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Commercial shipping activity plays a crucial role in the unintentional primary and secondary introduction of aquatic Non-Indigenous species (NIS), with ballast water (BW) and hull biofouling being the two major vectors of NIS transportation. The aim of this study is to identify potential high-risk donor port areas that may act as pools for NIS introduction in Saronikos Gulf, Greece. For the purpose of the study, we conducted a regional risk assessment and produced a NIS watch list based on the commercial vessel arrivals at the major ports of the Saronikos Gulf (Piraeus and Elefsis) for the period 2020–2022. In our risk analysis, we used the two most important factors for ship-mediated species introductions identified in the literature: salinity and biogeographic region of the voyage last origin ports. Then, combined with data on vessel arrivals, based on marine traffic data collected from the Marine Traffic online platform, we produced a NIS watch list for the study area. The most highrisk ports for primary introductions were found to be in the Temperate Northern Atlantic (e.g. Gemlik, Ambarli, Asyaport and Derince in Türkiye, Sines in Portugal), Western Indo-Pacific (e.g. Jeddah in Saudi Arabia, Aqaba in Jordan) and the Central Indo-Pacific (e.g. Singapore). For secondary introduction, the most high-risk voyage origin ports are located in the Levantine Sea (e.g. Limassol in Cyprus, Alexandria and Port Said in Egypt, Haifa and Ashdod in Israel, Iskenderun, Mersin and Nemrut in Türkiye), the Aegean Sea (e.g. Izmir in Türkiye) and the Ionian Sea (e.g. Marsaxlokk in Malta). Our watch list included 44 high risk and 13 medium risk NIS to be transferred to Saronikos Gulf. Of these, 38 high-risk species are already present in the Mediterranean, 6 high-risk species are absent from the Mediterranean and 18 species pose a high risk for both primary and secondary introduction. [ABSTRACT FROM AUTHOR]

Arctic shipping activities are increasing in the context of sea ice decline. However, research gaps persist in studying recent Arctic shipping activities across various vessel types and their connection with sea ice conditions. Utilizing Automatic Identification System (AIS) data and sea ice satellite observations between 2015 and 2020, these matters are delved into this study. A discernible overall growth trend in Arctic traffic occupancy occurs from 2015 to 2020 during summer and autumn. Excluding passenger ships, the traffic occupancy trend for each ship type closely parallels that for all ships. Variations in traffic occupancy along the Northeast Passage dominate that in the entire Arctic. As sea ice diminishes, both Arctic traffic occupancy and its variability noticeably increase. Further examination of the relationship between shipping activities and ice conditions reveals that increased traffic occupancy corresponds significantly to diminishing sea ice extent, and the constraint imposed by sea ice on Arctic traffic occupancy weakens, while the 6-year AIS data could lead to uncertainties. In summary, as the Arctic sea ice declines continuously, not only sea ice but also additional social, military, and environmental factors constraining marine activities should be considered in the future operation of Arctic shipping. [ABSTRACT FROM AUTHOR]

The accurate detection of seafarers' unsafe behaviors is of great significance to improve the ship navigation safety. This study proposes an improved deep learning framework with a self-made dataset to detect the unsafe behavior of seafarers on duty. In order to increase the detection speed, the improved Cross Stage Partial connections (CSP) module is proposed to replace the original CSP module in the neck network of traditional algorithm. The efficient channel attention (ECA) module is also introduced to the backbone network of conventional algorithm as the attention mechanism network. In addition, the learning and representation capacities of the improved deep learning framework are promoted by redesigning the sizes of anchor boxes. The experiment results show that the proposed framework outperforms traditional object detection algorithms (e.g., YOLOv5s, R-CNN) in detecting seafarers' unsafe behaviors because of the much higher detection speed and detection accuracy. [ABSTRACT FROM AUTHOR]

Safe navigation at sea is more important than ever. Cargo is usually transported by vessel because it makes economic sense. However, marine accidents can cause huge losses of people, cargo, and the vessel itself, as well as irreversible ecological disasters. These are the reasons to strive for safe vessel navigation. The navigator shall ensure safe vessel navigation. He must plan every maneuver and act safely. At the same time, he must evaluate and predict the actions of other vessels in dense maritime traffic. This is a complicated process and requires constant human concentration. It is a very tiring and long-lasting duty. Therefore, human error is the main reason of collisions between vessels. In this paper, different reinforcement learning strategies have been explored in order to find the most appropriate one for the real-life problem of ensuring safe maneuvring in maritime traffic. An experiment using different algorithms was conducted to discover a suitable method for autonomous vessel navigation. The experiments indicate that the most effective algorithm (Deep SARSA) allows reaching 92.08% accuracy. The efficiency of the proposed model is demonstrated through a real-life collision between two vessels and how it could have been avoided. [ABSTRACT FROM AUTHOR]

