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The collection and distribution network of ports is the main cause of carbon emissions. The carbon peak is a basic policy in China, and the subsidy policy is one of the common measures used by the government to incentivize carbon reduction. We analyzed the transportation methods and the flow direction of a port and proposed a carbon emission calculation method based on emission factors. Based on the transportation time and the cost, a generalized transportation utility function was constructed, and the logit model was used to analyze the impacts of subsidy policies on transportation, thus calculating the effects of the subsidies on carbon reduction. We used Guangzhou Port as a case study, and calculated the carbon reduction effects in six different subsidy policy scenarios and concluded that the absolute carbon reduction value was proportional to the subsidy intensity. In addition, we constructed a subsidy carbon reduction efficiency index and found that the Guangzhou Port collection and distribution network had higher subsidy carbon reduction efficiency in low-subsidy scenarios. Finally, a sensitivity analysis was conducted on the subsidy parameters, and scenario 8 was found to have the highest subsidy carbon reduction efficiency. This achievement can provide decision support for the carbon emission strategy of the port collection and distribution network.

Most species of whales are vulnerable to vessel collisions, and the probability of lethality increases logistically with vessel speed. An Automatic Identification System (AIS) can provide valuable vessel activity data, but terrestrial-based AIS has a limited spatial range. As the need for open ocean monitoring increases, AIS broadcasts relayed over earth-orbiting satellites, satellite AIS (SAIS), provides a method for expanding the range of AIS broadcast reception. We used SAIS data from 2013 and 2014 to calculate vessel density and speed over ground around the coast of Washington state in the northwestern United States. Nearby shipping lanes connecting the Ports of Seattle, Tacoma, Portland, and in Canada, Vancouver, have the greatest density of vessel traffic arriving and departing. Knowledge of shipping activity is important in this area due to the nearby presence of NOAA designated Cetacean Density and Distribution Working Group's Biologically Important Areas (BIA) for large whale species vulnerable to vessel collisions. We quantified density and speed for each vessel type that transits through BIA's. We found that cargo and tanker vessels traveled the farthest distance at the greatest speeds. As ship-strike risk assessments have traditionally relied on terrestrial AIS, we explored issues in the application of SAIS data. Temporal gaps in SAIS data led to a resulting systematic underestimation of vessel speed in calculated speed over ground. However, SAIS can be helpful in documenting minimum vessel speeds across large geographic areas and across national boundaries, especially beyond the reach of terrestrial AIS receivers. SAIS data can also be useful in examining vessel density at broad scales and could be used to assess basin-wide open ocean routes. Future use of additional satellite platforms with AIS receivers and technological advances will help rectify this issue and improve data coverage and quality.

The huge fuel consumption of shipping activities has a great impact on the ecological environment, port city environment, air quality, and residents' health. This paper uses Automatic Identification System (AIS) data records and ship-related data in 2021 coastal waters of the United States to calculate pollutant emissions from ships in 30 ports of the United States in 2021. After calculating the pollutant emissions from ships at each port, the multiscale geographically weighted regression (MGWR) model is used to analyze the factors affecting the ship pollutant emissions. Geographically weighted regression (GWR) model is used to investigate the spatial heterogeneity of various factors affecting the characteristics of ship pollutant emissions at different scales. This paper mainly compares the effect of models of GWR and MGWR. MGWR may truly reveal the scale difference between different variables. While controlling the social and economic attributes, the coastline length, container throughput, and population are used to describe the spatial effects of ship pollutant emissions in the United States. The results denote that the distribution trend of ship pollutant emissions has a gap based on various ship types and ports. NOx accounts for the highest proportion of pollutant emissions from port ships, followed by SO₂ and CO. The impact coefficients of coastline length and population on pollutant emissions in port areas are mostly positive, indicating that the growth of coastline length and population will increase pollutant emissions in port areas, while the effect of container throughput is opposite. Relevant departments should put forward effective measures to curb NOx emission. Port managers should reasonably plan the number of ship transactions according to the coastline length of the port.

Measuring the environmental impact of their supply chain has become an increasingly important issue for many companies. To meet this demand, the CMA CGM Group will be making available to customers a new service starting in April 2011: the eco-calculator.

