Search Results (39)

The expansion of global maritime activities threatens marine ecosystems and biodiversity. Collisions between ships and marine megafauna profoundly impact vulnerable species such as whales, who serve as keystone predators. However, the specific regions most heavily affected by shipping traffic and the multi-species facing collision risk remain poorly understood. Here, we analyzed global shipping data to assess the distribution of areas with high shipping pressure and identify global hotspots for whale–ship collisions. The results reveal that high-pressure habitats are primarily distributed within exclusive economic zones (EEZs), which are generally consistent with the distribution of collision hotspots. High-pressure habitats exhibit significant spatial mismatch: 32.9% of Marine Protected Areas endure high shipping stress and yet occupy merely 1.25% of protected ocean area. Additionally, 25.1% of collision hotspots (top 1% risk) affect four or more whale species, forming critical aggregation in regions like the Gulf of St. Lawrence and Northeast Asian marginal seas. Most of these high-risk areas lack protective measures. These findings offer actionable spatial priorities for implementing targeted conservation strategies, such as the introduction of mandatory speed restrictions and dynamic vessel routing in high-risk, multi-species hotspots. By focusing on critical aggregation areas, these strategies will help mitigate whale mortality and enhance marine biodiversity protection, supporting the sustainable coexistence of maritime activities with vulnerable marine megafauna. Full article

This study identifies the optimal location for an offshore energy island to supply sustainable power to desalination plants along the Red Sea coast. As demand for clean energy in water production grows, integrating renewables into desalination systems becomes increasingly essential. A decision-making framework was developed to assess site feasibility based on renewable energy potential (solar, wind, and wave), marine traffic, site suitability, planned developments, and proximity to desalination facilities. Data was sourced from platforms such as Windguru and RETScreen, and spatial analysis was conducted using Inverse Distance Weighting (IDW) and Multi-Criteria Decision Analysis (MCDA). Results indicate that the central Red Sea region offers the most favorable conditions, combining high renewable resource availability with existing infrastructure. The estimated regional desalination energy demand of 2.1 million kW can be met using available renewable sources. Integrating these sources is expected to reduce local CO₂ emissions by up to 43.17% and global desalination-related emissions by 9.5%. Spatial constraints for offshore installations were also identified, with land-based solar energy proposed as a complementary solution. The study underscores the need for further research into wave energy potential in the Red Sea, due to limited real-time data and the absence of a dedicated wave energy atlas. Full article

The long-term sustainability of seaports depends on various operational factors, including infrastructure efficiency, digital innovation, environmental management, and regulatory compliance, among which maritime pilotage plays a crucial role in ensuring safe navigation and minimizing environmental, economic, and social risks. This research employed the PRISMA-ScR framework to evaluate the environmental, economic, and social impacts of pilotage on the sustainability of seaports. The findings demonstrate efficient navigation and spill avoidance, which reduce emissions, safeguard marine biodiversity, and maintain water quality. Economically, it reduces delays, optimizes operational expenses, and increases port competitiveness by increasing maritime traffic. Moreover, pilotage improves navigational safety, local professional skill development, and community interactions via ecological conservation and operational efficiency. It also indicates how environmental initiatives benefit the economy, increase port competitiveness, and promote job security and community happiness. The results also emphasize the significance of pilotage in sustainable seaport operations by quantifying pollution reductions, cost savings, and safety. The result also suggests that successful pilotage enhances ports’ viability and responsibility in global shipping networks while addressing environmental, economic, and social concerns. Full article

