A new motivation for marine restoration has been observed, associated with the dissatisfaction with current marine restoration governance arrangements (MRGAs). An MRGA consists of alliances of public and private actors (coalitions) who, through their common conceptualisation of the problem (discourses), try to influence and design marine restoration activities while considering the rules of decision-making, and the management of limited resources. Emerging MRGAs rise in parallel to existing ones and aim to contribute to the same goals or show another way of reaching those goals. This phenomenon raises questions of legitimacy both for the emerging and the existing arrangement. Building on existing literature, this paper proposes an analytical framework to simultaneously explore input, throughput and output legitimacy as three essential pre-conditions of legitimacy for MRGAs. The framework is tested in three European cases of MRGAs that were part of the European Union MERCES project (http://www.merces-project.eu/). Analysis showed that actors who are influential in achieving restoration goals, and also those who are impacted by restoration actions, should be involved in the MRGAs (input legitimacy); actors within MRGAs should establish and follow procedures for decision-making that are both transparent and clear (throughput legitimacy); and actors within MRGAs need to establish a common understanding of restoration, of the goal to reach and of the related uncertainties (output legitimacy). Awareness of these pre-conditions allows actors internal and external to MRGAs to address aspects that give legitimacy to restoration actions. It also creates a language that allows actors to engage in discussion on legitimacy that goes beyond the mere application of the rule of law.
The report is organized as follows. The introduction will lay out the current state-of-play of eco-efficiency and the zeitgeist of the current situation on maritime that we find ourselves in, in 2020. The next section will provide some historical context looking back to 2010 and 2000 to trace the trajectory and developmental course on which we are. The core contribution of this report is the Maritime Operations Roadmap that can be found in Figure 1 on page 9. This illustration plots the expectations for technological capabilities and policy from 2020 to 2030.
Policy emphasis in ship design must be shifted away from global and idealized towards regional based and realistic vessel operating conditions. The present approach to reducing shipping emissions through technical standards tends to neglect how damages and abatement opportunities vary according to location and operational conditions. Since environmental policy originates in damages relating to ecosystems and jurisdictions, a three-layered approach to vessel emissions is intuitive and practical. Here, we suggest associating damages and policies with ports, coastal areas possibly defined as Emission Control Areas (ECA) as in the North Sea and the Baltic, and open seas globally. This approach offers important practical opportunities: in ports, clean fuels or even electrification is possible; in ECAs, cleaner fuels and penalties for damaging fuels are important, but so is vessel handling, such as speeds and utilization. Globally we argue that it may be desirable to allow burning very dirty fuels at high seas, due to the cost advantages, the climate cooling benefits, and the limited ecosystem impacts. We quantify the benefits and cost savings from reforming current IMO and other approaches towards environmental management with a three-layered approach, and argue it is feasible and worth considering.
This PhD thesis examines the role of market-based measures (MBMs) in incentivizing international shipping greenhouse gas (GHG) emissions reductions to leverage the decarbonization efforts of the International Maritime Organization (IMO). The research motivation sprang from the Initial IMO Strategy, which, among other climate ambitions, envisages at least a 50% curb of GHG emissions until 2050 vis-a-vis 2008 levels. The regulatory framework involves several candidate measures, including MBMs, i.e., environmental policies like carbon taxes and emissions trading systems (ETS) that enforce the "polluter-pays" principle, and thus provide fiscal incentives to stakeholders to eliminate their carbon footprint.
The assessment of MBMs as means of decarbonizing shipping is based on three main pillars: their economic efficiency, their environmental effectiveness, and their climate policy design. Compliance with carbon pricing regimes can entail the adoption of both operational measures, such as speed reduction, route reconfiguration, or voyage optimization techniques, and technological measures like the uptake of zero-carbon technologies and alternative marine fuels. Due to this wide range of conformity practices, this thesis assesses several short- and long-term responses to MBMs in order to encapsulate their cost effectiveness in relation to their carbon abatement potential.
