Search Results (613)

This article addresses the pressing need for knowledge on how digital technologies, artificial intelligence, and blockchain can revolutionize opportunities in the marine economy and sustainably support business while balancing environmental protection and economic growth, and legal instruments and policy innovations for marine environmental protection. However, implementation, legal, and governance concerns still exist. This study discusses the development and challenges of these technologies according to their environmental, economic, business, and regulatory dimensions, following a literature review of more than 100 peer-reviewed articles, books, and a synthesis of global shipping policies, risk, policymakers, industry experts, and environmental scientists. The findings highlight the need for aligned international regulations to strike a balance between innovation and environmental goals, risks, and technology. This study introduces an innovative governance assessment framework, bridging the gap between technology scalability and equitable policy responses, as well as the environmental impact and ecosystem balance. We conclude with actionable recommendations for policymakers and companies to harness digital innovations while strategizing for long-term sustainability in the maritime sector and aligning UN Sustainable Development Goals with the principles of maritime law, the United Nations Convention on the Law of the Sea, and the United Nations Environment Programme Regional Seas Programme, offering ways to mitigate governance fragmentation. This study informs interdisciplinary discussion by bridging technical feasibility and legal feasibility, providing actionable suggestions to policymakers to reconcile digital innovation with the sustainability of the marine ecosystem. Full article

In a cellular maritime communication system, ocean buoys are essential to enable environmental monitoring, offshore platform management, and disaster response. Therefore, energy-efficient transmission from the buoys is a key requirement to prolong their operational time. A fixed uplink beamforming can be considered to save energy by leveraging its beam gain while managing the target link reliability. However, the dynamic condition of ocean waves causes buoys’ random orientation, leading to frequent misalignment of their predefined beam direction aimed at the base station, which degrades both the link reliability and energy efficiency. To address this challenge, we propose a wave-adaptive beamforming framework to satisfy data-rate demands within limited power budgets. This strategy targets scenarios where sea state information is unavailable, such as in network-assisted systems. We propose a Two-Dimensional Thompson Sampling (2DTS) scheme that jointly selects beamwidth and transmit power to satisfy the target-rate constraint with minimal power consumption and thus achieve maximal energy efficiency. This adaptive learning approach effectively balances exploration and exploitation, enabling efficient operation in uncertain and changing sea conditions. In simulation, under a moderate sea state, 2DTS achieves an energy efficiency of $1.26 \times {10}^4$ bps/Hz/J at round 600, which is $73.7\%$ of the ideal ($1.71 \times {10}^4$), and yield gains of $96.9\%$ and $447.8\%$ over exploration-based TS and conventional TS, respectively. Under a harsh sea state, 2DTS attains $3.09 \times {10}^4$ bps/Hz/J ($85.6\%$ of the ideal $3.61 \times {10}^4$), outperforming the exploration-based and conventional TS by $83.9\%$ and $113.1\%$, respectively. The simulation results demonstrate that the strategy enhances energy efficiency, confirming its practicality for maritime communication systems constrained by limited power budgets. Full article

Mango (Mangifera indica L.) is a popular tropical fruit enjoyed worldwide, with Europe being a significant importer of this fruit. Its climacteric nature and short shelf-life pose challenges for maintaining quality, while emissions from transportation threaten the sustainability of the supply chain. This highlights the importance of low-impact logistics in maintaining fruit quality. This study aimed to evaluate the quality of fresh mangoes in Italy by comparing the different shipping systems (air, sea, and road) for seven cultivars sourced from seven countries. Quality assessment included pomological analysis, PTR-ToF-MS for volatile profiling (n = 11 cultivars × 2 years × 3 replicates), and consumer sensory analysis (n = 65 for untrained panellists in 1 year, n = 8 for trained panellists over 2 years). Results indicated that air and truck transport better preserved fruit quality compared to sea freight, primarily due to shorter transit times, which allowed for harvesting at more advanced ripeness stages. The combination of PTR-ToF-MS and PLS-DA effectively differentiated samples based on the method of transport, showcasing its potential as a quick quality monitoring tool. Mangoes transported by air showed significantly higher levels of volatile organic compounds (VOCs), a 29% greater total soluble solids (TSSs) content, and a 44% lower acidity (TA). Sensorial tests indicated that consumers preferred these mangoes. However, air transport resulted in 30 times higher CO₂ emissions per kg of fruit compared to sea freight (~642,117 CO₂e (kg) vs. ~19,132 CO₂e (kg)), highlighting a critical dilemma between sustainability and quality. These findings provide a framework for developing hybrid logistics strategies that strike a balance between preserving quality and environmental responsibility. Additionally, they support the development of European mango cultivation, which can optimise harvest timing, reduce emissions, and enhance fruit quality. Full article