The remote monitoring of maritime signaling facilities is one of the marine navigation safety rules essential for ensuring global maritime traffic. Some maritime signaling facilities have not yet implemented remote monitoring systems. This challenge is posed by factors such as insufficient signal range, limited availability of electrical energy, or various economic reasons. Therefore, this paper reviews the current and relevant scientific literature on 10 communication technologies for maritime signaling facilities in the last two decades using PRISMA guidelines. PRISMA 2020 represents guidelines for conducting systematic review papers using mixed methods, including their applicability to various reviews. In addition, this paper analyzes the selection of the best-suited communication technology for communication between maritime signaling facilities. The results show that, initially, 214 papers met the specified criteria, and after applying the filtering, it was narrowed to 29 relevant papers for the research topic. Surprisingly, almost half of them were found in databases other than WOS, SCOPUS, and GOOGLE SCHOLAR. Also, LoRa WAN is the most energy-efficient and cost-effective option, with a consumption rate 2.14 times lower than AIS and NB-IoT. To summarize, it has been found that LoRa WAN represents the optimal communication technology for transmitting data from maritime signaling facilities across long distances. Full article

The imperative of decarbonization in maritime shipping is underscored by the sector’s sizeable contribution to worldwide greenhouse gas emissions. ShipNetSim, an open-source multi-ship simulator created in this study, combines state-of-the-art hydrodynamic modeling, dynamic ship-following techniques, real-time environmental data, and cybersecurity threat simulation to quantify and evaluate marine fuel consumption and CO₂ emissions. ShipNetSim uses well-validated approaches, such as the Holtrop resistance and B-Series propeller analysis with a ship-following model inspired by traffic flow theory, augmented with a novel module simulating cyber threats (e.g., GPS spoofing) to evaluate operational efficiency and resilience. In a case study simulation of the journey of an S175 container vessel from Savannah to Algeciras, the simulator estimated the total fuel consumption to be 478 tons of heavy fuel oil and approximately 1495 tons of CO₂ emissions for a trip of 7 days and 15 h within 13.1% of reported operational estimates. A twelve-month sensitivity analysis revealed a marginal 1.5% range of fuel consumption variation, demonstrating limiting variability for different environmental conditions. ShipNetSim not only yields realistic predictions of energy consumption and emissions but is also demonstrated to be a credible framework for the evaluation of operational scenarios—including speed adjustment, optimized routing, and alternative fuel strategies—that directly contribute to reducing the marine carbon footprint. This capability supports industry stakeholders and policymakers in achieving compliance with global decarbonization targets, such as those established by the International Maritime Organization (IMO). Full article

Monitoring the oceans and establishing a global ocean observing system is a task of paramount importance for topics as diverse as the study of climate change, the management of marine environments, and the safety of coastal areas and marine traffic. These systems must be based on long-term observations that allow the correct modeling of the behavior of the seas and the proper environmental management of them. Despite the logical present trend toward automation, in situ measurements from oceanographic vessels are still needed at present, especially when dealing with biogeochemical variables or when seeking information from the subsurface or deep layers of the sea. Long-term measurements by oceanographic vessels can be carried out at one single fixed oceanographic station with a high sampling frequency (typically once a month) or across a grid of stations. In the latter case a larger geographical area is usually covered, but the cost is a reduction of sampling frequency. The question that arises is: what objectives can be achieved, and what questions can be answered according to the sampling frequency and the spatial coverage of the monitoring program? In this work, we analyze the influence of the sampling frequency on the capacity of observing programs to capture the temporal variability of ocean variables at different time scales and to estimate average seasonal cycles and long-term trends. This analysis is conducted through the study of sea surface chlorophyll concentrations in the Western Mediterranean. The trade-off between sampling frequency and spatial coverage is addressed. For this purpose, a monitoring program in the Spanish Mediterranean waters is used as a case study. We show that monthly and fortnightly intervals are the best sampling frequencies for describing the temporal variability of ocean variables as well as their average seasonal cycles. Quarterly sampling could also be appropriate for estimating such seasonal cycles. Surprisingly, the limitations of these low frequency samplings do not arise from the high frequency variability of ocean variables but from the shape of the seasonal cycles. Both high and low frequency sampling designs could be suitable for detecting long-linear trends, depending on the variance of the noise and that of the trend. In the case of quarterly sampling, we show that some statistics improve with the length of the time series, whereas others do not. Although some results may be related to the dynamics of this region, the results are generally applicable to any other marine monitoring system. Full article

