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A growing and increasingly globalised human population, requiring the movement of goods and commodities, is placing increasing demands on the maritime industry, resulting in a concurrent increase in global shipping activities. This has consequences for the marine environment, particularly for species vulnerable to the impacts of vessel traffic. For example, vessel collisions can result in sub‐lethal or fatal injuries for marine mammals, whilst vessel noise can cause acoustic masking that effectively reduces an animal's listening space, potentially impacting their communication, navigation and foraging capacity. While a number of parallel approaches to mapping collision risk to large whales have arisen, these methods vary in their focus, usually on either co‐occurrence, collision probability, or probability of mortality. However, little attention has been given to the implications of methodological choice and data selection on subsequent risk predictions. To assess differences between these approaches, we used a standardised input dataset comprised of telemetry‐point data from tagged bowhead whales, and satellite‐based Automated Identification System (AIS) data of spatial vessel movements covering the Davis‐Baffin Arctic Marine Area. We applied this data to eight different, previously published analyses for deriving areas of vessel risk. We found that the choice of risk mapping approach affected the location, and total area, identified as ‘high risk’, and that more computationally complex approaches did not necessarily equate to different predictions. There was considerable variation in the total area of ‘high risk’ predicted within each map (range = 20–42,246 km2). Synthesis and Applications. The results underscore the importance of methodological transparency, informed data selection and careful interpretation when predicting collision risk. We provide practical recommendations for enhancing transparency when predicting risk, and discuss choice of approach suitable for different situations or management applications. It is critical that managers and policy makers are aware of the implications of applying different approaches when interpreting risk evaluation outputs. [ABSTRACT FROM AUTHOR]

Simulation technology has been extensively utilized in the study of ship entry and exit from ports, as well as navigation through waterways. It effectively mirrors the stochastic dynamic changes and interrelationships among various elements within the port system. This paper provides a comparative analysis of the advantages and disadvantages of various modeling methods used in ship navigation simulations. It proposes a simulation modeling approach for ship–port systems based on multi-agent information interaction, which simulates the entire process of ships entering and exiting ports and navigating through complex waterways, achieving a precise and detailed simulation of the entire port entry and exit process in complex waters. Using the Qiongzhou Strait as a case study, the validity and accuracy of the model are verified. The model is employed to quantitatively identify port navigation elements, assess waterway capacity, and evaluate port operational capability. Furthermore, the model enables the analysis of coordination among port channels, berths, and anchorages. Based on simulation results and port development plans, recommendations are provided to enhance port service levels and promote scientific, rational development and efficient operation of ports. [ABSTRACT FROM AUTHOR]

Safety management of maritime traffic is crucial for archipelagic states such as Indonesia, especially in areas like the connection between the Sunda Strait and the Java Sea. This study proposes a traffic lane design using the IMO routeing measures, employing the Formal Safety Assessment scientific method. The study recommends implementing Traffic Separation Schemes (TSS), precautionary areas with a recommended counterclockwise route, and inshore traffic zones. Results indicate that TSS is more effective in reducing collision frequency compared with two-way routes, with a counterclockwise flow further mitigating crossing situations. The proposed measures, particularly Risk Control Option 3, show a 54% reduction in collision frequency compared with the existing conditions. However, despite improvements, collision frequencies remain intolerable, necessitating additional strategies. The total collision frequency for all proposed measures is deemed unacceptable, requiring further methods to enhance safety. The economic evaluation shows potential savings, with estimated values for Gross Cost of Averting Fatality and Net Cost of Averting Fatality at US$ 3.21 million and US$ 2.9 million, respectively. Thus, while the proposed measures demonstrate some efficacy, additional strategies are imperative to adequately address collision risks in the designated area.

Abstract The Eastern Mediterranean region, a vital conduit for global maritime trade, faces significant environmental challenges due to marine pollution, particularly from oil spills. This is the first study covering the long period of comprehensive monitoring of oil pollution using the full mission of Sentinel-1 Synthetic Aperture Radar (SAR) data in the Mediterranean Sea, so this research aims to detect and analyze comprehensively the occurrence of oil spills in the Eastern Mediterranean over a decade (2014–2023). This study focuses on identifying geographical distribution patterns, proximity to shorelines, frequency across maritime zones, and potential sources of these spills, especially around major ports and maritime routes. This study utilizes SAR data from the Sentinel-1 satellite. The methodology included automated detection algorithms within the Sentinel application platform (SNAP) and integration with GIS mapping to study oil spill patterns and characteristics. Over 1000 Sentinel-1 scenes were investigated in the northern Mediterranean waters off the coast of Egypt, to detect and analyze 355 oil spill events with a total impacted area of more than 6000 km2. The analysis of temporal spill distribution reveals significant fluctuations from year to year. Within the entire timeline of the study, 2017 had the largest spatial areas covering one thousand square kilometers. In contrast, the single largest spill recorded during the study period occurred in 2020, covering 198.73 square kilometers. The results identified a non-uniform distribution of oil spills and primarily exhibiting elongated patterns aligned with the navigation routes. The distinct increase of oil spill incidents was within the Exclusive Economic Zone (EEZ), obviously drifted to the coastline and around major ports. The study emphasizes the critical role of remote sensing technologies in addressing environmental challenges caused by the maritime transport sector, advocating for enhanced monitoring and regulatory enforcement to protect marine ecosystems and support sustainable naval activities. The findings highlight the urgent need for targeted continuous monitoring and rapid response strategies in high-traffic maritime areas, particularly around the EEZ and major ports.