Hybrid battery systems, which combine high-energy and high-power cells, offer a promising solution for electrifying heavy-duty applications by balancing energy density, power capability, and cost. This paper presents a generic methodology for cost-optimal sizing of hybrid battery energy storage systems using a Mixed Integer Nonlinear Programming framework. A large-scale simulation study involving 10,000 load profiles replicating applications varying from road transportation to sea-going vessels is used to derive practical “rules of thumb” that guide when hybridization is beneficial, offering significant reductions in cost, weight, and volume compared to monotype battery configurations. Sensitivity analyses further validate the robustness of the method across varying cell costs and C-rates, making it applicable to a wide range of battery chemistries and use cases. Full article

Under the context of “Energy Conservation and Emission Reduction,” low-sulfur fuel has become widely adopted in maritime operations, posing significant challenges to cylinder lubrication systems. Traditional oil injection strategies, heavily reliant on manual experience, suffer from instability and high costs. To address this, a lightweight image retrieval model for cylinder lubrication is proposed, leveraging deep learning and computer vision to support oiling decisions based on visual features. The model comprises three components: a backbone network, a feature enhancement module, and a similarity retrieval module. Specifically, EfficientNetB0 serves as the backbone for efficient feature extraction under low computational overhead. MobileViT Blocks are integrated to combine local feature perception of Convolutional Neural Networks (CNNs) with the global modeling capacity of Transformers. To further improve receptive field and multi-scale representation, Receptive Field Blocks (RFB) are introduced between the components. Additionally, the Convolutional Block Attention Module (CBAM) attention mechanism enhances focus on salient regions, improving feature discrimination. A high-quality image dataset was constructed using WINNING’s large bulk carriers under various sea conditions. The experimental results demonstrate that the EfficientNetB0 + RFB + MobileViT + CBAM model achieves excellent performance with minimal computational cost: 99.71% Precision, 99.69% Recall, and 99.70% F1-score—improvements of 11.81%, 15.36%, and 13.62%, respectively, over the baseline EfficientNetB0. With only a 0.3 GFLOP and 8.3 MB increase in model size, the approach balances accuracy and inference efficiency. The model also demonstrates good robustness and application stability in real-world ship testing, with potential for further adoption in the field of intelligent ship maintenance. Full article

This study investigates the hydrodynamics of the net system of the bottom-mounted aquaculture farms located in the Bohai Sea, addressing the growing demand for high-quality aquatic products and the limitations of coastal aquaculture. Based on the validation part, the established lumped-mass method integrated with the finite element method ABAQUS/AQUA was employed to evaluate the structural responses of the net system with three arrangement schemes under diverse environmental loads. The hydrodynamic loads on net twines are modeled with Morison formulae. With the motivation of investigating the trade-offs between volume expansions, load distributions, and structural reliabilities, Scheme 1 refers to the baseline design enclosing the basic aquaculture volume, while Scheme 2 targets to increase the aquaculture volume and utilization rate and Scheme 3 seeks to optimize the load distributions instead. The results demonstrate that Scheme 1 provides the optimal balance of structural safety and functional efficiency. Specifically, under survival conditions, Scheme 1 reduces peak bottom tension rope loads by 14% compared to Scheme 2 and limits maximum netting displacement to 4.0 m. It is 21.3% lower than Scheme 3, of which the displacement is 5.08 m. It has been confirmed that Scheme 1 effectively minimizes collision risks, whereas the other schemes exhibit severe collisions. Scheme 1 trades off maximum volume expansion for optimal load management, minimal deformation, and the highest overall structural reliability, making it the recommended design. These findings offer valuable insights for the design and optimization of net systems in offshore aquaculture structures serviced in comparable offshore regions. Full article