Remote sensing target detection technology in cloud and mist scenes is of great significance for applications such as marine safety monitoring and airport traffic management. However, the degradation and loss of features caused by the obstruction of cloud and mist elements still pose a challenging problem for this technology. To enhance object detection performance in adverse weather conditions, we propose a novel target detection method named CM-YOLO that integrates background suppression and semantic context mining, which can achieve accurate detection of targets under different cloud and mist conditions. Specifically, a component-decoupling-based background suppression (CDBS) module is proposed, which extracts cloud and mist components based on characteristic priors and effectively enhances the contrast between the target and the environmental background through a background subtraction strategy. Moreover, a local-global semantic joint mining (LGSJM) module is utilized, which combines convolutional neural networks (CNNs) and hierarchical selective attention to comprehensively mine global and local semantics, achieving target feature enhancement. Finally, the experimental results on multiple public datasets indicate that the proposed method realizes state-of-the-art performance compared to six advanced detectors, with mAP, precision, and recall indicators reaching 85.5%, 89.4%, and 77.9%, respectively. Full article

Since the Industrial Revolution, underwater soundscapes have become more complex and contaminated due to increased cumulative human activities. Anthropogenic underwater sources have been growing in number, and shipping noise has become the primary source of chronic acoustic exposure. However, global data on current and historic noise levels is lacking. Here, using the Listening to the Deep-Ocean Environment network, we investigated the baseline shipping noise levels in thirteen observatories (eight stations from ONC Canada, four from the JAMSTEC network, and OBSEA in the Mediterranean Sea) and, in five of them, animal presence. Our main results show yearly noise variability in the studied locations that is not dominated by marine traffic but by natural and biological patterns. The halt in transportation due to COVID was insignificant when the data were recorded far from shipping routes. In order to better design a legislative framework for mitigating noise impacts, we highlight the importance of using tools that allow for long-term acoustic monitoring, automated detection of sounds, and big data handling and management. Full article

The analysis of large amounts of vessel trajectory data can facilitate more complex traffic management and route planning, thereby reducing the risk of accidents. The application of deep learning methods in vessel trajectory prediction is becoming more and more widespread; however, due to the complexity of the marine environment, including the influence of geographical environmental factors, weather factors, and real-time traffic conditions, predicting trajectories in less constrained maritime areas is more challenging than in path network conditions. Ship trajectory prediction methods based on kinematic formulas work well in ideal conditions but struggle with real-world complexities. Machine learning methods avoid kinematic formulas but fail to fully leverage complex data due to their simple structure. Deep learning methods, which do not require preset formulas, still face challenges in achieving high-precision and long-term predictions, particularly with complex ship movements and heterogeneous data. This study introduces an innovative model based on the transformer structure to predict the trajectory of a vessel. First, by processing the raw AIS (Automatic Identification System) data, we provide the model with a more efficient input format and data that are both more representative and concise. Secondly, we combine convolutional layers with the transformer structure, using convolutional neural networks to extract local spatiotemporal features in sequences. The encoder and decoder structure of the traditional transformer structure is retained by us. The attention mechanism is used to extract the global spatiotemporal features of sequences. Finally, the model is trained and tested using publicly available AIS data. The prediction results on the field data show that the model can predict trajectories including straight lines and turns under the field data of complex terrain, and in terms of prediction accuracy, our model can reduce the mean squared error by at least $6\times {10}^{-4}$ compared with the baseline model. Full article

The increasing congestion in major global maritime routes poses significant threats to international maritime safety, exacerbated by the proliferation of large, high-speed vessels. To improve the detection of abnormal ship behavior, this research employed automatic identification system (AIS) data for ship trajectory forecasting. Traditional methods primarily focus on spatial and temporal correlations but often lack accuracy and reliability. In this study, ship path predictions were enhanced using the WTG model, which combines wavelet transform, temporal convolutional networks (TCN), and gated recurrent units (GRU). Initially, wavelet decomposition was applied to deconstruct the input trajectory time series. The TCN and GRU modules then extracted features from both the time series and the decomposed data. The predicted elements were reassembled using a multi-head attention mechanism and a pooling layer to produce the final predictions. Comparative experiments demonstrated that the WTG model surpasses other models in the accuracy of ship trajectory prediction. The model proposed in this study proves to be reliable for forecasting ship paths, which is crucial for marine traffic management and ensuring safe navigation. Full article

