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Understanding the determination mechanism and dynamics of shipping freight rates has significant implications for practitioners, economists, and regulators of maritime transport. This paper systematically reviews the relevant papers on shipping freight rate published between 2000 and 2019. Specifically, it provides empirical insights including the major influencing factors of shipping freight rates and differences among the shipping sectors, and discusses the dominant methods and their applicability, strengths and weaknesses, and opportunities for new methods. Furthermore, the omissions and limitations in methods are explored to identify the research gaps and set a future research agenda. It is found that there is a strong focus on temporal dynamics with a wide range of modelling methods applied, while discussion on cross-sectional dynamics on how shipping freight rates are determined by vessel characteristics, contract terms, market competition, etc., is limited. Besides, the collaboration network analysis shows that more knowledge sharing and cross-discipline collaboration efforts can create potential for more inspired insights with advanced methods in this field. [ABSTRACT FROM AUTHOR]

Traditional radar detection methods heavily rely on the signal-to-clutter ratio (SCR); a variety of feature-based detection methods have been proposed, providing a new way for radar detection and the recognition of weak targets. Existing feature-based detection methods determine the presence or absence of a target based on whether the feature value is within the judgment region, generally focusing only on the distribution of features and making insufficient use of inter-feature chronological information. This paper uses the autoregressive (AR) model to model and predict the time sequence of radar echoes in the feature domain and takes the chronological information of historical frame features as the prior information to form new features for detection on this basis. A classification method for floating small targets based on the Doppler spectrum centroid sequence is proposed. By using the AR model to fit the Doppler spectrum centroid feature sequence of the target, the model coefficients are regarded as the secondary features for target identification. The measured data show that the correct classification and identification rate of this method for ship targets and floating small targets can reach over 92% by using 50 centroid features. [ABSTRACT FROM AUTHOR]

This paper presents a mechanism design-based approach to tackle the crowdshipping problem in which a delivery service provider (DSP) solicits ordinary individuals, termed crowdsourcees, who use their limited available time to perform urban parcel delivery. The DSP collects private information from crowdsourcees while assigning shipments to minimize the cost of delivery. Given that crowdsourcees may strategically misreport private information, the assignment is devised with a payment rule to incentivize truthful reporting.. Doing so requires additional payment to crowdsourcees, whose asymptotic properties are investigated. We extend the static mechanism to a dynamic case by performing assignment periodically and examine the bounds for periodicity. Numerical results show that the proposed mechanisms will likely reduce shipping cost compared to three alternative scenarios: 1) no such mechanism is in place; 2) the DSP pays crowdsourcees at a fixed rate; and 3) truck-only delivery. Several additional insights from the mechanism implementation are further obtained. [ABSTRACT FROM AUTHOR]

In order to study the asymmetric multifractality in maritime shipping freight rates, we have resorted to the use of the novel approach of asymmetric Multifractality Detrended Fluctuation Analysis. This approach examines the maritime shipping freight response towards the downward and upward movements. The outcomes in this regard show that the major maritime shipping freight rates have multifractals, which tend to increase as the fractal scale also increases. Also, a higher level of multifractality is observed in the downward movements for the Baltic Dry Index, and the Baltic Clean Tanker Index, suggesting that both the indexes have been less efficient, and also unpredictable during the time period pertaining to the pandemic. Moreover, the multifractality is observed to be greater in the upside for the Baltic Dirty Tanker Index during the pandemic, and also in the full-time period. The results also propagate that the maritime shipping freight rates are inefficient, a situation that has been evidently visible during the time period pertaining to the COVID-19 pandemic. The maritime shipping freight rates require special attention to monitor such sudden changes in the price dynamics, and following strict regulations is extremely critical in this regard. [ABSTRACT FROM AUTHOR]

This article examines the impact of transportation on the growth and development of three towns in the Okanagan Valley of British Columbia: Vernon, Kelowna, and Penticton. The transportation systems, including railways and steamboats, played a crucial role in connecting the region with markets and facilitating the commercial production of fruit, particularly apples. While transportation brought economic benefits and growth to the towns, it also had negative consequences for the Indigenous Syilx Okanagan people, as their lands were affected and their employment opportunities limited. The article highlights the changing transportation systems and the subsequent shift in the relative status of the towns after World War II, with Kelowna emerging as the main urban center in the region. [Extracted from the article]