When conducting accident analysis, the assessment of risk is one of the important links. Moreover, with regards to crew training, risk cognition is also an important training subject. However, most of the existing researches only rely on a single or a few data sources. It is necessary to fuse the collected multi-source data to obtain a more comprehensive risk evaluation model. There are few studies on the three-dimensional (3D) multi-modal data-fusion-based trajectory risk cognition. In this paper, a fuzzy logic-based trajectory risk cognition method is proposed based on multi-model spatial data fusion and accident data mining. First, the necessity of multi-model spatial data fusion is analysed and a data-fusion-based scene map is constructed. Second, a risk cognition model fused by multiple factors, multi-dimensional spatial calculations as well as data mining results is proposed, including a novel ship boundary calculation approach and newly constructed factors. Finally, a radar chart is used to illustrate the risk, and a risk cognition system is developed. Experiment results confirm the effectiveness of the method. It can be applied to train human operators of unmanned ship systems. [ABSTRACT FROM AUTHOR]

The influence of shipping on air quality over the Southern Baltic Sea was investigated by characterizing the horizontal and vertical distribution of aerosols and trace gases using airborne measurements in the summer of 2015. Generally, continental and anthropogenic emissions affected the vertical distribution of atmospheric pollutants, leading to pronounced stratification in and above the marine boundary layer and controlling the aerosol extinction. Marine traffic along the shipping corridor "Kadet Fairway" in the Arkona Basin is shown to influence the presence and properties of both trace gases and aerosol particles in the lowest atmospheric layer. Total particle number concentration and NOy mixing ratio increased in the corridor plumes, relative to background, by a factor 1.55 and 3.45, respectively. Titration, triggered by the enhanced presence of nitrogen compounds, led to a median ozone depletion of 19% in the corridor plumes. The enforcement of the Sulphur Emission Control Area (SECA) might be responsible for the minor sulphur dioxide increase (20%) in the corridor plumes. Ship traffic caused a minor enhancement of black carbon mass concentration, estimated to be around 10%. The study of individual ship plumes indicated that ship emitted aerosol was substantially different from background aerosol: fresh ship exhaust was preferentially enriched in aerosol particles with diameters below 100 nm and in black carbon particles with core diameters above 300-400 nm. With the present work the impact of marine traffic on the concentration and properties of atmospheric components within the marine boundary layer over the open water of the Southern Baltic Sea is assessed with airborne observations for the first time. Due to the high uncertainty affecting the estimations of ship emissions, this dataset represents a valuable reference for the assessment of ship emission inventories and related environmental-climatic impacts on the Southern Baltic Sea. [ABSTRACT FROM AUTHOR]

The paper estimates the exhaust emissions of marine traffic in the Port of Rijeka based on the ship’s data obtained from the pilot company. The Port of Rijeka is the largest port in Croatia that includes several berthing locations with different terminals. The estimation is made for each of them respecting carbon dioxide (CO2), nitrogen oxides (NOx), sulphur oxides (SOx) and particulate matter (PM) as well as for the amount of total emissions for the area. The aim is to prepare basic records for estimation and further monitoring with respect to changes in the ongoing environmental regulation and restrictions. This paper will contribute to the overall national strategy of preparing shipping emission inventories for the Republic of Croatia. The estimation method is based on the bottom– up approach widely used in such research that starts with ship characteristics and activities when approaching the port. [ABSTRACT FROM AUTHOR]

The development of coastal infrastructure and related maritime transport necessitatesthe intensification of vessel traffic monitoring. Navigation systems used in this research are traditionally based on the information transmitted by radio waves. Marine traffic safety requires constant supervision carried out by dedicated systems, the operation of which may be limitedby difficult environmental conditions. The possibilities of supporting navigation systems with underwater observation systems are explored here. The research was carried out using an underwater measurement system. Local disturbances of the hydroacoustic and hydrodynamic field from the moving vessels were analysed. The potential for identifying a moving vessel, for example for offshore infrastructure security purposes, is demonstrated. [ABSTRACT FROM AUTHOR]