The main target of DSP in respect of Contship Italia Group, is to address the IT strategies of the various companies to guarantee an harmonious development respecting the peculiarity and the autonomy of the single realities. In the last years DSP, using the acquired know-how in the IT problems of shipping, port management and intermodal transportation has enlarged is portfolio of activities offering to the market professional services in terminal operations processes and systems deployment and optimisiation. In 2007 DSP became partner of NAVIS (part of Cargotec Corporation) and certified its staff as SPARCS 3.7 and SPARCS N4 senior consultants, carrying out various international projects. DSP has recently developed for Contship Italia Group an innovative and flexible system for automatic invoicing (Fatteuro) for container and general cargo terminals interfaced with other systems in order to manage all the necessary information to calculate and register the invoices. It is currently is use at CICT (Cagliari), EGT(Tangier), LSCT(La Spezia) and at the General Cargo Terminal SPETER of La Spezia. DSP is also tightly linked with the new University of Applied Science of Southern Switzerland. In his team a professor of this university is leading analysis and design activities and most part of his personnel has a degree in Computer Science and where recruited there. This also gives the chance to DSP to participate to research projects on the transport and IT area and to remain always skilled with the newest technology

Second as mentioned above these are costly loans. Therefore you should calculate your ability to repay the loan and accordingly clear the debt as per the scheduled time period given by the lender.

A new analysis done to support the investigation into the 2015 sinking of the El Faro cargo ship has calculated the likelihood of a massive rogue wave during Hurricane Joaquin in October of that year - and demonstrated a new technique for evaluating the probability of rogue waves over space and time.

Statisticians have calculated the probability of ships of different Polar Ship Categories becoming beset in ice along the Northern Sea Route. Their data will help assess the risks of maritime traffic in the Arctic.

Vessel strikes have been documented around the world and frequently figure as a top human cause of large whale mortality. The shipping lanes in the Santa Barbara Channel, California and nearby waters have some of the highest predicted whale mortality from vessel strikes in the United States waters of the eastern Pacific. Beginning in 2007, National Oceanographic and Atmospheric Administration requested voluntary vessel speed reductions (VSRs) for vessels greater than 300 GT traveling in the Santa Barbara Channel shipping routes to decrease whale mortality from ship strikes. We employed a ship strike model using whale density data and automatic identification system (AIS) vessel data to estimate mortality under several management scenarios. To assess the effect of the VSR on strike mortality, we bootstrapped speeds from vessels greater than 19 m long that transited when no VSR was in place. Finally, we calculated the predicted mortality for hypothetical cooperation scenarios by artificially adding speed caps post-hoc to real vessel transits. For 2012-2018, we estimated that in our study area on average during summer/fall (June-November) 8.9 blue, 4.6 humpback, and 9.7 fin whales were killed from ship strikes each year (13-26% greater than previously estimated). We evaluated winter/spring (January-April) humpback mortality for the first time, resulting in an estimate of 5.7 deaths on average per year. Poor cooperation with the VSR led to low (5% maximum) to no reductions in the estimated number of strike mortalities. Evaluating potential scenarios showed that if 95% cooperation occurred in the lanes, whale deaths there would decrease by 22-26%. Adding VSRs with similar cooperation levels at the northern end of the Santa Barbara Channel and south of Channel Islands National Marine Sanctuary could decrease estimated strike mortalities in those areas by 30%. If VSRs were added and cooperation reached 95% there and in the lanes, we estimate a 21-29% decrease i