The installation of offshore wind farms is rising, driven by the goal of changing the global energy matrix. However, many of their possible impacts are still unknown. Increased noise levels, disruptions to food chains, pollution due to traffic, and impacts on fishing communities and tourism are all potential effects to consider. Marine habitats are essential carbon dioxide sinks. Therefore, losing marine biodiversity due to offshore wind farms can be counterproductive in mitigating climate change. Balancing biodiversity conservation, wind potential, and political interests is challenging. Today, Uruguay has significantly decreased the fossil share in its electricity generation, incorporating electricity generation from wind, solar, and biomass energy alongside hydroelectricity. In line with this, the country’s Hydrogen Roadmap highlights green hydrogen as relevant, potentially serving as a fuel for both domestic and export transportation. Combining the country’s strong base of wind energy production experience with its sustainable policy, it plans to implement offshore wind farms to produce green hydrogen, making studies of its impacts crucial. This paper reviews the current social and environmental information on the Uruguayan coastal habitat, analyzes onshore wind farms’ ecological studies, and examines offshore wind farms’ global environmental and social impacts. Finally, it proposes studies for environmental approval of offshore wind farms. Full article

Despite decreasing anthropogenic mercury (Hg) emissions in Europe and the banning and restriction of many persistent organic pollutants (POPs) under the Stockholm Convention, Mediterranean marine mammals still have one of the highest body burdens of persistent pollutants in the world. Moreover, the Mediterranean basin is one of the most sensitive to climate change, with likely changes in the biogeochemical cycle and bioavailability of Hg, primary productivity, and the length and composition of pelagic food webs. The availability of food resources for marine mammals is also affected by widespread overfishing and the increasing number of alien species colonizing the basin. After reporting the most recent findings on the biogeochemical cycle of Hg in the Mediterranean Sea and the physico-chemical and bio-ecological factors determining its exceptional bioaccumulation in odontocetes, this review discusses possible future changes in the bioavailability of the metal. Recent ocean–atmosphere–land models predict that in mid-latitude seas, water warming (which in the Mediterranean is 20% faster than the global average) is likely to decrease the solubility of Hg and favor the escape of the metal to the atmosphere. However, the basin has been affected for thousands of years by natural and anthropogenic inputs of metals and climate change with sea level rise (3.6 ± 0.3 mm year⁻¹ in the last two decades), and the frequency of extreme weather events will likely remobilize a large amount of legacy Hg from soils, riverine, and coastal sediments. Moreover, possible changes in pelagic food webs and food availability could determine dietary shifts and lower growth rates in Mediterranean cetaceans, increasing their Hg body burden. Although, in adulthood, many marine mammals have evolved the ability to detoxify monomethylmercury (MMHg) and store the metal in the liver and other organs as insoluble HgSe crystals, in Mediterranean populations more exposed to the metal, this process can deplete the biological pool of Se, increasing their susceptibility to infectious diseases and autoimmune disorders. Mediterranean mammals are also among the most exposed in the world to legacy POPs, micro- and nanoplastics, and contaminants of emerging interest. Concomitant exposure to these synthetic chemicals may pose a much more serious threat than the Se depletion. Unfortunately, as shown by the literature data summarized in this review, the most exposed populations are those living in the NW basin, the main feeding and reproductive area for most Mediterranean cetaceans, declared a sanctuary for their protection since 2002. Thus, while emphasizing the adoption of all available approaches to mitigate anthropogenic pressure with fishing and maritime traffic, it is recommended to direct future research efforts towards the assessment of possible biological effects, at the individual and population levels, of chronic and simultaneous exposure to Hg, legacy POPs, contaminants of emerging interest, and microplastics. Full article