The tourist attraction of a cruise itinerary is composed of the on board experience plus the shore-based experience. Due to the positive dynamism of the cruise industry since the beginning of the twenty-first century, cruise lines are driven to innovate to create new experiences that help maintain high demand rates. From the point of view of creating new experiences on land, cruise lines move their vessels from one destination region to another to maximise the vessel's occupancy and to offer itineraries with a wider variety of shore-based attractions. These new itinerary designs lead to alterations in the seasonality patterns of the neighbouring regions. In this work, the 17 most important cruise ports located in the northeast quadrant of the Atlantic Ocean are analysed to find groups of ports with homogeneous seasonality patterns using clustering techniques. The analysis showed two different seasonality patterns. Consequently, some implications to improve the use of the ports of both clusters are included. [ABSTRACT FROM AUTHOR]

With the continuous growth of international trade and the number of ships, the pressure on marine safety is increasing. To strengthen the efficiency and pertinence of accident prevention and control measures, in-depth research on the characteristics of marine traffic accidents is of great significance. This study uses a Weighted Association Rule Mining (WARM) approach to investigate the association between marine traffic accidents characteristics. The Mediterranean Sea and Black Sea play a crucial role in global maritime transportation. The marine traffic accidents in the Mediterranean Sea and Black Sea region from 2006 to 2020 are collected from the Lloyd's List Intelligence (LLI) database. Then, WARM is applied to obtain the characteristics of marine traffic accidents. The findings show that Flag of Convenience (FOC) vessels in the Mediterranean have a lower accident rate than non-FOC vessels do. Moreover, the results reveal a strong relationship between accidents and the age, gross tonnage, and ship type. Older general cargo ships with a gross tonnage between 500 and 3000 tons are more prone to accidents. This research provides insights for authorities to develop targeted measures for preventing specific types of accidents and enhancing marine safety. • In this study, the main objective was to investigate maritime accident characteristics and improve navigation safety. • It is fully considered that in the association rule approach, different accidents may have their own weights. • The weighted association rule approach is employed to mine the causal characteristics of ship traffic accidents. • The results of the study reveal a strong relationship between the age, gross tonnage, and ship type of the accidents. [ABSTRACT FROM AUTHOR]

Automatic Identification System (AIS) data is used for monitoring the movements of vessels live movements through instant transmission of vessel information while, at the same time, historical AIS data is used for marine traffic analysis by researchers. There are several methods and computer programs developed for the analysis of marine traffic by the use of AIS data. Combining the intersection algorithm proposed by Antonio (1992) and distance calculation method, this study develops a method to analyse vessel distribution on a selected cross sectional line (SCS) in the Northern Aegean Sea. As a complementary to the new methods proposed, a desktop application is developed in C# programming language to visualize the vessel distribution on the SCS line. SQL server is used for AIS data storage and analysis. The study is conducted over 7-day AIS data, specifically 2.382.469 rows and 42.884.442 data in total, belonging to the Northern Aegean Sea marine traffic. As a result, the mapping of the movements of different types of vessels in the Northern Aegean Sea is effectively performed and Frequency-Distance, Draught-Distance, SOG-Distance, SOG-COG distributions on the SCS line are successfully analysed by the new method introduced. [ABSTRACT FROM AUTHOR]

Ship grounding is a major maritime hazard that poses great consequences. Risk and sustainability associated with ship grounding need to be rationally assessed for a safe and sustainable maritime traffic. This paper presents a probabilistic risk analysis of ship grounding hazard considering damage caused by bottom penetration. Sustainability is introduced for ship grounding risk analysis for a synthesized assessment of the damage consequences. Sustainability indicators assess the economic, social, and environmental performance following a hazard event. In terms of ship grounding incident this includes the ship damage repair, operational delay, cargo loss, injury or fatality of crew, and environmental impact such as clean-up of oil spill. The economical, social, and environmental metrics are evaluated separately and then converted into an integrated monetary metric. Utility function that can incorporate attitude towards risk taking is used in the analysis for decision making purposes in risk control. The proposed approach is illustrated using a hypothetical oil tanker grounding in the Delaware Bay region. [ABSTRACT FROM AUTHOR]