Air quality is one of the most important public health problems faced by the inhabitants of the European Union. The negative effects of air pollution include an increased incidence of various diseases and conditions, primarily respiratory, cardiovascular, and malignant diseases. Various measures are designed and implemented in all sectors to reduce the harmful consequences of air pollution. Maritime transport, when contrasted with other methods of moving people and goods, has a lesser environmental impact and its utilization is steadily increasing. To avoid a concomitant significant increase in the negative impact on the quality of the atmosphere, it is important to continuously reduce emissions of harmful substances from ships. The paper describes the most important harmful substances and their effects on human health. Based on the results of research conducted in the last five years, the effects of pollutants emitted into the air from ships on the mortality and morbidity of European Union residents are listed, with an emphasis on the effectiveness of the implemented preventive measures.

The Arctic region is undergoing significant changes in maritime accessibility. This study investigates observed ship trajectories from 2013 to 2020 to demonstrate the recent trends of Arctic traffic. A notable surge in maritime activities has been observed, particularly during summer months, driven by economic interests and the increasing popularity of existing routes. Unique patterns in the northern Barents Sea have been observed where ships favour different routes based on seasonal ice conditions. Another contribution from this work is the validation of the Arctic Traffic Accessibility Model (ATAM) using the observed ship traffic data. Results show that the ATAM model underestimates the accessibility and vessel travel speed. This is largely due to outdated model parameters. The predefined ice multipliers and calculation of ice numerals used in the ATAM may not accurately reflect real-world conditions.

The Eastern Mediterranean region, a vital conduit for global maritime trade, faces significant environmental challenges due to marine pollution, particularly from oil spills. This is the first study covering the long period of comprehensive monitoring of oil pollution using the full mission of Sentinel-1 Synthetic Aperture Radar (SAR) data in the Mediterranean Sea, so this research aims to detect and analyze comprehensively the occurrence of oil spills in the Eastern Mediterranean over a decade (2014–2023). This study focuses on identifying geographical distribution patterns, proximity to shorelines, frequency across maritime zones, and potential sources of these spills, especially around major ports and maritime routes. This study utilizes SAR data from the Sentinel-1 satellite. The methodology included automated detection algorithms within the Sentinel application platform (SNAP) and integration with GIS mapping to study oil spill patterns and characteristics. Over 1000 Sentinel-1 scenes were investigated in the northern Mediterranean waters off the coast of Egypt, to detect and analyze 355 oil spill events with a total impacted area of more than 6000 km2. The analysis of temporal spill distribution reveals significant fluctuations from year to year. Within the entire timeline of the study, 2017 had the largest spatial areas covering one thousand square kilometers. In contrast, the single largest spill recorded during the study period occurred in 2020, covering 198.73 square kilometers. The results identified a non-uniform distribution of oil spills and primarily exhibiting elongated patterns aligned with the navigation routes. The distinct increase of oil spill incidents was within the Exclusive Economic Zone (EEZ), obviously drifted to the coastline and around major ports. The study emphasizes the critical role of remote sensing technologies in addressing environmental challenges caused by the maritime transport sector, advocating for enhanced monitoring and regulatory enforcement to protect marine ecosystems and support sustainable naval activities. The findings highlight the urgent need for targeted continuous monitoring and rapid response strategies in high-traffic maritime areas, particularly around the EEZ and major ports. [ABSTRACT FROM AUTHOR]

The Arctic region is undergoing significant changes in maritime accessibility. This study investigates observed ship trajectories from 2013 to 2020 to demonstrate the recent trends of Arctic traffic. A notable surge in maritime activities has been observed, particularly during summer months, driven by economic interests and the increasing popularity of existing routes. Unique patterns in the northern Barents Sea have been observed where ships favour different routes based on seasonal ice conditions. Another contribution from this work is the validation of the Arctic Traffic Accessibility Model (ATAM) using the observed ship traffic data. Results show that the ATAM model underestimates the accessibility and vessel travel speed. This is largely due to outdated model parameters. The predefined ice multipliers and calculation of ice numerals used in the ATAM may not accurately reflect real-world conditions. [ABSTRACT FROM AUTHOR]

Safety management of maritime traffic is crucial for archipelagic states such as Indonesia, especially in areas like the connection between the Sunda Strait and the Java Sea. This study proposes a traffic lane design using the IMO routeing measures, employing the Formal Safety Assessment scientific method. The study recommends implementing Traffic Separation Schemes (TSS), precautionary areas with a recommended counterclockwise route, and inshore traffic zones. Results indicate that TSS is more effective in reducing collision frequency compared with two-way routes, with a counterclockwise flow further mitigating crossing situations. The proposed measures, particularly Risk Control Option 3, show a 54% reduction in collision frequency compared with the existing conditions. However, despite improvements, collision frequencies remain intolerable, necessitating additional strategies. The total collision frequency for all proposed measures is deemed unacceptable, requiring further methods to enhance safety. The economic evaluation shows potential savings, with estimated values for Gross Cost of Averting Fatality and Net Cost of Averting Fatality at US$ 3.21 million and US$ 2.9 million, respectively. Thus, while the proposed measures demonstrate some efficacy, additional strategies are imperative to adequately address collision risks in the designated area. [ABSTRACT FROM AUTHOR]

This article analyzes the effects of the acquisition of the Port of Piraeus by the Chinese shipping operator COSCO in July 2016 on the organization of container traffic in Europe. Using real‐time container ship positions provided by vessel tracking systems between 2015 and 2019, we study the impact of the privatization of the Greek port on its attractiveness and on that of competing ports for the ships of the various operators, and more particularly of COSCO. Difference‐in‐difference estimates suggest that the number of container ship calls to the Port of Piraeus has increased following its privatization, but that this increase in attractiveness corresponds mainly to vessels operated by COSCO with a capacity of more than 3000 twenty‐foot equivalent units, and in particular to the largest of them. We do not identify any crowding out effect between operators in Piraeus: the use of Piraeus by the vessels of other operators remains relatively unchanged. The privatization of Piraeus seems to have imposed the Greek port as COSCO's transhipment hub for the European market without this being to the detriment of ports in any other particular European area. [ABSTRACT FROM AUTHOR]