The maritime industry is addressing environmental issues, and “cold ironing” offers a promising solution. This method involves supplying ships at port with energy, reducing fossil fuel dependence and emissions, and aiding in global climate change efforts. It is especially important for islands like Lesvos, which suffer from high energy costs and environmental issues due to imported fossil fuel reliance. However, research gaps exist in using renewable energy sources (RES) for cold ironing, mainly due to insufficient data on power needs and lack of monitoring for precise calculations and the very limited applications for the case of non-interconnected islands. This study uses real data from the port of Lesvos to evaluate power requirements for cold ironing and assesses the viability of a wind power park for an electrified port with the novelty and uniqueness of developing the application on a non-interconnected island. It also examines potential CO₂ emission reductions. Data from Marine Traffic S.A. were used, considering factors like ship arrivals, hoteling duration, and engine types. This study also includes a simulation using RETScreen software for a 20 MW wind park intended for port operations. The findings show that the monthly energy demand at Mytilene port is around 6118 MWh, with an average power demand of 8.2 MW. The simulated wind park could supply about 72,080 MWh yearly, with a significant surplus (14,956 MWh annually) exportable to the grid. However, demand fluctuations mean the port might need an extra 924 MWh from the main grid. This underscores the need for additional strategies like energy storage and demand–response practices to fully transition to 100% RES-powered operations. Full article

The significance of international maritime chokepoints and the exploration of their safety and security are intricately linked to the expansion of the maritime economy, the maintenance of political and social stability, and the safeguarding of state interests. Limited efforts have been dedicated to comprehensively assessing the extent of chokepoints’ influence or establishing a global ranking of their importance using dependable maritime data. In light of the growing significance of oceans and seas in the realms of economy and society, there is a pressing need to afford heightened attention to the importance of chokepoints. In this paper, 15 critical chokepoints from around the world are studied, and the method of Location Quotient is used to calculate the influence of their radiation range utilizing the Automatic Identification System (AIS); this study charts the worldwide spatial and temporal dimensions of maritime transport spanning from 2012 to 2022. The conclusion of this study reveals the following key findings: (1) Maritime shipping trajectories exhibit fluctuating growth over time, with traffic hotspots predominantly located in continental border zones, gradually decreasing from the equator toward the poles; (2) The regions with active maritime traffic do not exhibit a positive correlation with the hotspots; instead, there is a pattern of “strong in the north, weak in the south, strong in the east, weak in the west”; (3) The Strait of Gibraltar and the Strait of Malacca are identified as the globally most strategically valuable straits for maritime shipping; (4) There is significant variation in the influence range of strategic passages, and countries with mutual dependencies may have competitive relationships. Full article

Recent projections from marine transportation experts highlight an uptick in maritime traffic, attributed to the fourth industrial revolution’s technological strides and global economic rebound. This trend underscores the need for enhanced systems for maritime accident prediction and traffic management. In this study, to analyze the flow of maritime traffic macroscopically, spatiality and continuity reflecting the output of ships are considered. The course–speed (CS) model used in this study involved analyzing COG, ROT, speed, and acceleration, which can be obtained from the ship’s AIS data, and calculating the deviation from the standard plan. In addition, spatiality and continuity were quantitatively analyzed to evaluate the smoothness of maritime traffic flow. A notable finding is that, in the target sea area, the outbound and inbound CS indices are measured at 0.7613 and 0.7501, suggesting that the outbound ship flows are more affected than inbound ship flows to the liquidity of maritime traffic flow. Using the CS model, a detailed quantitative evaluation of the spatiality and continuity of maritime traffic is presented. This approach facilitates robust comparisons over diverse scales and periods. Moreover, the research advances our understanding of factors dictating maritime traffic flow based on ship attributes. The study insights can catalyze the development of a novel index for maritime traffic management, enhancing safety and efficiency. Full article