Synthetic aperture radar (SAR) ship detection is of significant importance in military and commercial applications. However, a high similarity in intensity and spatial distribution of scattering characteristics between the ship target and harbor facilities, along with a fuzzy sea-land boundary due to the strong speckle noise, result in a low detection accuracy and high false alarm rate for SAR ship detection with complex inshore scenes. In this paper, a new inshore ship detection method based on multi-modality saliency is proposed to overcome these challenges. Four saliency maps are established from different perspectives: an ocean-buffer saliency map (OBSM) outlining more accurate coastline under speckle noises; a local stability saliency map (LSSM) addressing pixel spatial distribution; a super-pixel saliency map (SPSM) extracting critical region-based features for inshore ship detection; and an intensity saliency map (ISM) to highlight target pixels with intensity distribution. By combining these saliency maps, ship targets in complex inshore scenes can be successfully detected. The method provides a novel interdisciplinary perspective (surface metrology) for SAR image segmentation, discovers the difference in spatial characteristics of SAR image elements, and proposes a novel robust CFAR procedure for background clutter fitting. Experiments on a public SAR ship detection dataset (SSDD) shows that our method achieves excellent detection performance, with a low false alarm rate, in offshore scenes, inshore scenes, inshore scenes with confusing metallic port facilities, and large-scale scenes. The results outperform several widely used methods, such as CFAR-based methods and super-pixel methods. [ABSTRACT FROM AUTHOR]

Antarctic Bottom Water is primarily formed via overflows of dense shelf water (DSW) around the Antarctic continental margins. The dynamics of these overflows therefore influence the global abyssal stratification and circulation. Previous studies indicate that dense overflows can be unstable, energizing topographic Rossby waves (TRW) over the continental slope. However, it remains unclear how the wavelength and frequency of the TRWs are related to the properties of the overflowing DSW and other environmental conditions, and how the TRW properties influence the downslope transport of DSW. This study uses idealized high-resolution numerical simulations to investigate the dynamics of overflow-forced TRWs and the associated downslope transport of DSW. It is shown that the propagation of TRWs is constrained by the geostrophic along-slope flow speed of the DSW and by the dynamics of linear plane waves, allowing the wavelength and frequency of the waves to be predicted a priori. The rate of downslope DSW transport depends nonmonotonically on the slope steepness: steep slopes approximately suppress TRW formation, resulting in steady, frictionally dominated DSW descent. For slopes of intermediate steepness, the overflow becomes unstable and generates TRWs, accompanied by interfacial form stresses that drive DSW downslope relatively rapidly. For gentle slopes, the TRWs lead to the formation of coherent eddies that inhibit downslope DSW transport. These findings may explain the variable properties of TRWs observed in oceanic overflows, and they imply that the rate at which DSW descends to the abyssal ocean depends sensitively on the manifestation of TRWs and/or nonlinear eddies over the continental slope. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) can detect objects in various climate and weather conditions. Therefore, SAR images are widely used for maritime object detection in applications such as maritime transportation safety and fishery law enforcement. However, nearshore ship targets in SAR images are often affected by background clutter, resulting in a low detection rate, high false alarm rate, and high missed detection rate, especially for small-scale ship targets. To address this problem, in this paper, we propose a novel deep learning network with deformable convolution and attention mechanisms to improve the Feature Pyramid Network (FPN) model for nearshore ship target detection in SAR images with complex backgrounds. The proposed model uses a deformable convolutional neural network in the feature extraction network to adapt the convolution position to the target sampling point, enhancing the feature extraction ability of the target, and improving the detection rate of the ship target against the complex background. Moreover, this model uses a channel attention mechanism to capture the feature dependencies between different channel graphs in the feature extraction network and reduce the false detection rate. The designed experiments on a public SAR image ship dataset show that our model achieves 87.9% detection accuracy for complex scenes and 95.1% detection accuracy for small-scale ship targets. A quantitative comparison of the proposed model with several classical and recently developed deep learning models on the same SAR images dataset demonstrated the superior performance of the proposed method over other models. [ABSTRACT FROM AUTHOR]

We investigate the convergence rate of the optimal entropic cost v ε to the optimal transport cost as the noise parameter ε ↓ 0 . We show that for a large class of cost functions c on R d × R d (for which optimal plans are not necessarily unique or induced by a transport map) and compactly supported and L ∞ marginals, one has v ε - v 0 = d 2 ε log (1 / ε) + O (ε) . Upper bounds are obtained by a block approximation strategy and an integral variant of Alexandrov's theorem. Under an infinitesimal twist condition on c, i.e. invertibility of ∇ xy 2 c (x , y) , we get the lower bound by establishing a quadratic detachment of the duality gap in d dimensions thanks to Minty's trick. [ABSTRACT FROM AUTHOR]