Climate change in Antarctica has profound global implications, influencing sea level rise, atmospheric circulation, and the Earth’s energy balance. This study presents a data-driven baseline analysis of meteorological observations from a British Antarctic Survey automatic weather station (2020–2024). Temporal and seasonal analyses reveal strong insolation-driven variability in temperature, snow depth, and solar radiation, reflecting the extreme polar day–night cycle. Correlation analysis highlights solar radiation, upwelling longwave flux, and snow depth as the most reliable predictors of near-surface temperature, while humidity, pressure, and wind speed contribute minimally. A linear regression baseline and a Random Forest model are evaluated for temperature prediction, with the ensemble approach demonstrating superior accuracy. Although the short data span limits long-term trend attribution, the findings underscore the potential of lightweight, reproducible pipelines for site-specific climate monitoring. All analysis codes are openly available in github, enabling transparency and future methodological extensions to advanced, non-linear models and multi-site datasets. Full article

Tidal inlets regulate the exchange of water and sediment between the open sea and adjacent basins. In many locations, engineering interventions combined with coastal protections and polders have intensified erosion and scouring. This study reports on a three-year monitoring program following the implementation of a Nature-based Solution (NbS) at a previous engineering tidal inlet in the Zwin, located along the Belgian–Dutch coast. In 2019, large-scale modifications to the intertidal zone and the opening of a dyke doubled the surface area of the tidal inlet and its associated tidal marsh. Results revealed rapid and substantial morphological adjustments: the main channel deepened, widened, and migrated eastward. Sediment balance analyses showed stability at the inlet entrance but material loss further inland. Tidal prism and cross-sectional measurements indicated a fourfold increase in tidal prism immediately after NbS implementation, triggering strong channel responses. Within a year, the channel cross-sectional area reached a new equilibrium, which remained stable in the following years. These patterns highlight active sediment transport driven by coupled hydrodynamic and morphodynamic processes. Using an extensive data set, a conceptual model is presented to illustrate how the NbS influenced tidal inlet dynamics through the interaction of flow and sedimentation processes. Full article

Shipping in complex marine environments requires a balance between navigational safety, minimising travel time and optimising logistics management, which is particularly challenging in areas with geometric obstructions and Offshore Wind Farms (OWFs). This study focuses on the maritime route networks in the Croatian ports of Pula and Rijeka, including the main access routes to OWFs and zones characterised by multiple navigational challenges. The aim of the research is to develop an empirically based and practically applicable framework for the optimisation of sea routes that combines analytical precision with operational efficiency. The parallel application of Dijkstra and A* algorithms enables a comparative analysis between deterministic and heuristic approaches in terms of reducing navigation risk, optimising route costs and ensuring fast logistical access to OWFs. The applied methods include the analysis of real and simulated route networks, the evaluation of statistical route parameters and the visualisation of the results for the evaluation of logistical and operational efficiency. Adaptive heuristic modifications of the A* algorithm, combined with the parallel implementation of Dijkstra’s algorithm, enable dynamic route planning that takes into account real-world conditions, including variations in wind speed and direction. The results obtained provide a comprehensive framework for safe, efficient and logistically optimised navigation in complex marine environments, with direct applications in the maintenance, inspection and operational management of OWFs. Full article