Despite efforts to aid recovery, Eastern North Pacific blue whales faces numerous anthropogenic threats. These include behavioral disturbances and noise interference with communication, but also direct physical harm - notably injury and mortality from ship strikes. Factors leading to ship strikes are poorly understood, with virtually nothing known about the cues available to blue whales from nearby vessels, behavioral responses during close encounters, or how these events may contribute to subsequent responses. At what distance and received levels (RLs) of noise whales respond to potential collisions is difficult to observe. A unique case study of a close passage between a commercial vessel and a blue whale off Southern California is presented here. This whale was being closely monitored as part of another experiment after two suction-cup archival tags providing acoustic, depth, kinematic, and location data were attached to the whale. The calibrated, high-resolution data provided an opportunity to examine the sensory information available to the whale and its response during the close encounter. Complementary data streams from the whale and ship enabled a precise calculation of the distance and acoustic cues recorded on the tag when the whale initiated a behavioral response and shortly after at the closest point of approach (CPA). Immediately before the CPA, the whale aborted its ascent and remained at a depth sufficient to avoid being struck for ∼3 min until the ship passed. In this encounter, the whale may have responded to a combination of cues associated with the close proximity of the vessel to avoid a collision. Long-term photo-identification records indicate that this whale has a long sighting history in the region, with evidence of previous ship encounters. Therefore, experiential factors may have facilitated the avoidance of a collision. In some instances these factors may not be available, which may make some blue whales particularly susceptible to dea

The optimization of empty container repositioning nets has become an essential problem in low-carbon port cooperation. This paper proposed three optimization models of multi-port low-carbon empty container repositioning considering threshold under input and output of empty containers as random variables. Non repositioning strategy means the highest threshold, and complete-repositioning strategy means the lowest threshold; threshold-repositioning strategy is in the middle. The probability of empty-container inventory in each port and the storage cost, repositioning cost, lease cost, and carbon emission cost of empty containers are calculated. This paper mainly compares each cost of three models. The results have shown that: (1) Compared with the non repositioning strategy, the threshold-repositioning strategy and complete-repositioning strategy can reduce the ports storage costs and lease costs of empty containers and also reduce carbon emissions. The lower the repositioning threshold of empty containers between ports is, the more obvious the advantages of the threshold-repositioning strategy become. (2) When the cost of storage per empty container increases, under three strategies, the total cost, storage cost, lease cost, and carbon emission cost of the port will all increase. The ports proportion of dependence on its own empty-container storage will decrease, and the proportion of dependence on other ports and leasing companies will both increase.

The combined emissions of metals and other environmentally hazardous substances from ships is putting the marine environment at risk according to a new study from Chalmers University of Technology, Sweden. When the researchers calculated the contaminant load from these emissions into the marine environment in four ports, it was found that water discharged from ships' scrubbers, whose purpose is to clean their exhaust gases, accounts for more than 90 per cent of the contaminants.

With the construction of China's ecological civilization and the proposal of carbon peaking and carbon neutrality goals, shore power has been vigorously developed as an important technology for the future green development of ports. However, China's electricity is still mostly coal-fired, which produces many carbon emissions. Coupled with regional differences, shore power is by no means certain to lower carbon emissions compared with fuel throughout China. Considering the power energy structure in different regions, this paper establishes a carbon emission correlation model between fuel and shore power during ship berthing, calculates the feasibility and actual emission reduction effect of shore power in coastal ports, and studies the restriction condition of starting time for the use of shore power for ships attached to ports according to the national policy of mandatory use of shore power. The results show that only a small part of coastal provinces and cities are suitable for using shore power, and it is limited by the berthing time of the ship. However, this condition is not related to the size of ships but related to the proportion of power generation. Therefore, the government should develop shore power according to local conditions, and vigorously increase the proportion of clean energy, so that the shore power truly achieve zero carbon emissions.

It is significant for port ship scheduling and traffic management to be able to obtain more precise location and shape information from ship instance segmentation in SAR pictures. Instance segmentation is more challenging than object identification and semantic segmentation in high-resolution RS images. Predicting class labels and pixel-wise instance masks is the goal of this technique, which is used to locate instances in images. Despite this, there are now just a few methods available for instance segmentation in high-resolution RS data, where a remote-sensing image's complex background makes the task more difficult. This research proposes a unique method for YOLOv7 to improve HR-RS image segmentation one-stage detection. First, we redesigned the structure of the one-stage fast detection network to adapt to the task of ship target segmentation and effectively improve the efficiency of instance segmentation. Secondly, we improve the backbone network structure by adding two feature optimization modules, so that the network can learn more features and have stronger robustness. In addition, we further modify the network feature fusion structure, improve the module acceptance domain to increase the prediction ability of multi-scale targets, and effectively reduce the amount of model calculation. Finally, we carried out extensive validation experiments on the sample segmentation datasets HRSID and SSDD. The experimental comparisons and analyses on the HRSID and SSDD datasets show that our model enhances the predicted instance mask accuracy, enhancing the instance segmentation efficiency of HR-RS images, and encouraging further enhancements in the projected instance mask accuracy. The suggested model is a more precise and efficient segmentation in HR-RS imaging as compared to existing approaches.