Inland ships are an important source of NOx , especially for cities along busy waterways. The amount and effect of such emissions depend on the traffic density and NOx emission rates of individual vessels. Ship emission rates are typically derived using in situ land measurements in relation to NOx emission factors (e.g. the number of pollutants emitted by ships per unit of burnt fuel). In this study, a different approach is taken, and NOx emission rates are obtained (in gs-1). Within the EU LIFE project, CLean INland SHipping (CLINSH), a new approach to calculating the NOx emission rates from data of in situ measurement stations has been developed and is presented in this study. Peaks (i.e. elevated concentrations) of NOx were assigned to the corresponding source ships, using the AIS (automated identification system) signals they transmit. Each ship passage was simulated, using a Gaussian puff model, in order to derive the emission rate of the respective source ship. In total, over 32 900 ship passages have been monitored over the course of 4 years. The emission rates of NOx were investigated with respect to ship speed, ship size, and direction of travel. Comparisons of the onshore-derived emission rates and those on board for selected CLINSH ships show good agreement. The derived emission rates are of a similar magnitude to emission factors from previous studies. Most ships comply with existing limits due to grandfathering. The emission rates (in gs-1) can be directly used to investigate the effect of ship traffic on air quality, as the absolute emitted number of pollutants per unit of time is known. In contrast, for relative emission factors (in gkg-1 fuel), further knowledge about the fuel consumption of the individual ships is needed to calculate the number of pollutants emitted per unit of time. [ABSTRACT FROM AUTHOR]

Strict carbon emission regulations are set with respect to countries' territorial seas or shipping activities in exclusive economic zones to meet their climate change commitment under the Paris Agreement. However, no shipping policies on carbon mitigation are proposed for the world's high seas regions, which results in carbon intensive shipping activities. In this paper, we propose a Geographic-based Emission Estimation Model (GEEM) to estimate shipping GHG emission patterns on high seas regions. The results indicate that annual emissions of carbon dioxide equivalent (CO2-e) in shipping on the high seas reached 211.60 million metric tonnes in 2019, accounting for about one-third of all shipping emissions globally and exceeding annual GHG emissions of countries such as Spain. The average emission from shipping activities on the high seas is growing at approximately 7.26% per year, which far surpasses the growth rate of global shipping emission at 2.23%. We propose implementation of policies on each high seas region with respect to the main emission driver identified from our results. Our policy evaluation results show that carbon mitigation policies could reduce emissons by 25.46 and 54.36 million tonnes CO2-e in the primary intervention stage and overall intervention stage, respectively, with 12.09% and 25.81% reduction rates in comparison to the 2019 annual GHG emissions in high seas shipping. [ABSTRACT FROM AUTHOR]

Due to background clutter in synthetic aperture radar (SAR) images, the detection of dense ship targets suffers from a low detection rate, high false alarm rate, and high missed detection rate. To address this issue, an FSM-DFF-YOLOv5+Confluence algorithm is proposed in this paper for the detection of near-shore ship targets in SAR images with complex backgrounds. First, based on the YOLOv5 target detection algorithm, two improvements are made in the feature extraction network: feature refinement and multi-feature fusion; in the feature extraction network, deformable convolutional neural networks are adopted to change the position of the target sampling points of the convolution to improve the feature extraction capability of the target and the detection rate of ship targets in SAR images with a complex background; in the multi-feature fusion network structure, cascading and parallel pyramids are used in the multi-feature fusion network to realize feature fusion at different levels; the visual perceptual field of feature extraction is expanded by using null convolution to enhance the adaptability of the network to detect near-shore multi-scale ship targets with complex backgrounds and reduce the false alarm rate of ship target detection in SAR images with complex environments. In this way, the DFF-YOLOv5 near-shore ship target detection algorithm is established. Meanwhile, to address the problem of missed detection in near-shore dense ship target detection, this paper adds rectangular convolution kernels to the convolution of the feature extraction network to better realize the feature extraction of dense ship targets in SAR images with complex backgrounds. Besides, the Confluence algorithm instead of non-maximum suppression is used in the prediction stage. Through experiments on the constructed complex background near-shore ship detection dataset, it is indicated that the average accuracy of the FSM-DFF-YOLOv5+Confluence detection algorithm reaches 88.96%, and the recall rate reaches 88.80%. [ABSTRACT FROM AUTHOR]