This article addresses the multifaceted challenges inherent in the development of the novel REEFS (Renewable Electric Energy From Sea) wave energy converter (WEC). Building on the submerged pressure differential principle, it frames similar WECs before focusing on REEFS that combines renewable energy generation with coastal protection, functioning as an artificial reef. The review follows chronological criteria, encompassing experimental proof-of-concept, small-scale laboratory modeling, simplified and advanced computational fluid dynamics (CFD) simulations, and the design of a forthcoming real-sea model deployment. Key milestones include the validation of a passive variable porosity system, demonstration of wave-to-wire energy conversion, and quantification of wave attenuation for coastal defense. Additionally, the study introduces a second patent-protected REEFS configuration, isolating internal components from seawater via an elastic enveloping membrane. Challenges related to scaling, numerical modeling, and funding are thoroughly examined. The results highlight the importance of the proof-of-concept as the keystone of the development process, underscore the relevance of mixed laboratory-computational approaches and emphasize the need for a balanced equilibrium between intellectual property safeguard and scientific publishing. The REEFS development trajectory offers interesting insights for researchers and developers navigating the complex innovation seas of emerging wave energy technologies. Full article

Cetaceans are essential for maintaining the balance and stability of deep-sea ecosystems. However, environmental challenges and limited funding have resulted in a marked lack of data on species diversity and the conservation status of deep-sea cetaceans. In this study, we undertook two research expeditions in the deep-water regions of the northern South China Sea, employing an integrated visual and acoustic survey approach. In total, 28 cetacean encounters, involving 12 species and more than 1000 individuals, were documented through visual observation, while acoustic monitoring recorded 53 detections. These findings demonstrate that the deep-sea waters of the northern South China Sea have relatively high cetacean biodiversity and constitute significant habitats for these marine mammals. Nevertheless, this area also experiences intensive human activities, with fisheries, maritime traffic, and oil and gas extraction posing primary threats to local cetacean populations. Improving the management of human activities in this marine zone is essential for ensuring the effective protection of cetacean species and their critical habitats. Full article

The article addresses the issue of liquefied natural gas (LNG) distribution as a marine fuel, analyzing both ecological and economic aspects in the context of the Baltic Sea basin. The authors emphasize that LNG plays an increasingly significant role in the global energy balance, and its application in maritime transport is crucial for implementing sustainable development policies and advancing the energy transition. From an ecological perspective, LNG offers a substantial reduction in harmful emissions compared with conventional marine fuels such as marine diesel oil (MDO) and heavy fuel oil (HFO). In particular, the use of LNG results in lower emissions of carbon dioxide (CO₂), sulfur oxides (SO_x), nitrogen oxides (NO_x), and particulate matter (PM). The reduction in these pollutants is essential not only for improving air quality in port and coastal areas but also for mitigating global environmental impacts, including climate change. On the economic side, the article focuses on the cost structure of LNG distribution, highlighting that its price dynamics are subject to significant fluctuations. These variations are driven by geopolitical developments, crude oil price volatility, environmental regulations, and the expansion of bunkering infrastructure. From an economic perspective, LNG prices show significant volatility depending on the year and market conditions. Between 2018 and 2023, LNG prices ranged from approximately 450 to 530 USD/ton, at times exceeding the cost of HFO (400–550 USD/ton) but in some years remaining cheaper. In comparison, MDO prices were consistently the highest, increasing over the analyzed period from 600 USD/ton to over 720 USD/ton. This variability results from geopolitical factors, supply and demand dynamics, and environmental regulations, which highlight the strategic importance of LNG as a transitional fuel in shipping. The purpose of this study is to examine the role of LNG as an alternative fuel for shipping in the Baltic Sea, with particular emphasis on the scale of vessel emissions and the key factors influencing its distribution costs. Full article