From a climate policy design perspective, the two most prominent types of MBMs are the carbon taxes, a fixed-price approach that provides carbon price certainty, and the ETSs, a fixedquantity system that secures that GHG emissions levels are met. At first, the study evaluates the prospects of a carbon levy to achieve GHG emissions reductions by analyzing the macroeconomic effects of freight rates and fuel prices in inducing slow steaming as an operational response to the MBM. The results show that market conditions influence the overall effectiveness of a tax and that the attained reductions, although significant, are insufficient to reach the 50% decarbonization targets. Moreover, considering the imminent inclusion of the maritime sector into the EU ETS, the thesis examines the scenario of liner shipping operators opting for route reconfigurations as an operational response to a regional ETS. The outputs reveal that replacing EU ports with nearby non-EU competitor ports becomes cost-effective for minimal EU carbon prices. The action would result in carbon leakage, EU ETS evasion, loss of EU ETS revenue, and penalization of the EU ports.
To the extent that MBMs induce technological changes, this thesis evaluates the level of carbon pricing needed to close the price gap between alternative and conventional marine fuels. The analysis considers the capital and operational costs for implementing and utilizing alternative marine fuels onboard and develops their marginal abatement cost curves (MACCs) to evaluate their cost-competitiveness and carbon abatement spectrum. The analysis indicates that to reach full maritime decarbonization, fuels such as green liquid hydrogen and their supporting technology, as of today’s cost estimations, would require a carbon price of up to 700 USD/MT CO2e to become cost-competitive.
The thesis concludes that accounting for a well-to-wake scope of emissions will create the right
incentives for developing sustainable alternative marine fuel production pathways to facilitate
shipping’s future energy demand. Revenues from MBMs will be substantial and can accelerate
R&D, scale-up the availability of alternative fuels, subsidize "fist-movers" and green ships and
reverse possible detrimental effects of carbon pricing to developing countries such as the Least
Developed Countries (LDCs) and the Small Island Developing States (SIDS).
Results from life cycle assessment (LCA) studies are sensitive to modeling choices and data used in building the underlying model. This is also relevant for the case of fisheries and LCAs of fish products. Fisheries' product systems show both multifunctionality because of the simultaneous co-catch of multiple species and potential constraints to supply due to natural stock limits or socially established limits such as quota systems. The performance of fisheries also varies across seasons, locations, vessels, and target species. In this study, we investigate the combined effect of modeling choices and variability on the uncertainty of LCA results of fish products. We use time series data from official Danish statistics for catch and fuel use of several fisheries disaggregated using a top-down procedure. We apply multiple modeling approaches with different assumptions regarding the type of partitioning, substitution, and constraints. The analysis demonstrates that, in the presence of relevant multifunctionality, the results are substantially affected by the modeling approach chosen. These findings are robust across years and fisheries, indicating that modeling choices contribute to uncertainty more than the variability in fishing conditions. We stress the need for a more careful alignment of research questions and methods for LCA studies of fisheries and recommend a very transparent statement of assumptions, combined with uncertainty and sensitivity analysis. This article met the requirements for a gold-gold data openness badge described at http://jie.click.badges.
Since the outbreak of COVID-19, its impacts on the maritime transportation and logistics field have been multi-dimensional. In addition to the green shipping corridor proposed by the Clydebank Declaration in the United Kingdom in 2021, port digitalisation and decarbonisation of the maritime industry have become focal issues in the field. The industry needs a new framework to offset the negative impacts of the pandemic and to accommodate integrated technologies comprising of artificial intelligence (AI), blockchain, cloud systems, internet of things (IoT) and others, which have been applied to the industry. Having considered these circumstances, this paper aims to propose the 6th-generation ports model with smart port (6GP) as a new framework for the port logistics industry in the post-COVID-19 period. The proposed 6GP contributes to providing business development strategy and port development policy for stakeholders in the industry in the post-pandemic era reflecting focal challenges such as digitalisation, decarbonisation, sustainability and smart transformation. It also contributes to expanding port devolution theory from the fifth-generation ports (5GP) to 6GP.