Automatic Identification System (AIS) data is used for monitoring the movements of vessels live movements through instant transmission of vessel information while, at the same time, historical AIS data is used for marine traffic analysis by researchers. There are several methods and computer programs developed for the analysis of marine traffic by the use of AIS data. Combining the intersection algorithm proposed by Antonio (1992) and distance calculation method, this study develops a method to analyse vessel distribution on a selected cross sectional line (SCS) in the Northern Aegean Sea. As a complementary to the new methods proposed, a desktop application is developed in C# programming language to visualize the vessel distribution on the SCS line. SQL server is used for AIS data storage and analysis. The study is conducted over 7-day AIS data, specifically 2.382.469 rows and 42.884.442 data in total, belonging to the Northern Aegean Sea marine traffic. As a result, the mapping of the movements of different types of vessels in the Northern Aegean Sea is effectively performed and Frequency-Distance, Draught-Distance, SOG-Distance, SOG-COG distributions on the SCS line are successfully analysed by the new method introduced. [ABSTRACT FROM AUTHOR]

The Strait of Istanbul is one of the most congested and risky waterways in the world. Navigation patterns have been investigated using Automatic Indentification System (AIS) data collected over a long period. 1·5 billion AIS messages, gathered over a year from 309,000 moving vessels in the Strait were stored in a Structured Query Language (SQL) database. Grid-based analysis is used to track the time, number, position, type, dimension, heading, speed and course over ground of ships. Local traffic, whose effect on maritime risk has often been neglected, is found to dominate transit traffic by a ratio of eight to one. Vessel distributions indicate that the most common lengths of vessels are 100m and 170 m. Draught analysis shows a net transfer of goods from north to south. Southbound vessels are more likely to exceed the enforced speed limit due to predominant currents. Courses indicate that the local traffic strongly affects navigation patterns, especially at sectors with sharp turns. All these results help to understand the navigation patterns of ships and give the necessary input to assist in predicting maritime risk. [ABSTRACT FROM AUTHOR]

This paper describes a Multi-Criteria-Analysis (MCA)-based Decision Support System (DSS) developed for the management of incidents in maritime traffic. The developed DSS helps to organise a large quantity of information related to emergency management, spatial data and "live" data (radar data, weather forecasting data), to make it available to decision makers in a comprehensible and user-friendly way. Special care has been taken to model human Decision-Making (DM) processes during incident situations. Since the DM process is always multi-criterial, a Multi-Criteria Decision-Making (MCDM) method called Preference Ranking Organisation Method for Enrichment Evaluations (PROMETHEE) is used. However, a simplified variation of PROMETHEE II has been utilised to make results more understandable to non-expert users. The aim of this research is to incorporate effective DSS in human DM processes, thus reducing the possibility of making poor decisions. The concept of Web MCA-based DSS is presented as a case study: Web DSS developed for the east coast of the Adriatic Sea. [ABSTRACT FROM AUTHOR]

In recent years, the growth of marine traffic in ports and their surroundings raise the traffic and security control problems and increase the workload for traffic control operators. The automated identification system of vessel movement generates huge amounts of data that need to be analysed to make the proper decision. Thus, rapid self-learning algorithms for the decision support system have to be developed to detect the abnormal vessel movement in intense marine traffic areas. The paper presents a new self-learning adaptive classification algorithm based on the combination of a self-organizing map (SOM) and a virtual pheromone for abnormal vessel movement detection in maritime traffic. To improve the quality of classification results, Mexican hat neighbourhood function has been used as a SOM neighbourhood function. To estimate the classification results of the proposed algorithm, an experimental investigation has been performed using the real data set, provided by the Klaipėda seaport and that obtained from the automated identification system. The results of the research show that the proposed algorithm provides rapid self-learning characteristics and classification. [ABSTRACT FROM AUTHOR]