Maritime transport plays a key role in the global and local economy, accounting for 80% of global trade by volume. This makes smooth operation of the maritime transport essential. However, the sector faces the constant risk of various crises and their potential consequences that may significantly impact and disrupt the movement of goods on local, regional, and global levels. In recent years, two notable crises, namely the COVID-19 pandemic and the war in Ukraine, have been observed. This paper aims to analyse how international crises, such as armed conflicts and pandemics, influence maritime traffic and assess their impact on both global and local economies. A comparison is drawn between the periods before and during the COVID-19 pandemic and before and during the war in Ukraine to exemplify the effects of crises. The findings are then extrapolated to apply to potential future crises. Vessel movements are studied using data collected from Automatic Identification Systems (AIS). In our quantitative approach, we analyse big data using dedicated tools and visualisation techniques to gain insights into specific phenomena. The paper identifies economically significant regions for maritime traffic and examines the impact of crises on their performance. Its unique value lies in its flow-based analysis of changes in maritime traffic. The main conclusion is that China's importance for worldwide maritime traffic is increasing. This makes the global economy heavily reliant on China to a substantially greater extent than it is, for example, on Russia. Consequently, any crisis in the China region could exert a dramatic impact on the global economy. The paper also discusses observations of changes in maritime traffic following the outbreak of the war in Ukraine. [ABSTRACT FROM AUTHOR]

Simulation technology has been extensively utilized in the study of ship entry and exit from ports, as well as navigation through waterways. It effectively mirrors the stochastic dynamic changes and interrelationships among various elements within the port system. This paper provides a comparative analysis of the advantages and disadvantages of various modeling methods used in ship navigation simulations. It proposes a simulation modeling approach for ship–port systems based on multi-agent information interaction, which simulates the entire process of ships entering and exiting ports and navigating through complex waterways, achieving a precise and detailed simulation of the entire port entry and exit process in complex waters. Using the Qiongzhou Strait as a case study, the validity and accuracy of the model are verified. The model is employed to quantitatively identify port navigation elements, assess waterway capacity, and evaluate port operational capability. Furthermore, the model enables the analysis of coordination among port channels, berths, and anchorages. Based on simulation results and port development plans, recommendations are provided to enhance port service levels and promote scientific, rational development and efficient operation of ports.

A profound apprehension across the scientific and political landscape on the increasing severity of the adverse effects of climate change has provoked a rethink on tackling the challenges. These challenges have questioned the status quo on current governance arrangements and its relevance in addressing extant environmental exigencies. Besides the urgent need to reduce anthropogenic emissions and the swiftly intensifying trajectory of global warming, there is also the urgent need to adapt to the consequences of the changing climate due to its impact on societal well-being. The quest for societal behaviors to remain in sync with a rapidly changing environment has propelled scholarly exploration in the direction of the climate emergency. However, as the issue of the climate emergency in shipping is largely unexplored, research into understanding of the phenomenon is an essential prerequisite. The article uses experiences gained from the impact of the COVID-19 pandemic on global shipping as a tool to address the governance of climate emergencies in global shipping. This goal is achieved through the application of expert opinion in analogical mapping which lays the foundation for the knowledge interpretation. The results of the analysis confirmed the existence of structure similarities between pandemics and the climate emergency through attribute variables that are common to both phenomena. [ABSTRACT FROM AUTHOR]

Recognizing vessel navigation patterns plays a vital role in understanding maritime traffic behaviors, managing and planning vessel activities, spotting outliers, and predicting traffic. However, the growth in trajectory data and the complexity of maritime traffic in recent years presents formidable challenges to this endeavor. Existing approaches predominantly adopt a 'trajectory perspective', where the instantaneous behaviors of vessel groups (e.g., the homing of fishing vessels) that occurred at certain times are concealed in the massive trajectories. To bridge this gap and to reveal collective patterns and behaviors, we look at vessel patterns and their dynamics at only individual points in time (snapshots). In particular, we propose a recognition framework from the snapshot perspective, mixing ingredients from group dynamics, computational geometry, graph theory, and visual perception theory. This framework encompasses algorithms for detecting basic types of patterns (e.g., collinear, curvilinear, and flow) and strategies to combine the results. Case studies were carried out using vessel trajectory (AIS) data around the Suez Canal and other areas. We show that the proposed methodology outperformed DBSCAN and clustering by measuring local direction centrality (CDC) in recognizing fine-grained vessel groups that exhibit more cohesive behaviors. Our results find interesting collective behaviors such as convoy, turning, avoidance, mooring (in open water), and berthing (in the dock), and also reveal abnormal behaviors. Such results can be used to better monitor, manage, understand, and predict maritime traffic and/or conditions. [ABSTRACT FROM AUTHOR]