Reliable dam reservoir operation is crucial for the sustainable management of water resources under climate change-induced uncertainties. This study evaluates four machine learning algorithms—linear regression, decision tree, random forest, and XGBoost—for forecasting daily water levels in a dam reservoir in the Western Black Sea Region of Türkiye. A dataset of 5964 daily hydro-meteorological observations spanning 17 years (2008–2024) was used, and model performances were assessed using MAE, RMSE, and R² metrics after hyperparameter optimization and cross-validation. The linear regression model showed weak predictive capability (R² = 0.574; RMSE = 2.898 hm³), while the decision tree model achieved good accuracy but limited generalization (R² = 0.983; RMSE = 0.590 hm³). In contrast, ensemble models delivered superior accuracy. Random forest produced balanced results (R² = 0.983; RMSE = 0.585 hm³; MAE = 0.046 hm³), while XGBoost achieved comparable accuracy (R² = 0.983) with a slightly lower RMSE (0.580 hm³). Statistical tests (p > 0.05) confirmed no significant differences between predicted and observed values. These findings demonstrate the reliability of ensemble learning methods for dam reservoir water level forecasting and suggest that random forest and XGBoost can be integrated into decision support systems to improve water allocation among agricultural, urban, and ecological demands. Full article

Oceans, which cover more than 70% of Earth’s surface, are home to vast biological and mineral resources. Deep-sea exploration encounters significant challenges due to harsh environmental factors, including low temperatures, high pressure, and complex hydrodynamic forces. These constraints have led to the widespread use of underwater robots as essential tools for deep-sea resource exploration and exploitation. Conventional underwater robots, whether rigid with fixed stiffness or fully flexible, fail to achieve the propulsion efficiency observed in biological fish. To overcome this limitation, researchers have developed adjustable stiffness mechanisms for robotic fish designs. This innovation strikes a balance between structural rigidity for stability and flexible adaptability to dynamic environments. By dynamically adjusting localized stiffness, these bio-inspired robots can alter their mechanical properties in real time. This capability improves propulsion efficiency, energy utilization, and resilience to external disturbances during operation. This paper begins by reviewing the evolution of underwater robots, from fixed-stiffness systems to adjustable-stiffness designs. Next, existing methods for stiffness adjustment are categorized into two approaches: offline component replacement and online real-time adaptation. The principles, implementation strategies, and comparative advantages of each approach are then analyzed. Finally, we identify the current challenges in adjustable-stiffness underwater robotics and propose future directions, such as advancements in intelligent sensing, autonomous stiffness adaptation, and enhanced performance in extreme environments. Full article

Pressure on fresh water resources has been aggravated in recent decades, basically due to population growth, rapid urbanization, and global warming. Integrated engineering solutions and the circular economy, considering the urban water cycle as a whole, are becoming fundamental, particularly in arid and semi-arid regions under permanent or recurrent hydric deficit. This study aims to develop and present an integrated engineering solution for water supply, wastewater collection, and treated wastewater reuse for landscape irrigation in a large, topographically complex, and arid to semi-arid coastal urban region at the south of Santiago Island, Cape Verde. The region is one of the driest and most arid of the Island, with a current average annual precipitation between about 100 and 200 mm, and has very limited underground water resources. The main study area, with about 600 ha, has altitudes ranging from values close to sea level up to about 115 m and has several topographic difficulties, including several relatively rugged zones. The devised water supply system considers four altimetric distribution levels, three main reservoirs connected to each other by a serial system of pipelines with successive pumping, a fourth downstream reservoir for pressure balance in one of the levels, and desalinated water as the source. The sanitary sewer pipes of the urbanizations drain to an interceptor system that operates predominantly in open channel flow in a closed pipe. The long interceptor crosses laterally along the coast several very dug valleys in the path to the Praia Wastewater Treatment Plant in the east, and requires several conduits working under pressure for the crossings, either lifting or governed by gravity. The under-pressure pipeline system of recycled water is partially forced and partially ruled by gravity and transports the treated wastewater from the plant in the opposite direction of the interceptor to a natural reservoir or lake located in the region of urbanizations and the main green spaces to be irrigated. The conceived design of the interceptor and recycled water pipeline minimizes the construction and operation costs, maximizing their hydraulic performance. Full article