near top dead centre. The gas is cooled rapidly by the wall temperature and H2SO4 is produced in the region where the local temperature is less than 600 K. Based on the flue gas correlation, the acid dew point temperature is higher than the wall temperature, suggesting that acid condensation may begin early at the top part of the cylinder liner. The predicted distribution corresponds well with the distribution of corroded parts observed in service engines. The model is expected to serve as an important tool to simulate the rates of SO2 absorption into lubricating oil film and H2SO4 condensation in this combustion system.
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.
Aiming at reducing CO2 emissions from shipping at the EU level, a system for monitoring, reporting, and verification (MRV) of CO2 emissions of ships was introduced in 2015 with the so-called ‘MRV Regulation’. Its stated objective was to produce accurate information on the CO2 emissions of large ships using EU ports and to incentivize energy efficiency improvements by making this information publicly available. On 1 July 2019, the European Commission published the relevant data for 10,880 ships that called at EU ports within 2018. This milestone marked the completion of the first annual cycle of the regulation’s implementation, enabling an early assessment of its effectiveness. To investigate the value of the published data, information was collected on all voyages performed within 2018 by a fleet of 1041 dry bulk carriers operated by a leading Danish shipping company. The MRV indicators were then recalculated on a global basis. The results indicate that the geographic coverage restrictions of the MRV Regulation introduce a significant bias, thus prohibiting their intended use. Nevertheless, the MRV Regulation has played a role in prompting the IMO to adopt its Data Collection System that monitors ship carbon emissions albeit on a global basis.
The shipping sector's rising greenhouse gas emissions are often considered “hard-to-abate”. Some ship-owners have recently adopted or started to consider the adoption of alternative fuels, but systematic studies of this are still lacking. We address this gap by studying how ship-owners differ in both actual and intended adoption of alternative fuels. We analyze data from a unique survey with 281 ship-owners in Norway, a major ship-owning country and center for maritime technology development, with descriptive statistics and analysis of variance. We find early adopters among large and established ship-owners in offshore, international cargo and domestic passenger shipping segments, which are often subjected to specific contractual demands for alternative fuel adoption. Laggards were typically small and young ship-owners operating in shipping segments where demands for alternative fuel adoption are weak. Our findings also suggest that firms' business strategy and financial and knowledge resources may have relevance for ship-owner's adoption of alternative fuels. Our study has implications for national and international policymaking, highlighting for example how contracting mechanisms can be an effective tool in incentivizing the adoption of alternative fuels.
This paper deals with two speed optimization problems for ships that sail in and out of Emission Control Areas (ECAs) with strict limits on sulfur emissions. For ships crossing in and out of ECAs, such as deep-sea vessels, one of the common options for complying with these limits is to burn heavy fuel oil (HFO) outside the ECA and switch to low-sulfur fuel such as marine gas oil (MGO) inside the ECA. As the prices of these two fuels are generally very different, so may be the speeds that the ship will sail at outside and inside the ECA. The first optimization problem examined by the paper considers an extension of the model of Ronen (1982) in which ship speeds both inside and outside the ECA are optimized. The second problem is called the ECA refraction problem, due to its conceptual similarity with the refraction problem when light travels across two different media, and also involves optimizing the point at which the ship crosses the ECA boundary. In both cases the objective of the problem is to maximize daily profit. In addition to mathematical formulations, examples and sensitivity analyses are presented for both problems.
Operational cycles for maritime transportation is a new concept to improve the assessment of ships’ energy efficiency and offer benchmarking options among similar ship types and sizes. This work extends previous research to consolidate the methodology, bring more comprehensiveness, and provide a more holistic assessment of these operational cycles. The cycles are designed from noon reports from a fleet of around 300 container ships divided into eight size groups. The comparison between cycles derived from speed and draft with those based on main engine power identifies that the cycles based on speed and draft are more accurate and allow for estimating the Energy Efficiency Operational Index but require more data. The main-engine-power cycles are more effective in benchmarking through the Annual Efficiency Ratio. These cycles reduce the inherent variability of the carbon intensity indicator and present good opportunities as a benchmarking tool for strengthening the regulatory framework of international shipping.
Ship designers face increasing pressure to comply with global emission reduction ambitions. Alternative fuels, potentially derived from bio-feedstock or renewable electricity, provide promising solutions to this problem. The main challenge is to identify a suitable ship power system, given not only uncertain emission requirements but also uncertain fuel and carbon emission prices. We develop a two-stage stochastic optimization model that explicitly considers uncertain fuel and carbon emission prices, as well as potential retrofits along the lifetime. The bi-objective setup of the model shows how the choice of optimal power system changes with reduced emission levels. Methanol and LNG configurations appear to be relatively robust initial choices due to their ability to run on fuel derived from different feedstocks, and their better retrofittability towards ammonia or hydrogen. From a policy perspective, our model provides insight into the effect of the different types of carbon pricing mechanisms on a shipowner's decisions.
The design of emission control areas (ECAs), including ECA width and sulfur limits, plays a central role in reducing sulfur emissions from shipping. To promote sustainable shipping, we investigate an ECA design problem that considers the response of liner shipping companies to ECA designs. We propose a mathematical programming model from the regulator’s perspective to optimize the ECA width and sulfur limit, with the aim of minimizing the total sulfur emissions. Embedded within this regulator’s model, we develop an internal model from the shipping liner’s perspective to determine the detoured voyage, sailing speed, and cargo transport volume with the aim of maximizing the liner’s profit. Then, we develop a tailored hybrid algorithm to solve the proposed models based on the variable neighborhood search meta-heuristic and a proposition. We validate the effectiveness of the proposed methodology through extensive numerical experiments and conduct sensitivity analyses to investigate the effect of important ECA design parameters on the final performance. The proposed methodology is then extended to incorporate heterogeneous settings for sulfur limits, which can help regulators to improve ECA design in the future.