The main goal of this work is to obtain reliable predictions of pollutant concentrations related to maritime traffic (SO2, PM10, NO2, NOX, and NO) in the Bay of Algeciras, located in Andalusia, the south of Spain. Furthermore, the objective is to predict future air quality levels of the principal maritime traffic-related pollutants in the Bay of Algeciras as a function of the rest of the pollutants, the meteorological variables, and vessel data. In this sense, three scenarios were analysed for comparison, namely Alcornocales Park and the cities of La Línea and Algeciras. A database of hourly records of air pollution immissions, meteorological measurements in the Bay of Algeciras region and a database of maritime traffic in the port of Algeciras during the years 2017 to 2019 were used. A resampling procedure using a five-fold cross-validation procedure to assure the generalisation capabilities of the tested models was designed to compute the pollutant predictions with different classification models and also with artificial neural networks using different numbers of hidden layers and units. This procedure enabled appropriate and reliable multiple comparisons among the tested models and facilitated the selection of a set of top-performing prediction models. The models have been compared using several quality classification indexes such as sensitivity, specificity, accuracy, and precision. The distance (d1) to the perfect classifier (1, 1, 1, 1) was also used as a discriminant feature, which allowed for the selection of the best models. Concerning the number of variables, an analysis was conducted to identify the most relevant ones for each pollutant. This approach aimed to obtain models with fewer inputs, facilitating the design of an optimised monitoring network. These more compact models have proven to be the optimal choice in many cases. The obtained sensitivities in the best models were 0.98 for SO2, 0.97 for PM10, 0.82 for NO2 and NOX, and 0.83 for NO. These results demonstrate the potential of the models to forecast air pollution in a port city or a complex scenario and to be used by citizens and authorities to prevent exposure to pollutants and to make decisions concerning air quality. [ABSTRACT FROM AUTHOR]

In recent years, the increasing volume and complexity of ship traffic has raised the probability of collision accidents in ports, waterways, and coastal waters. Due to the relative rarity of collision accidents, near misses have been used in the research to study the collision risk in the relevant water areas. However, the factor of near miss identification is usually limited to the relative distance between ships, and the instantaneous quantification and geographical distribution of collision risk is not paid enough attention. Therefore, this article proposed a domain-based regional collision risk model that can quantify the collision risk by detecting near miss scenarios. The proposed model is capable of quantifying the collision risk in the water area instantaneously and periodically and can be used to depict the geographical distribution of collision risks in combination with a grid method and the spatial interpolation technique. To validate the proposed model, some experimental case studies were carried out using automatic identification system (AIS) data from the Bohai Strait. The results show the capability and advantage of the proposed model in regional collision risk identification and visualization, which is helpful for maritime surveillance when monitoring and organizing ship traffic and may therefore contribute to the improvement of maritime safety. [ABSTRACT FROM AUTHOR]

This document summarizes a collection of 14 research papers focused on various threats to marine mammals in the Mediterranean Sea. The studies cover topics such as depredation and bycatch of dolphins in fisheries, social dynamics of bottlenose dolphins near the River Tiber estuary, ship strikes on fin whales in the Catalan coast, contamination from plastic debris, and bacterial infections in cetaceans. The research provides valuable information for implementing mitigation strategies and conservation efforts to protect marine mammals in the region. [Extracted from the article]

IntroductionThe majority of studies on marine biosecurity focus on aquatic species, but invaders can also use dry ship compartments for dispersal; this pathway has been less explored than fouling or ballast water. Here we analysed the maritime traffic of the international Port of Gijon (south Bay of Biscay, Spain) as a case study.MethodsMain donor countries were identified from traffic data. From the Global Invasive Species Database, we detected a similar proportion of expected global alien invasive species (AIS) from fouling and containers pathways to be actually settled in the recipient region.ResultsThe AIS diversity transported via fouling was higher than that transported by containers. No significant difference between Australia, Brazil, Canada and South Africa in the proportion of global AIS actually transferred to Bay of Biscay supports the vision of port networks as a new ecosystem with multiple demes. Different AIS catalogues in the donor regions may explain a higher proportion of terrestrial AIS introduced via containers from Brazil and South Africa and marine AIS introduced via fouling.DiscussionA more careful surveillance of biota in dry ship compartments, including it in a future revision in the International Convention for Safe Containers, is recommended to reduce the contribution of shipping to biological invasions.

Oil spills pose a significant threat to marine ecosystems and coastal regions, necessitating effective monitoring and analysis for environmental management and response planning. In response, this study focused on the detection and characterization of oil spills along the North coast of Egypt, specifically in the vicinity of Port Said and the northern entrance of the Suez Canal, using data acquired from the Sentinel-1 satellite and employing advanced remote sensing techniques and spatial analysis tools including the SNAP toolbox to process and analyze the data. Analysis of the oil spills monitored by the Sentinel-1 satellite in the Mediterranean Sea during 2018 and 2019 indicates the presence of a few larger spills with a significant impact. In 2018, the minimum area of an oil spill event was 0.512 Km^2, and the maximum area was 96.729 Km^2; while in 2019, the minimum and maximum areas of the oil spills were 0.679 km^2 and 46.866 km^2, respectively. Spatial distribution analysis utilizing GIS software demonstrates that oil spill events are not confined to specific areas but occur along the entire coast of the study area. Clustering of events is observed around Port Said, with a higher concentration in the eastern Mediterranean Sea, likely attributed to increased ship transportation activity. Temporal analysis reveals that oil spill events occur throughout the year, displaying variations in frequency and size. The findings of this study would provide valuable insights for environmental assessment and the development of mitigation strategies to minimize the impact of oil spills in the study area. [ABSTRACT FROM AUTHOR]

Maritime drug trafficking operates through constantly evolving decentralized networks composed of armed organizations, small groups and logistics entities. These networks, influenced by the context, are adaptable and drive innovation among their actors. This article proposes to study this phenomenon from complexity theory, which offers tools to analyze this type of systems, and with a methodological approach based on the simulation of social systems. It is proposed to develop a simulation model based on nodes, connections, loadings and patrols. The proposed model, which will be developed and presented in subsequent articles, will provide empirical knowledge to better understand the dynamics of maritime drug trafficking and to be able to anticipate the effects of its intervention, in view of the authorities' decisions regarding this problem. [ABSTRACT FROM AUTHOR]