This study examines maritime routes between ports along the Atlantic coast of the US, utilising Automated Identification System (AIS) data for the years 2010 through 2012. The delineation of vessel routes conducted in this study was motivated by development planned for offshore Wind Energy Areas (WEAs) along the Atlantic coast of the US and the need to evaluate the effect of these development areas on commercial shipping. To this end, available AIS data were processed to generate commercial vessel tracks for individual vessels, though cargo vessels are the focus in this study. The individual vessel tracks were sampled at transects placed along the Atlantic coast. The transect samples were analysed and partitioned by voyages between Atlantic ports to facilitate computation of vessel routes between ports. The route boundary analysis utilised a definition from UK guidance in which routes' boundaries encompassed 95% of the vessel traffic between ports. In addition to delineating route boundaries, we found multi-modal transverse distributions of vessels for well-travelled routes, which indicated preference for lanes of travel within the delineated routes. [ABSTRACT FROM AUTHOR]

Ship domain is crucial for collision risk assessments and may vary depending on the navigation area. In this study, an empirical ship domain model for coastal waters is proposed. The proposed ship domain model is planned to reveal the ship domain model for an area where no traffic separation scheme exists. In the study, dodecagon ship domain for different type and size of vessels was created. One-year (11 month) of vessel encounters were analyzed and ship domain boundaries are prepared by considering different safety criteria. The passages of the vessel from forward, aft, port, and starboard were also statistically analyzed and the changes in ship domain dimensions according to the ship type and size are revealed. This model shows the vessels behavior regardless of traffic separation rules. • The construction of a novel, two-dimensional model of the probabilistic ship domain determination based on KDE. • To propose statistical regression general model of ships domain. • To determine with the above model the size and basic relationships of domains on a dedicated region. • Providing a computational basis for future risk modeling and detecting of anomalies in the study area. [ABSTRACT FROM AUTHOR]

This paper presents an overview of ship traffic volume and accidents in the Baltic Sea with a special focus on the Gulf of Finland. The most common accidents are groundings and collisions, usually reported to be caused by human error. The annual number of Baltic Sea accidents reported to HELCOM varied from 34-54 for collisions and 30-60 for groundings. The number of yearly port calls varied from 468-505 thousand with a peak in 2008. Exact port call data could not be found for all ports and hence had to be estimated. The number of line crossingings in HELCOM AIS data was found to be a good, rough surrogate measure for the total number of port calls and could be used if more precise port call data was not available. By analyzing two separate accident databases, an estimate for accident underreporting was calculated. Different statistical methods yielded an underreporting rate in the range of 40-50%. Lastly, the true number of accidents was estimated, based on the estimated underreporting percentage for the Baltic Sea. Based on these results, the true number of true accidents should be first estimated if accident statistics are used in building or validating maritime risk models. When using such models or accidents statistics in decision-making, the underlying uncertainty in the accident statistics should be taken into account as the underreporting frequency estimates are only approximations of the real number of accidents. [ABSTRACT FROM AUTHOR]

This study characterizes navigation conflicts in a region with a large traffic volume along the United States (US) Atlantic Coast, using an empirical approach that analyzes Automated Identification System (AIS) data for a full year (2010). The region includes areas proposed for wind energy development, and this characterization of vessel conflicts could be useful as a baseline to evaluating the effect of offshore wind areas on navigation conflicts and vessel collisions. There have been no collisions reported within the study area. This study analyzes the one year of AIS data to obtain vessel tracks and makes simultaneous pairwise comparisons to determine the number and rate of vessel encounters and near-misses (navigation conflicts). For vessel pairs in an encounter (3 nm distance; crossing, head-on, overtaking), a 'blind vessel' assumption was used to calculate the number of potential near misses and potential collisions. Graphical analysis of the frequency of vessels involved in potential near misses produced vessel response curves that provided the time of peak frequencies prior to the time of closest approach for each encounter type. These peak times were up to 600 s prior to the time of closest approach. The analyses of potential near misses and collision used the data during the period between the time of peak frequency and the time of closest approach to filter the data used in the calculation of the probability of potential collisions. The period included collsion avoidance maneuvering. Statistical analyses are made to estimate the point values and uncertainty of near miss rates and the probability of potential collisions for each type of encounter from which bounding estimates of the collision rates are made. These bounding collision rates are found to be comparable with estimates from previous studies. Causation probabilities were also estimated and compared with previous studies. The response curves may also have utility in the simulation of navigation conflicts. The use of surrogate data to evaluate the effect of wind energy areas is considered, though their usefulness depends on comparability of traffic density and the level and type of traffic control systems implemented. • Evaluates the occurrence of encounters and near-misses along the US Atlantic Coast that include proposed wind energy areas. • Examines the overall vessel responses to potential near-misses. • Estimates the bounding rate collisions and causation probabilities in the analysis domain. • Discusses the possible impacts of the presence of wind energy areas on collision rates. [ABSTRACT FROM AUTHOR]