Surface atmospheric temperatures over the Arctic Ocean are rising faster than the global average, and sea-ice coverage has declined, making some areas newly accessible to ocean-going ships. Even so, Arctic waters remain hazardous to ships, in part, because of the highly variable nature of sea-ice formation and drift in some areas. In this study, we investigated interannual variability in polar class (PC) ship accessibility in the northern BERING Sea and seas north of the BERING Strait (East Siberian, Chukchi, Beaufort) from February 2012 to February 2022. We used sea-ice charts from the U.S. National Ice Center and calculations of the Risk Index Outcome (RIO) for PC3, PC5, and PC7 ships to characterize spatiotemporal trends in PC ship accessibility during the months of February, June, September, and November over the last 10 to 11 years. We also characterized shipping activity on select days in 2021. Overall, PC ship accessibility during the months of February and June increased over the last decade, especially for PC7 ships. However, areas that became more accessible over time did not support heavy ship traffic, possibly because they were not located on preferred transit routes or because they were surrounded by unnavigable ice, which made them inaccessible in practice. Ship accessibility was highly variable in the northernmost, offshore regions of the study site. During June, PC7 ship accessibility was interannually variable in waters south of the BERING Strait, and ships were active in those regions (most were fishing vessels), indicating potentially hazardous conditions during this time of year. Accessibility was considerably less variable over space and time (months, years) for PC5 (ice capable) ships and for PC3 ships (heavy icebreakers). Information from this study can be used by PC ship operators planning safe and successful shipping routes and by coastal states preparing emergency services to protect the maritime community. As governments and the private se

The escalating greenhouse gas (GHG) emissions from maritime trade present a serious environmental and biological threat. With increasing emission reduction initiatives, such as the European Union's incorporation of the maritime sector into the emissions trading system, both challenges and opportunities emerge for maritime transport and associated industries. To address these concerns, this study presents a model specifically designed for estimating and projecting the spatiotemporal GHG emission inventory of ships, particularly when dealing with incomplete automatic identification system datasets. In the computational aspect of the model, various data processing techniques are employed to rectify inaccuracies arising from incomplete or erroneous AIS data, including big data cleaning, ship trajectory aggregation, multi-source spatiotemporal data fusion and missing data complementation. Utilizing a bottom-up ship dynamic approach, the model generates a high-resolution GHG emission inventory. This inventory contains key attributes such as the types of ships emitting GHGs, the locations of these emissions, the time periods during which emissions occur, and emissions. For predictive analytics, the model utilizes temporal fusion transformers equipped with the attention mechanism to accurately forecast the critical emission parameters, including emission locations, time frames, and quantities. Focusing on the sea area around Tianjin port-a region characterized by high shipping activity-this study achieves fine-grained emission source tracking via detailed emission inventory calculations. Moreover, the prediction model achieves a promising loss function of approximately 0.15 under the optimal parameter configuration, obtaining a better result than recurrent neural network (RNN) and long short-term memory network (LSTM) in the comparative experiments. The proposed method allows for a comprehensive understanding of emission patterns across diverse vessel types under vari

The propagation of electromagnetic waves on land and sea is significantly different. Although the Los scenario is significant in marine wireless communication, the marine wireless channel exists an obvious two-ray phenomenon due to the strong reflection path reflected through the sea surface. By modeling the measured data of marine wireless channels, this paper calculates the radio propagation characteristics of the Pearl River estuary. In addition, the wave fluctuations and high humidity environment will also impact the properties of the marine wireless channel. Therefore, sea surface morphology models under multiple wind speeds are built. To estimate the path loss in the same area under different conditions, the Monte Carlo method is employed to quantify the results. The simulation results show that the electric wave propagation gradually degenerated from the round earth loss (REL) model to the free space model with increasing wind speed. Moreover, the distribution of the shadow fading varies with distance. The findings provide references for the network planning of marine communication