The Strait of Messina is characterised by a significant ship flow, especially of ferries, between its two shores. The ferry services involve four harbours, located on the Sicilian and Calabrian shores. During the epidemic emergency related to the SARS-CoV-2 virus, due to the restrictions adopted to counteract the spread of the infection, a significant reduction in ferry activities and vehicle flow occurred. These circumstances made flow data, related to different actual scenarios, available and allowed the assessment of the environmental impact of the port area. Therefore, the port area became a noteworthy case study, suited to draw conclusions regarding possible future courses of action designed to curb greenhouse gas emissions in these types of settlements. In the study, in order to assess the effect of different levels of human activity on pollutant emissions, the total CO2 emissions from ferry activities in two successive years, 2019 before the spread of the virus and 2020 when the epidemic was at its peak, were evaluated and compared. The EMEP/EEA methodology was used and, as a result, an overall reduction of 13.2% in CO2eq yearly emission rates was observed, with the major reduction of 2784 tCO2eq due to maritime traffic. [ABSTRACT FROM AUTHOR]

Non-indigenous seaweed species have been introduced to the coasts of Brittany, France for decades, with an increasing arrival rate since the 1970s due to both the introduction of the Pacific oyster and increased maritime traffic. In this study, seven species of red macroalgae originating from the Pacific Ocean were found in new locations around the coasts of Brittany between 2018 and 2022. The seaweed species belong to four different orders: Ceramiales (Antithamnion hubbsii, Polysiphonia morrowii, and Symphyocladiella dendroidea), Halymeniales (including Pachymeniopsis lanceolata and Polyopes lancifolius), Rhodymeniales (Botryocladia wrightii), and Gigartinales (Solieria sp.). The dispersal mode and putative invasive potential of each species were examined, and the species were described in terms of their macroscopic and microscopic appearance and habitat. These finds result from a combination of citizen science and long-term monitoring. Used together, these two approaches can aid in the detection of these species on other European coasts and in understanding their dispersion. [ABSTRACT FROM AUTHOR]

The on-going reduction of sea-ice in the Arctic is now facilitating maritime activities in areas previously considered inaccessible. Numerous statistics indicate that fishing and tourism are clearly gaining momentum within the wider region under discussion. Furthermore, a certain number of private companies and state-affiliated actors are setting into motion plans for promoting the use of the so-called arctic passages, while certain interesting business projects are already underway; the Yamal LNG Project is for example clearly standing out. As human presence and operations are expected to intensify within that inherently risky region, the first aim of this paper is to qualitatively identify certain business opportunities associated with the Arctic and then highlight their interrelation with the prevailing patterns of maritime traffic. Additionally, on the basis of the report titled 'Arctic Shipping Status Report – Heavy Fuel Oil (HFO) Use by Ships in the Arctic 2019' (ASSR #2) that was released during October 2020 by the Arctic Council's Working Group on the Protection of the Arctic Marine Environment (PAME), it explains the use of the various types of fuels in the region under discussion and highlights certain environmental risks. Finally, it briefly assesses the overall effectiveness of a (proposed) regulatory intervention of completely banning the use of HFO in the Arctic. This initiative can indeed have a positive contribution to protecting the region's pristine environment, but any regulations of this type must also consider the issue of fishing vessels, which are not covered under the scope of International Maritime Organization's (IMO) International Convention for the Safety of Life at Sea (SOLAS) and the International Convention for the Prevention of Pollution from Ships (MARPOL). [ABSTRACT FROM AUTHOR]

Recently, with the development of marine space around the world, friction between maritime traffic and various marine activities is intensifying. In particular, different recommendations are being made for the buffer zone between offshore wind farms and maritime traffic, as the criteria vary significantly. In order to respond to these changes in marine space, conducted this study on the change of maritime traffic patterns before and after the installation of floating LiDAR (Light Detection And Ranging) in marine facilities and apply it to future changes in maritime traffic patterns. The maritime traffic data was based on Automatic Identification System (AIS) data, and it was targeted at cargo ships and tankers with regular traffic patterns. A trajectory and spatial analysis were performed based on the AIS in the marine space. As a result of analyzing the globally maritime traffic patterns targeting the location of the installation complex of LiDARs, it can be confirmed that the existing maritime traffic patterns change into three maritime traffic patterns. Furthermore, the study employed the Hausdorff-distance algorithm for clustering analysis, categorizing vessels with similar trajectories. This approach facilitated a locally analysis of the buffer zone associated with individual LiDAR, considering the length of the vessels. As a result, it was analyzed that each vessel navigated at different buffer zone depending on the size of the vessel, and it is possible for safe navigation and forecast the future maritime traffic patterns.

Predicting air quality is a very important task, as it is known to have a significant impact on health. The Bay of Algeciras (Spain) is a highly industrialised area with one of the largest superports in Europe. During the period 2017–2019, different data were recorded in the monitoring stations of the bay, forming a database of 131 variables (air pollutants, meteorological information, and vessel data), which were predicted in the Algeciras station using long short-term memory models. Four different approaches have been developed to make SO2 and NO2 forecasts 1 h and 4 h in Algeciras. The first uses the remaining 130 exogenous variables. The second uses only the time series data without exogenous variables. The third approach consists of using an autoregressive time series arrangement as input, and the fourth one is similar, using the time series together with wind and ship data. The results showed that SO2 is better predicted with autoregressive information and NO2 is better predicted with ships and wind autoregressive time series, indicating that NO2 is closely related to combustion engines and can be better predicted. The interest of this study is based on the fact that it can serve as a resource for making informed decisions for authorities, companies, and citizens alike. [ABSTRACT FROM AUTHOR]