This study aims to evaluate ship collision frequency in port fairways. One case study is created using one month's real-time ship movement data from five major Singapore port fairways. Results show that tankers account for the biggest proportion in the Temasek fairway, whereas the percentage of Roll-on-Roll-Off (RORO) and passenger ships is quite small in the Temasek fairway, Sinki fairway, Jong fairway and Southern fairway. Tankers and container ships are the two major ship types involved in dangerous encounters. The largest number of dangerous head-on and overtaking encounters is located in the Jong fairway. The majority of dangerous crossing encounters have occurred in the West Keppel fairway and Jong fairway. Ship collision frequency at night is found to be significantly higher than during the day in these fairways. [ABSTRACT FROM AUTHOR]

Appropriate management of the effects of human activities on animal populations requires quantification of the rate at which animals encounter stressors. Such activities are heterogeneously distributed in space, as are the individual animals in a population. This will result in a heterogeneous exposure rate, which is also likely to vary over time. A spatially explicit analysis of individual exposure is therefore required. We applied Bayesian spatially explicit capture-recapture models to photo-identification data to estimate the home range of well-marked individuals in a protected coastal population of bottlenose dolphins. Model results were combined with the estimated distribution of boat traffic to quantify how exposure to this disturbance varied in time and space. Variability in exposure between individuals was also investigated using a mixed-effects model. The cumulative individual exposure to boat traffic varied between summers, depending both on the overall area usage and the degree of individual movement around the activity centres. Despite this variability, regions of higher risk could be identified. There were marked inter-individual differences in the predicted amount of time dolphins spent in the presence of boats, and individuals tended to be consistently over- or underexposed across summers. Our study offers a framework to describe the temporal, spatial and individual variation in exposure to anthropogenic stressors when individuals can be repeatedly identified over time. It provides opportunities to map exposure risk and understand how this evolves in time at both individual and population levels. The outcome of such modelling can be used as a robust evidence base to support management decisions. [ABSTRACT FROM AUTHOR]

Risk evolution characteristics of an LNG-fueled vessel had been simulated by using the systems-theoretic accident modeling and processes (STAMP) model and a genetic algorithm (GA). First, the STAMP model was established to deconstruct the structure of the risk evolution which was affected by external environmental components. Second, given that the risk performance and maritime traffic develop in the time dimension, and the situation changes in the spatial dimension, a GA was used to provide a timeline for the STAMP model. Third, the coupled STAMP-GA model was applied to the LNG-fueled vessel system. Based on the golden section ratios for levels of risk performance, a Cloud model was introduced to provide input data for the GA model. Last, combined with the data for the LNG-fueled vessel and using a route scenario for a specific anchorage to a designated berth, the risk evolution performance was simulated to explore the risk characteristics of the LNG supply process. The results show that the risk evolution mode of the LNG-fueled vessel follows a bathtub-shaped distribution curve. The novel STAMP-GA model proves to be efficient in analyzing the mutation of risk components and the coupled process in the risk evolution. • 1.The law of navigational risk evolution was obtained using the STAMP-GA coupling model. • 2.The risk evolution mode of LNG-fueled vessels is a disturbed U-shaped curve. • The introduction of genetic algorithm obtains refinement of quantitative characterization of risk evolution pathway. [ABSTRACT FROM AUTHOR]

The Turkish Straits comprising the Strait of Canakkale, the Strait of Istanbul and the Sea of Marmara are unique in many respects. All dangers and obstacles characteristic of narrow waterways are present and acute in this critical sea lane. This research reveals the simulation of Canakkale (Dardanelle) Strait under different traffic conditions and identifies risky areas. The results of this simulation show that an increase of 25% in the existing traffic grows 43 times in the number of waiting ships (from 1.663 to 73.73), whereas waiting time increases 29 times (from 24.267 to 737.07). As a result of simulations and risk analysis, it is found that Nara turning point is the bottleneck point of the strait due to its topographic structure and the current system. [ABSTRACT FROM AUTHOR]

