The International Maritime Organization (IMO) has recently adopted short-term measures introducing technical standards for existing ships and a labeling system reflecting their operational carbon intensity. This paper investigates the relevant techno-economic implications from a shipowner's perspective and estimates the effect of six compliance options on six sample containerships. The study applies a new evidence-based bottom-up approach, and the results show that compliance, when possible, is not straightforward and costly. Engine power limitation is the most cost-effective option, but low power limits can lead to substantially increased sailing times (up to 793.92 h/year), which can be prohibitive. The option favors older ships with oversized engines as its effectiveness is mainly determined by the main engine load profile. In general, the effectiveness of the measures is not without limits, particularly concerning older ships and those that have already installed several options. Solutions such as market-based measures and alternative fuels, classed by IMO as medium- and long-term measures, must be considered soon.
The International Maritime Organization (IMO) has recently adopted short-term measures introducing technical standards for existing ships and a labeling system reflecting their operational carbon intensity. This paper investigates the relevant techno-economic implications from a shipowner's perspective and estimates the effect of six compliance options on six sample containerships. The study applies a new evidence-based bottom-up approach, and the results show that compliance, when possible, is not straightforward and costly. Engine power limitation is the most cost-effective option, but low power limits can lead to substantially increased sailing times (up to 793.92 h/year), which can be prohibitive. The option favors older ships with oversized engines as its effectiveness is mainly determined by the main engine load profile. In general, the effectiveness of the measures is not without limits, particularly concerning older ships and those that have already installed several options. Solutions such as market-based measures and alternative fuels, classed by IMO as medium- and long-term measures, must be considered soon.
The oceans, covering approximately 70% of Earth's surface, play a pivotal role in climate regulation, biodiversity, and biogeochemical processes. The large and growing volume and complexity of ocean data, spanning diverse disciplines and formats, and dispersed across a wide range of sources, presents opportunities and challenges for advancing scientific research, informing policy, and addressing societal needs.
In this review paper we aim to create an easy-to-navigate map of the field of ocean data, enabling the reader to establish a broad understanding of the ocean data sector, and bridging gaps between different disciplines and levels of familiarity with ocean data. This is done through the concept of the "data ecosystem", which is used to describe the actors, organisations, and infrastructures involved in all aspects of the data value chain. We propose a structured ocean data ecosystem model as a method for comprehensive mapping of the ocean data market landscape. The proposed model consists of five key elements: stakeholders, societal elements, data sources and product offering, standards and best practices, and emerging technologies. We provide an up-to-date analysis of ocean data sources and emerging solutions and a summary of relevant data standardization efforts such as marine standards, vocabularies, and ontologies. All this will promote the development of needs-based solutions, components, products, services, and technologies, thus contributing to the evolution of the ocean data ecosystem and promoting data-based ocean research.
Nowadays, the coastal communities around the world face challenges related to increasing energy consumption, rising energy costs, enchaining of conventional or non-renewable energy resources, climate change, environmental problems, and so on. Therefore, many countries intend to implement different policies to develop clean energy production. There has been a new paradigm in policy from the utilization of greenhouse gases (GHGs), particularly CO2, toward sustainable energy resources to access a high level of security and reliability. This chapter discusses the new trends of hybrid marine power systems and analyzes various sustainable resources, such as PV, tidal turbines, and wind turbines. In addition, the applications of various battery systems to alleviate the randomness and unpredictable features of green energy resources have been studied. In this regard, the capability of various types of energy storage units, such as electrochemical, electromagnetic, and thermal, are presented. The restrictions and opportunities of combining the various technologies in the ship power systems have been investigated from both economic and environmental perspectives. Finally, the energy management problem of two case studies of sero-emissions ferry boats as a promising way to reduce GHGs is presented.
Flood risk assessment approaches have traditionally been dominated by measures of economic damage. However, the importance of understanding the social impacts of flooding are increasingly being acknowledged. Social vulnerability indices have been constructed in various geographical contexts to understand the relative susceptibility of different social groups to flood hazards. However, integrated assessments of social vulnerability, exposure, and hazard information are lacking. Here, we construct a national social vulnerability index (SVI) for Denmark and combine this with direct and indirect social exposure data and coastal flood hazard data to construct a national social flood risk index (SFRI). Results show the spatial distribution of social flood vulnerability and social flood risk in Denmark. Our findings illustrate that including social data in flood risk assessment could significantly change our understanding of flood risk on a national scale. Methodologically, our work introduces a comprehensive flood risk modeling approach that explicitly considers the social impacts of flooding in all model components. The application of this model in Denmark reveals that the social impacts of flooding extend far beyond flooded areas, thus highlighting the importance of explicitly considering direct and indirect social exposure in addition to social vulnerability in flood risk assessment. By introducing a comprehensive, socially specific approach to flood risk assessment that is usable within existing risk management frameworks such as the EU Floods Directive, our work aims to mainstream social wellbeing, resilience, and justice as central considerations in decision making on flood risk management.