Ship hull fouling is recognized as an important vector for the introduction of nonindigenous species (NIS), which has been studied globally but no empirical works exist in the Southeast Pacific. The present study examined fouling organisms on the hulls of three ships in one international Chilean port, and compared them with those on settling plates and natural substrates. Also, genetic analyses were perfomed on the most common NIS recorded in order to explore number and potential origin of the genetic linages found. The highest number of total taxa and NIS were found on ship hulls, with three species identified as NIS in ship samplings. Settling plates displayed the largest number of taxa, with a large abundance of the invasive tunicate Ciona robusta, which also showed high mitochondrial genetic diversity. This study showed that Chilean coasts are subjected to both NIS colonization and propagule pressure through ship hulls. Biosecurity measures should urgently be taken on ship hulls along these coasts. [ABSTRACT FROM AUTHOR]

This research is based on a positivist paradigm of a quantitative approach with statistical elements, which allowed delving into the situation of the research variables, of a descriptive - explanatory - propositional type; of a non-experimental design, taking 105 users of the National Port System as a sample population, for which a 29-item questionnaire with a Likert and dichotomous assessment scale was applied, where the dimensions and indicators of the variable, the El Data analysis was performed with statistical and instrumental validity using the IBM SPSS software. The results achieved according to the goals of the analysis, indicated that 78% of the users of the national port system have little knowledge about marine pollution, 18% Regular and 4% Good; In relation to the magnitude of application of the MARPOL Annexes, 62% are classified as Good, 23% with little understanding and 14% as regular. The results demonstrate the need to propose an initiative that defines programs that involve the port sector, achieving one: awareness, training, implementation and monitoring that manage to provide a relevant contribution, with the application of MARPOL annexes I, II, III, IV and V. to which Ecuador is attached. [ABSTRACT FROM AUTHOR]

This paper aims to analyse maritime traffic safety assessment via a traffic flow simulation model. The model developed via NetLogo platform, agent-based modelling and simulation approach. And it is implemented on an open sea area, at the Aegean Sea to show its applicability. The model is verified through experiments conducted in the area. The simulation outputs give the risky locations and scores. Risky locations and risk scores in the area are determined as the outputs of the simulation runs. A traffic separation scheme is established to prove the suitability of the model as adaptable and updatable. After the scheme is implemented, it shows that the potential collision locations and scores change considerably. The developed model is convenient to simulate various conditions by changing the input parameters on maritime traffic safety. [ABSTRACT FROM AUTHOR]

In recent decades, the Spanish port system has been investing in the development of infrastructures aimed at attracting the cruise market. For this reason, this paper analyses, using a methodology based on data envelopment analysis (DEA), the efficiency of the Spanish port system for the cruise market. Most of the port authorities want to attract and maintain this traffic in their ports, due to the economic impact it has on them. Based on the data provided by Puertos del Estado and the port authorities in their annual reports, such as the number of cruise passengers per port or port authority, the number of stopovers or ships that visit our ports each year, and the infrastructures that have been developed for this market, an efficiency analysis was carried out to draw conclusions at the level of the port system and each port authority in terms of operational efficiency. Focusing the research on Malaga, the current situation was analyzed, as well as the forecasts that resulted from the research for the future development of the port in terms of cruise ships. [ABSTRACT FROM AUTHOR]

The North Sea is one of the most industrialised marine regions globally. We integrated cetacean-dedicated aerial surveys (2015–2022) with environmental covariates and ship positions from the Automatic Identification System (AIS) to investigate the disturbance radius and duration on harbour porpoise distribution. This study is based on 81,511 km of line-transect survey effort, during which 6511 harbour porpoise groups (8597 individuals) were sighted. Several proxies for ship disturbance were compared, identifying those best explaining the observed distribution. Better model performance was achieved by integrating maritime traffic, with frequent traffic representing the most significant disturbance to harbour porpoise distribution. Porpoises avoided areas frequented by numerous vessels up to distances of 9 km. The number of ships and average approach distance over time improved model performance, while reasons for the lower performance of predicted ship sound levels remain unclear. This study demonstrates the short-term effects of maritime traffic on harbour porpoise distribution. [Display omitted] • Cetacean survey data (2015–2022) in the North Sea were combined with vessel positions. • Effects of vessel presence on harbour porpoise distribution were investigated. • Spatial avoidance was detected, particularly in areas with heavy or frequent traffic. • Best predictors were the number of vessels and average approach distance over time. • This broad-scale study shows short-term effects over 9 km on porpoise distribution. [ABSTRACT FROM AUTHOR]

Recognizing vessel navigation patterns plays a vital role in understanding maritime traffic behaviors, managing and planning vessel activities, spotting outliers, and predicting traffic. However, the growth in trajectory data and the complexity of maritime traffic in recent years presents formidable challenges to this endeavor. Existing approaches predominantly adopt a ‘trajectory perspective’, where the instantaneous behaviors of vessel groups (e.g., the homing of fishing vessels) that occurred at certain times are concealed in the massive trajectories. To bridge this gap and to reveal collective patterns and behaviors, we look at vessel patterns and their dynamics at only individual points in time (snapshots). In particular, we propose a recognition framework from the snapshot perspective, mixing ingredients from group dynamics, computational geometry, graph theory, and visual perception theory. This framework encompasses algorithms for detecting basic types of patterns (e.g., collinear, curvilinear, and flow) and strategies to combine the results. Case studies were carried out using vessel trajectory (AIS) data around the Suez Canal and other areas. We show that the proposed methodology outperformed DBSCAN and clustering by measuring local direction centrality (CDC) in recognizing fine-grained vessel groups that exhibit more cohesive behaviors. Our results find interesting collective behaviors such as convoy, turning, avoidance, mooring (in open water), and berthing (in the dock), and also reveal abnormal behaviors. Such results can be used to better monitor, manage, understand, and predict maritime traffic and/or conditions.