Container traffic has a dominant role in the transport of general cargo, because it integrates different ways of transport into a unique transport chain. The reason is that it is easier to handle cargo and the turn - around time is reduced, thus decreasing the costs of transhipment and reducing freight rates, attracting more users. Due to all these factors, container transport is considered to be the most perspective way of transporting of cargo. The Mediterranean Sea is of extreme importance for container transport, because it is one of three most important routes on relation East-West i.e. that one connecting Europe with Near East, Middle East, Far East. Taking into consideration the fact that in liner marine service there's a trend of rationalization of the number of ports of call because of the reduction of costs, the Mediterranean ports in the vicinity of main fairway between Suez Channel and Gibraltar took the function of main transhipment container ports. The distribution of containers from those ports towards distant ports of the Mediterranean basin is done by regular feeder lines Container traffic in the Adriatic appeared in the end of 1970. and it is of the greatest intensity in the North Adriatic ports, because they have the best traffic connections with gravitational hinterland, i.e. the States of Central Europe. However, although having exceptionally convenient geographical position in comparison to traffic routes between Europe and East, North Adriatic ports don't take advantage of that position. It is proved by the fact that main competitors are the ports of North and Baltic Sea across which the majority of foreign trade of the eastern states of Central Europe is carried out, although being in the close vicinity to the Adriatic. [ABSTRACT FROM AUTHOR]

Black carbon (BC) is one of the main components of ambient particulate matter. Previous studies have suggested that BC is more toxic than PM 2.5 (mass concentration of all sub-2.5 μm particles). One possible reason for the greater toxicity is that BC is typically in a size range which penetrates easily into lung alveoli and BC particles have a large surface area due to their fractal structure. Due to these properties, toxic gaseous compounds can condensate on the surface of BC particles and then be transported effectively into human lungs, causing a large lung-depositing surface area (LDSA) of particles. In this study, we investigated the relationship between BC and LDSA concentrations in street canyon, highway, and harbour environments in the Helsinki Metropolitan area. In all the studied environments, BC and LDSA concentrations were strongly correlated. In the harbour, cases where marine traffic was considered as the main emission source, the average LDSA per BC mass was 2.4–2.7 times higher than in the road traffic environments. This result was linked to a larger lung depositing size of BC, suggesting that condensation and coagulation of other co-emitted compounds can have a major role in the lung deposition of BC. Thus, BC emissions from marine traffic can cause higher exposure of other co-emitted toxic compounds in the human lungs than the road traffic. The fraction of LDSA linked to BC emissions in the street canyon, the highway, and the harbour were 33%, 30%, and 47%, respectively, whereas the fractions of BC mass in PM 1 concentration were 14%, 14%, and 7%, respectively. The results show that BC emissions contribute much more to LDSA than to mass concentration, which indicates that the possible strong negative health effects linked to ambient BC mass concentration could be related to the high LDSA concentration. • Characteristics of LDSA investigated in a harbour and near traffic in Helsinki area. • BC emitted from marine traffic is linked to higher LDSA per mass than road traffic. • BC emissions contribute more to LDSA (30–47% of total LDSA) than to PM 1 (7–14%). • In the harbour, higher absorption Ångström exponent was connected to higher LDSA. • Health hazard of BC might be related to high LDSA and other co-emitted species. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates port traffic risk issues by discussing historic accidents in Hong Kong port. A total of 2012 marine accidents with 94 deaths were reported in Hong Kong waters in year 2001–2005, while 660,427 oceanic ships visited the port. A negative binomial regression model is used to analyze the record of dataset. It is found that port traffic risks are of certain pattern and collision accidents are the most popular incidents when port traffic is heavy. Passenger-type vessels have higher potential for injuries during accidents. The findings have identified statistically significant factors for improvements in managing port traffic risks. [Copyright &y& Elsevier]

The Turkish Straits, comprising the Strait of C¸anakkale, the Strait of Istanbul and the Sea of Marmara, are unique in many respects. The very narrow and winding shape of the strait, gives it river like characteristics, and it is an established fact that for mariners the Turkish Straits are one of the most hazardous, crowded, and potentially dangerous, waterways in the world. All the dangers and obstacles characteristic of narrow waterways are present and acute in this critical sea lane.In this research, the simulation of the Istanbul Strait was done under unique traffic conditions and results of this simulation, and the effects of probable increase in marine traffic due to new oil pipelines, are discussed. [Copyright &y& Elsevier]