The International Energy Agency Technology Collaboration Program for Ocean Energy Systems (OES) initiated the OES Wave Energy Conversion Modeling Task, which focused on the verification and validation of numerical models for simulating wave energy converters (WECs). The long-term goal is to assess the accuracy of and establish confidence in the use of numerical models used in design as well as power performance assessment of WECs. To establish this confidence, the authors used different existing computational modeling tools to simulate given tasks to identify uncertainties related to simulation methodologies: (i) linear potential flow methods; (ii) weakly nonlinear Froude–Krylov methods; and (iii) fully nonlinear methods (fully nonlinear potential flow and Navier–Stokes models). This article summarizes the code-to-code task and code-to-experiment task that have been performed so far in this project, with a focus on investigating the impact of different levels of nonlinearities in the numerical models. Two different WECs were studied and simulated. The first was a heaving semi-submerged sphere, where free-decay tests and both regular and irregular wave cases were investigated in a code-to-code comparison. The second case was a heaving float corresponding to a physical model tested in a wave tank. We considered radiation, diffraction, and regular wave cases and compared quantities, such as the WEC motion, power output and hydrodynamic loading.
This paper proposes a multi-time scale scheduling strategy for a practical port coupled hydrogen-electricity energy system (CHEES) to optimize the integration of renewable energy and manage the stochasticity of port power demand. An optimization framework based on day-ahead, intra-day and real-time scheduling is designed. The framework allows coordinating adjustable resources with different rates to reduce the impact of forecast errors and system disturbances, thus improving the flexibility and reliability of the system. The effectiveness of the proposed strategy is verified by a case study of the actual CHEES in the Ningbo Zhoushan Port, and the impact of equipment anomalies on the port power system operation is studied through simulation of different scenarios. The results show that compared with a scheduling scheme without energy management strategy, CHEES with multi-time scale scheduling can save 25.42% of costs and reduce 14.78% of CO 2 emissions. A sensitivity analysis is performed to highlight the impact of hydrogen price and soft open points (SOP) rated power on the system economy. This study not only provides a new perspective for the optimal scheduling of port energy systems, but also provides a practical framework for managing port energy systems to achieve green transformation and sustainable development.
Implementation of alternative energy supply solutions requires the broad involvement of local communities. Hence, smart energy solutions are primarily investigated on a local scale, resulting in integrated community energy systems (ICESs). Within this framework, the distributed generation can be optimally utilised, matching it with the local load via storage and demand response techniques. In this study, the boat demand flexibility in the Ballen marina on Samsø—a medium-sized Danish island—is analysed for improving the local grid operation. For this purpose, suitable electricity tariffs for the marina and sailors are developed based on the conducted demand analysis. The optimal scheduling of boats and battery energy storage system (BESS) is proposed, utilising mixed-integer linear programming. The marina’s grid-flexible operation is studied for three representative weeks—peak tourist season, late summer, and late autumn period—with the combinations of high/low load and photovoltaic (PV) generation. Several benefits of boat demand response have been identified, including cost savings for both the marina and sailors, along with a substantial increase in load factor. Furthermore, the proposed algorithm increases battery utilisation during summer, improving the marina’s cost efficiency. The cooperation of boat flexibility and BESS leads to improved grid operation of the marina, with profits for both involved parties. In the future, the marina’s demand flexibility could become an essential element of the local energy system, considering the possible increase in renewable generation capacity—in the form of PV units, wind turbines or wave energy
Driven by increased integration of renewable energy sources, the widespread decarbonization of power systems has led to energy price fluctuations that require greater adaptability and flexibility from grid users in order to maximize profits. Industrial loads equipped with flexible resources can optimize energy consumption rather than merely reacting to immediate events, thereby capitalizing on volatile energy prices. However, the absence of sufficient measured data in industrial processes limits the ability to fully harness this flexibility. To address this challenge, we present a black-box optimization model for optimizing the energy consumption of cooling systems in the aquaculture industry using Extreme Gradient Boosting (XGBoost) and Bayesian Optimization (BO). XGBoost is employed to establish a nonlinear relationship between cooling system power consumption and available measured data. Based on this model, Bayesian Optimization with the Lower Confidence Bound (LCB) acquisition function is used to determine the optimal discharge temperature of water into breeding pools, minimizing day-ahead electricity costs. The proposed approach is validated using real-world data from a case study at the Port of Hirtshals, Denmark based on measurements from 2023. Our findings illustrate that leveraging the inherent flexibility of industrial processes can yield financial benefits while providing valuable signals for grid operators to adjust consumption behaviors through appropriate price mechanisms. Furthermore, machine learning techniques prove effective in optimizing energy consumption for industries with limited measured data, delivering accurate and practical estimates.