In recent years, the increasing volume and complexity of ship traffic has raised the probability of collision accidents in ports, waterways, and coastal waters. Due to the relative rarity of collision accidents, near misses have been used in the research to study the collision risk in the relevant water areas. However, the factor of near miss identification is usually limited to the relative distance between ships, and the instantaneous quantification and geographical distribution of collision risk is not paid enough attention. Therefore, this article proposed a domain-based regional collision risk model that can quantify the collision risk by detecting near miss scenarios. The proposed model is capable of quantifying the collision risk in the water area instantaneously and periodically and can be used to depict the geographical distribution of collision risks in combination with a grid method and the spatial interpolation technique. To validate the proposed model, some experimental case studies were carried out using automatic identification system (AIS) data from the Bohai Strait. The results show the capability and advantage of the proposed model in regional collision risk identification and visualization, which is helpful for maritime surveillance when monitoring and organizing ship traffic and may therefore contribute to the improvement of maritime safety.

Maritime transports play a critical role in international trade and commerce. Massive vessels sailing around the world continuously generate vessel trajectory data that contain rich spatial–temporal patterns of vessel navigations. Analyzing and understanding these patterns are valuable for maritime traffic surveillance and management. As essential techniques in complex data analysis and understanding, visualization and visual analysis have been widely used in vessel trajectory data analysis. This paper presents a literature review on the visualization and visual analysis of vessel trajectory data. First, we introduce commonly used vessel trajectory data sets and summarize main operations in vessel trajectory data preprocessing. Then, we provide a taxonomy of visualization and visual analysis of vessel trajectory data based on existing approaches and introduce representative works in details. Finally, we expound on the prospects of the remaining challenges and directions for future research.

For developing national maritime traffic routes through the coastal waters of Korea, the customary maritime traffic flow must be accurately identified and quantitatively evaluated. In this study, the occupancy time of ships in cells was calculated through a density analysis based on automatic identification system data. The density map was statistically created by logarithmically transforming the density values and adopting standard deviation-based stretch visualization to increase the normality of the distribution. Many types of traffic routes such as open-sea, coastal, inland, and coastal access routes were successfully identified; moreover, the stretch color ramp ratio was reduced to identify routes having relatively high density. Adopting a single standard deviation and demonstrating the top 25% of color ramps, the analysis afforded the main routes through which customary traffic flows. This novel density analysis method and statistical visualization method is expected to be used for developing national maritime traffic routes and should ultimately contribute to maritime safety. Moreover, it provides a scientific means and simulator for determining the navigation area and analyzing conflicts with other activities in marine spatial planning. [ABSTRACT FROM AUTHOR]

In order to detect multi-ship encounter situations and improve the safety of navigation, this paper proposed a model which was able to mine multi-ship encounter situations from Automatic identification system (AIS) data and analyze the encounter spatial-temporal process and make collision avoidance decisions. Pairwise encounters identification results and ship motion index were combined into a ship encounter graph network which can use the complex network theory to describe the encounter spatial-temporal process. Network average degree, network average distance and network average clustering coefficient were selected. Based on the recognition results of pairwise encounter identification results, a discrete multi-ship encounter network is constructed. The process of multi-ship encounters from simple to complex to simple is mined based on the process of average network degree from 0 to 0 to obtain a continuous spatial-temporal process. The results can be used for multi-ship encounter situation awareness, multi-ship collision avoidance decision-making and channel navigation evaluation, and also provide data for machine learning. Quaternary dynamic ship domain, fuzzy logic and the weighted PageRank algorithm were used to rank the whole network risk, which is critical to "key ship collision avoidance." This method overcame the problem that the traditional collision risk evaluation method is only applicable to the difference between two ships and ship perception. The risk rank combined with the artificial potential field method was used. Compared with the traditional artificial potential field method, this method has fewer turns and a smoother trajectory. [ABSTRACT FROM AUTHOR]

Angiostrongylus cantonensis is an important emerging and zoonotic nematode that has been reported worldwide since its first description in Asia 86 years ago. Among places where this parasite has been recently described, insular regions of northwest Africa seem to be particularly relevant. We performed a systematic review in scientific databases to search and extract information about all reports describing cases of A. cantonensis in Spain until July 2021. As a result, seven surveys about the presence of this pathogen in Spanish insular regions were found, especially in the Canary Islands, as well as a non‐autochthonous report of A. cantonensis in the mainland Spain. The lack of reliable information about the presence or absence of this nematode in the Iberian Peninsula highlights the need for further studies concerning this emerging pathogen since rodents acting as competent definitive hosts of A. cantonensis are widely distributed in the mainland. Moreover, the high maritime traffic daily registered in Spanish ports could be a main entrance pathway for A. cantonensis or its intermediate hosts in the country due to the frequent and direct connection between these points and regions where this pathogen is endemic. We encourage to focus further efforts on investigating the current epidemiological situation of A. cantonensis in the Iberian Peninsula, just as in other Mediterranean countries with similar epidemiological, ecological and geographical characteristics. In this sense, the relevant implications of this parasite for animal and public health make necessary to act integrating different viewpoints under the One Health perspective. [ABSTRACT FROM AUTHOR]

The Asian mussel Arcuatula senhousia is known as a successful invader into coastal and estuarine environments worldwide. We here report its Northward expansion along the French Atlantic coast evidenced by new records from the commercial ports of La Rochelle (Bay of Biscay) and Dunkirk (North Sea), both in 2018, following sampling of benthic macroinvertebrates. To date, the Asian mussel has only been observed along the French coast from the Mediterranean Sea and the Southern part of the Bay of Biscay. Its presence in these new locations, which are important for international maritime transport, is most likely related to ship ballast water and/or sediment as vector of introduction. These new insights suggest that this species has not yet finished its expansion process, which could be at the origin of irreversible impacts on ecosystem structure, functioning and services. [ABSTRACT FROM AUTHOR]