Regulations for the control of air-pollutant emissions from ships within pollutant emission control areas (ECAs) have been issued for several years, but the lack of practical technologies and fundamental theory in the implementation process remains a challenge. In this study, we designed a model to calculate the nitrogen-oxide-emission intensity of ships and the sulfur content of ship fuels using theoretical deduction from the law of the conservation of mass. The reliability and availability of the derived results were empirically evaluated using measurement data for NOx, SO2, and CO2 in the exhaust gas of a demonstration ship in practice. By examining the model and the measured or registered fuel-oil-consumption rates of ships, a compliance-determination workflow for NOx-emission intensity and fuel-sulfur-content monitoring and supervision in on-voyage ships were proposed. The results showed that the ship fuel's NOx-emission intensity and sulfur content can be evaluated by monitoring the exhaust-gas composition online and used to assist in maritime monitoring and the supervision of pollutant emissions from ships. It is recommended that uncertainties regarding sulfur content should be considered within 15% during monitoring and supervision. The established model and workflow can assist in maritime monitoring. Meanwhile, all related governments and industry-management departments are advised to actively lead the development of monitoring and supervision technology for ship-air-pollutant control in ECAs, as well as strengthening the quality management of ships' static data. [ABSTRACT FROM AUTHOR]

Port state control (PSC) is the last line of defense for substandard ships. During a PSC inspection, ship detention is the most severe result if the inspected ship is identified with critical deficiencies. Regarding the development of ship detention prediction models, this paper identifies two challenges: learning from imbalanced data and learning from unlabeled data. The first challenge, imbalanced data, arises from the fact that a minority of inspected ships were detained. The second challenge, unlabeled data, arises from the fact that in practice not all foreign visiting ships receive a formal PSC inspection, leading to a missing data problem. To address these two challenges, this paper adopts two machine learning paradigms: cost-sensitive learning and semi-supervised learning. Accordingly, we expand the traditional logistic regression (LR) model by introducing a cost parameter to consider the different misclassification costs of unbalanced classes and incorporating a graph regularization term to consider unlabeled data. Finally, we conduct extensive computational experiments to verify the superiority of the developed cost-sensitive semi-supervised learning framework in this paper. Computational results show that introducing a cost parameter into LR can improve the classification rate for substandard ships by almost 10%. In addition, the results show that considering unlabeled data in classification models can increase the classification rate for minority and majority classes by 1.33% and 5.93%, respectively. [ABSTRACT FROM AUTHOR]

The past decades have witnessed the rapid development of China's manufacturing industry, which has established China's status as a manufacturing and trading power. Along with the impressive transportation volume of global trade, Chinese and global shipping markets have been further developed. Both trade volumes and freight rates will be impacted by the import-export market as well as price fluctuation. The freight rates of the dry bulk shipping market are our main concern, whether they are influenced by Chinese manufacturing industry. Moreover, the relationships between the Chinese and global shipping freight rates of dry bulk in every sub-sector are discussed by employing Vector Autoregressive (VAR) model and the least absolute shrinkage and selection operation (LASSO) regression. Besides, the effects of China's economic policy uncertainty (EPU) on freight rates are explored. Our data includes the monthly data from July 2012 to August 2021, where the development of the Chinese shipping market and manufacturing industry is represented by the Tianjin Bulk Freight Index (TBI) and China's Manufacturing Purchasing Managers' Index (PMI). We find that Chinese PMI only influences freight rates of Panamax and Capesize sub-segments of the global shipping market. Surprisingly, Chinese EPU has no meaningful effect on the freight rates of the dry bulk shipping market due to the lack of shipping characteristics. Our investigation is helpful for shipowners and operators when engaging in dry bulk shipping services and investment decision-making. • This study explores the impacts of Chinese manufacturing industry and Economic Policy Uncertainty on shipping freight rates. • This study analyzes sub-sectors of dry bulk shipping market and Chinese shipping market simultaneously. • VAR and LASSO regression are used to investigate the relationship between PMI and shipping freight indices. • The positive relationship between PMI and shipping freight rates in Panamax and Capesize sub-segments is confirmed. [ABSTRACT FROM AUTHOR]