To comply with regulations stated by the United Nation's International Maritime Organization, ballast water discharged by ships must be treated to avoid the spread of invasive organisms including algae. In this study, Raman spectroscopy and multivariate data analysis was used to make a Partial Least Squares Discriminant Analysis (PLS-DA) classification model for discrimination between viable (potential invasive) and UV exposed non-viable organisms. UV exposure is commonly used as a ballast water treatment strategy and a UV based exposure method was developed such that non-viable (and dying) algae consistently could be obtained. Raman spectra from both viable and UV treated algae of Rhodomonas salina and Tetraselmis suecica were measured. A PLS-DA model was obtained to form the normalized dataset, and Cross-Validated using Venetian blinds. Based on their individual Raman spectra, it was possible to obtain 100 % discrimination between the two algal species. The model classified 92 and 91 % of the viable algae correctly for R. salina and T. suecica, respectively, as opposed to 82 and 94 % for non-viable algae. In conclusion, in this proof of concept study, Raman spectroscopy was found to have a potential for algae species identification as well as discrimination between viable and non-viable algae.
The liner shipping industry is undergoing an extensive decarbonization process to reduce its 275 million tons of CO2 emissions as of 2018. In this process, the long-term solution is the introduction of new alternative maritime fuels. The introduction of alternative fuels presents a great set of unknowns. Among these are the strategic concerns regarding sourcing of alternative fuels and, operationally, how the new fuels might affect the network of shipping routes. We propose a problem formulation that integrates fuel supply/demand into the liner shipping network design problem. Here, we present a model to determine the production sites and distribution of new alternative fuels-we consider methanol and ammonia. For the network design problem, we apply an adaptive large neighborhood search combined with a delayed column generation process. In addition, we wish to test the effect of designing a robust network under uncertain demand conditions because of the problem's strategic nature and importance. Therefore, our proposed solution method will have a deterministic and stochastic setup when we apply it to the second-largest multihub instance, WorldSmall, known from LINER-LIB. In the deterministic setting, our proposed solution method finds a new best solution to three instances from LINER-LIB. For the main considered WorldSmall instance, we even noticed a new best solution in all our tested fuel settings. In addition, we note a profit drop of 7.2% between a bunker-powered and pure alternative fuel-powered network. The selected alternative fuel production sites favor a proximity to European ports and have a heavy reliance on wind turbines. The stochastic results clearly showed that the found networks were much more resilient to the demand changes. Neglecting the perspective of uncertain demand leads to highly fluctuating profits.
Successful maritime spatial planning processes require stakeholder engagement and participation, thus requiring tools that support collaboration. Communication-driven spatial decision support systems are designed to facilitate decision making processes of complex spatial problems and are therefore suited for this task, but there are unresolved questions about user access control for these systems. In this study, user access control was designed for a spatial decisions support system for collaborative maritime spatial planning based on observation of two user tests. It was found that there were three distinct groups of users with special access needs to collaborative functionality. The level of access to functionality was organized into three groups: passive participants, actively contributing collaborators and managing moderators.
In the present study, large eddy simulation is used to investigate combustion recession for the Engine Combustion Network Spray A flame at two ambient temperatures (850 K and 800 K) and two injection pressures (100 MPa and 50 MPa). The present numerical results are able to capture different combustion recession phenomena after the end-of-injection (AEOI). With an injection pressure of 100 MPa, the model predicts a ‘‘separated’’ combustion recession at the ambient temperature of 850 K and no combustion recession at the ambient temperature of 800 K, in which both predictions correspond to the measurements. The combustion recession is mainly controlled by the auto-ignition process at the ambient temperature of 850 K. At the ambient temperature of 800 K, the local temperature within the fuel-rich region is not high enough to promote the hightemperature ignition process. As time progresses, the mixture within the fuel-rich region rapidly transitions to become an overly fuel-lean mixture, which further hinders high-temperature ignition to occur. Nonetheless, it is shown that lowering the injection pressure to 50 MPa causes the combustion recession to occur at the
ambient temperature of 800 K. This is likely attributed to the low injection case having a lower air entrainment rate AEOI, which causes the mixtures upstream of the lift-off position to transition slower from fuel-rich to fuel-lean mixtures.
Product-based companies worldwide attempt to integrate services into their offerings, embarking on “servitization” as a key strategy. These days, the acceleration of technological innovation (i.e., Industry 4.0) has triggered an emerging IT-driven business paradigm called digital servitization or smart product-service system (PSS) that embeds Industry 4.0 technologies. As a result of these developments, related literature has expanded across different disciplines in recent years. However, understanding and describing literature is not easy considering its volume and variety. Establishing common ground for central concepts is essential for science. Thus, to clarify important topics and research issues on servitization and PSSs in Industry 4.0, we carry out a comprehensive literature review by performing text mining of 419 journal articles. A machine learning approach is applied to learn and identify the specific topics, and the suggested key references are manually reviewed to develop a state-of-the-art overview. A total of 10 key research topics are identified, and the enabler–engineering–goal framework is developed. This study contributes to clarifying a systematized view of dispersed studies of servitization and PSSs in Industry 4.0 across multiple disciplines and encourages further academic discussions and industrial transformation.