Abstract The expanded Panama Canal opened on June 26, 2016. This expansion is the third set of locks that enabled the canal to double its capacity through the addition of new traffic lanes, which allowed neo-Panamax and some post-Panamax vessels to transit across the canal. The widening of the canal has increased maritime traffic within Latin America and the Caribbean (LAC). Major ports in the regions have made huge investments in port expansion and infrastructural development to accommodate neo-Panamax vessels. In this study, we investigated the impact of the Panama Canal expansion (PCE) on the Latin America and the Caribbean (LAC) ports by using the Difference in Difference (DID) method. This impact was evaluated for 100 major and regular ports within the three sub-regions of LAC, namely Caribbean, Central, and South America, before and after the treatment effect, that is, the PCE. The findings from the model revealed that the average container port throughput (TEUs) for the treated ports (DTrp) was more than that of the controlled ports (CONTp) with transshipment hub, Central America, and South America having 20%, 12%, and 34% growth, respectively, since the PCE (the treatment) except for the Caribbean ports (DTrp), which experienced losses of 8% within the LAC region from 2010 to 2019.

Abstract The aim of this paper is to detect port maritime communities sharing similar international trade patterns, by a modelisation of maritime traffic using a bipartite weighted network, providing decision-makers the tools to search for alliances or identify their competitors. Our bipartite weighted network considers two different types of nodes: one represents the ports, while the other represents the countries where there are major import/export activity from each port. The freight traffic among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the Spanish case is considered, with the data segmented by each type of traffic for a fine tuning. A sort of link prediction is possible, finding for those communities with two or more ports, countries that are part of the same community but with which some ports do not have yet significant traffic. The evolution of the traffics is analyzed by comparing the communities in 2009 and 2019. The set of communities formed by the ports of the Spanish port system can be used to identify global similarities between them, comparing the membership of the different ports in communities for both periods and each type of traffic in particular.

The role of navigation in transporting and introducing non-indigenous species (NIS) in ports is globally acknowledged, and maritime traffic is correlated with increasing NIS introductions. On the other hand, different types of vessels can occur in a port (e.g., for commercial or recreational purposes) and the success of a NIS in a new area also depends on several chemical-physical and biotic conditions of the arrival port. In this context, a study was conducted in 2020 in three marinas at Sanremo (Ligurian Sea, Italy) with the aim to assess if boat traffic influences the presence of NIS in marine fouling communities. Samples were collected from docks and pontoons with a hand-held rigid net in the marinas of Sanremo (Porto Sole, characterized by international recreational boat traffic; and Porto Vecchio, hosting only local fishing boats), as well as in Ospedaletti, a nearly finished, abandoned and unused marina. Overall, 47 species (including 9 NIS), 45 (8 NIS) and 86 (2 NIS) were collected in Porto Sole, Porto Vecchio and Ospedaletti, respectively. Number and proportion of NIS were significantly lower in the unused marina of Ospedaletti in comparison with the other two ones, which in turn exhibited similar sessile assemblages and comparable NIS richness. The peculiarity of Ospedaletti fouling community, despite the geographical proximity and similar habitat conditions of the other marinas, highlights the role of boating traffic in facilitating NIS settlement, while the sole presence of artificial substrates is not sufficient to promote NIS introduction. This site could provide opportunities for experimenting novel NIS management measures. • Comparison of fouling communities of two active and one inactive marinas. • A highly diverse fouling community was observed in the inactive marina. • A higher number of non-indigenous species (NIS) was observed in the active marinas. • Importance of the role of small boat traffic in NIS introduction. [ABSTRACT FROM AUTHOR]

Ship Time Headway (STH) is used in maritime navigation to describe the time interval between the arrivals of two consecutive ships in the same water area. This measurement may offer a straightforward way to gauge the frequency of ship traffic and the likelihood of congestion in a particular area. STH is an important factor in understanding and managing the dynamics of ship movements in busy waterways. This paper introduces a hybrid deep learning method for predicting STH in time domain. The method integrates the Seasonal-Trend Decomposition using Loess (STL), Multi-head Self-Attention (MSA) mechanism into Long Short-Term Memory (LSTM) neural network. The STH dataset was extracted from the Automatic Identification System (AIS) through ship trajectory spatial motion, and the seasonal, trend and residual components of the decomposition were then determined from the STH dataset using the STL algorithms. MSA-LSTM is adopted to comprehensively capture the evolving patterns of STH from the sequence. Comparison studies with existing methods demonstrate the accuracy and robustness of the predictions provided by this method, indicating that the proposed method outperforms other models in terms of prediction performance and learning capabilities. By predicting STH, the method offers potential to assist maritime traffic managers and navigators in assessing ship flow, thereby enabling them to make informed decisions on navigation safety and efficiency. [ABSTRACT FROM AUTHOR]

• A method to detect and classify ship abnormal behaviour is proposed. • A Sliding Window algorithm is adopted to detect ship abnormal behaviour. • Ship abnormal behaviour is further characterised by several motion features. • A clustering algorithm is applied to group similar abnormal behaviour patterns. • The Random Forest method is used for abnormal behaviour classification. This paper proposes a method for detecting and classifying ship abnormal behaviour in ship trajectories. The method involves generating parameter profiles for the ship's trajectory and applying a Sliding Window algorithm to detect the ship's abnormal behaviour. Then, several features are adopted to effectively describe the characteristics of each ship's abnormal behaviour, such as the standard deviation of speed, detour factor, maximum drift angle, accumulative change of Course Over Ground and maximum lateral distance to the ship route. A density-based clustering algorithm is applied to group similar abnormal behaviour patterns according to the feature similarity, and the Random Forest Classification method is used to train a classification model based on the features extracted from the clusters. The proposed method is then tested on historical ship trajectory data provided by the Automatic Identification System. The results suggest that the method effectively identifies and classifies different abnormal behaviours in the ship trajectories. [ABSTRACT FROM AUTHOR]