Modern anoxic marine sediments release phosphorus (P) to seawater, driving feedbacks at multiple timescales. On sub‐Myr timescales, anoxic P regeneration amplifies ocean deoxygenation; on multi‐Myr timescales, it stabilizes atmospheric O2. Some authors have extended this thinking to the Precambrian: by analogy, widespread ocean anoxia would imply extensive P regeneration from sediments. However, this neglects the role of sulfate in P regeneration. While abundant in seawater today, sulfate was scarce in the Precambrian. Here a simple model is used to isolate the role of sulfate in anoxic P cycling. The model reproduces known feedbacks driven by anoxic P regeneration in a high‐sulfate world, but shows muted P regeneration in low‐sulfate, anoxic sediments. The transition between "limited" and "enhanced" P regeneration is thus controlled by sulfate. As a result, sulfate is a double‐edged sword wielded by the anoxic P cycle: it can amplify oxygenation or deoxygenation depending on environmental context. Plain Language Summary: Phosphorus is a critical nutrient and its availability controls the rate of biological productivity in the ocean. Constraining phosphorus availability in seawater through time is thus of great interest to paleoceanographers. A key observation in recent years has been that ancient marine sediments from the Precambrian Era (prior to 541 million years ago) contain less phosphorus than younger sediments. Researchers disagree as to why this is, with proposed ideas falling into two main camps. One camp maintains that phosphorus burial was efficient in the Precambrian, meaning that phosphorus was quickly removed from seawater, creating a small ocean inventory and keeping sedimentary phosphorus levels low. Another camp suggests that Precambrian phosphorus burial was inefficient, causing sediments to have low phosphorus content, instead allowing phosphorus to accumulate to high levels in seawater. Here a simple model is used to reconcile these contrasting hypotheses. The model examines the effect of sulfate on phosphorus burial efficiency in anoxic sediments, finding that lower sulfate levels imply higher burial efficiency, and vice‐versa. The contrasting hypotheses for Precambrian phosphorus burial can thus both potentially be accurate, and this exercise highlights the importance of constraining marine sulfate levels to know more about the ancient phosphorus cycle. Key Points: Sulfur cycling drives phosphorus (P) release from modern anoxic sediments to overlying seawaterIn a high‐sulfate, high‐O2 world, P regeneration stabilizes atmospheric O2 on long timescales, but amplifies transient ocean anoxic eventsIn a low‐sulfate, low‐O2 world, P regeneration amplifies transient atmosphere oxygenation events [ABSTRACT FROM AUTHOR]

Railway freight rates are seen as a key driving factor of global trade activities, influenced by numerous factors. Given the limitations of fuzziness and randomness of variable quantification in the previous studies, this paper proposes a cognitive cloud model of factors influencing railway bulk goods freight rates. In the cognitive cloud model, randomness and fuzziness are described by three parameters. Furthermore, a cloud generator including forwarding and backward cloud generators is designed to solve the bidirectional conversion between qualitative indicators and quantitative values. In addition, we propose a floating cloud gathering algorithm to determine the weight of the index system to solve the uncertainty problem in the transformation process of qualitative indicators. Finally, the cognitive cloud model and the adapted algorithm are used to perform an in-depth analysis of the affecting factors of Z Railway Bureau freight transport pricing. [ABSTRACT FROM AUTHOR]

This study determines the impact of the coronavirus disease (COVID-19) that has been prevalent since the year 2019, on the shipping freights. This task has been undertaken by using the wavelet quantile on the quantile approach. The results of the study affirm that the pandemic has in fact affected the shipping freight costs, primarily due to the lower demand for energy and raw materials, and the unavailability of the vessels. In addition to this, the spread of COVID-19 has had a positive impact on the Baltic Dry Index in the high quantiles and is deemed to be more responsive in the long run. Also, the COVID-19 infection has had a negative effect on the Baltic Dry Tanker Index and the Baltic Clean Tanker Index in the medium to high quantiles, particularly in the short and the medium run. The positive impact of COVID-19 on the Baltic Clean Tanker Index has been recognized in the long term in the high quantiles. These findings support the theoretical model which states that the spread of COVID-19 and the shipping freights are closely related. The results suggest that the degree of the effect is more causal in the short. Therefore, the shipping industry must ideally pay special attention to the detection of abrupt changes in the freight rate dynamics, and the specific regulations regarding these intricacies are critical. [ABSTRACT FROM AUTHOR]

As the boil-off gas (BOG) rate is tested to evaluate the thermal insulation performance of cryogenic containers at a 90 % liquid level in standard. This study aims to predict the BOG rate of cryogenic containers at different liquid levels based on a single test. If the BOGs at a 90 % liquid level can be evaluated based on the BOG test at a low liquid level, the large amount of working medium can be saved to reduce the test cost and the equilibration time can be shortened to improve the test efficiency. In this study, the QHALW (heat absorbed by the liquid from its corresponding outer wall) and QHTVL (heat transferred from the corresponding wall of the vapor to the liquid) are analysed to establish the energy equation of the liquid in the BOG test, indicating latent heat of BOG in cryogenic containers includes the QHALW and QHALW. Therefore, the equation between the latent heat of BOG and the two parts of heat isbuilt to predict BOGs at different liquid levels with the tested BOG. The maximum error of the experimental results is not more than 7.0 %, which shows that the BOG is successfully predicted at different liquid levels with a single-tested BOG. [ABSTRACT FROM AUTHOR]

This paper deals with the inverse optimal leader-following consensus problem of a class of high-order nonlinear multi-agent systems in strict-feedback form under directed communication topology. By employing the backstepping methodology and introducing an integral type Lyapunov function, a nonlinear distributed control law is constructed using the relative information between neighboring agents. The proposed control law solves the inverse optimal leader-following consensus problem under directed communication graph that contains a spanning tree with the root node being the leader agent. A practical example of ship slew rate control system is given to verify the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

In this work, using a mathematical model and numerical simulation, we investigate the effect of time-dependent evaporation rates on stripe formation inside containers. This pattern formation is driven by the coffee-ring effect. The coffee particles inside a container move according to random walk and under the gravitational force. Because of the time-dependent evaporation rate, we can observe stripe formation inside a container after evaporation of the coffee particle-laden liquid. Various numerical experiments are performed to demonstrate the proposed model can simulate the stripe formation in a container. [ABSTRACT FROM AUTHOR]

• Coalition strategies with capacity sharing/cross-port investment among ports are tested. • Provide equilibrium problem with equilibrium constraints conceptualization of problem. • Give evidence that coalitions can improve system resilience and demand fulfillment rates. • Found positive returns on investment for individual and network of ports via coalition. • Support policies that increase market share through increased reliability of service routes. Reliable port services are key to maritime freight transport system performance. These systems are vulnerable to disasters of anthropogenic or natural cause, which can significantly impact port capacity, handling times and overall system performance. To improve resilience of individual ports, strategies involving capacity sharing and protective cross-port investments through coalition formation are proposed. This collaborative port protection and investment approach to improve individual and system-level port resilience is formulated as an Equilibrium Problem with Equilibrium Constraints. That is, the program is bi-level with multiple players in the upper level and a common liner shipping problem in the lower level. Its solution is obtained at a Nash equilibrium wherein no port stakeholder can achieve better performance by unilaterally changing its investment plan. A Stackelberg equilibrium between upper and lower levels infers that best investment decisions are made given competition between ports and the market's response to improvements. The benefits of regional coalitions in this co-opetitive (competitive and collaborative) environment in terms of port and system resilience, port- and system-level demand fulfilment rates and return on investment are investigated from multiple perspectives, including the perspectives of shippers, port owners and the larger shipping network. With insights gained through study of the proposed coalition policies, this work aims to facilitate port authorities in making decisions on port capacity expansion, infrastructure investment and forming strategic partnerships. Shipping companies may also take into consideration the ability of a port to provide service under disruption events when choosing which ports to include in their service loops. [ABSTRACT FROM AUTHOR]

In today's world, changes in the economic and industrial sectors are taking place more quickly than in the past. Based on today's competitive market, considering the needs and desires of the customer is very important. Thus, designing the supply chain network to minimize the costs and improve the system efficiency, the service facility, and attention to the timely service delivery to the customer should be considered. Also, deployment costs to determine the number and position of facilities are regarded as another strategic issue. Therefore, to become closer to the real-world application, by considering the Jackson network model (queuing theory), the present study aims to design a closed-loop supply chain network to reduce the waiting time in the queue. Two objectives, namely minimizing the cost and waiting time incurred in queues formed in producers and distributors, are investigated. Queuing mathematical expressions are used both in dealing with objectives and constraints. To develop a model, which is close to real by considering uncertainty, the parameters, including demand rate and shipping cost of products, were considered as a trapezoidal fuzzy number. Also, we crisp this fuzzy uncertainty using both Jimenez and chance-constrained programming approaches. Due to the suggested model's complexity and nonlinearity, we linearized the mathematical model as much as possible, then two meta-heuristic algorithms, namely multi-objective particle swarm optimization and non-dominated sorted genetic algorithm (NSGA-II), are used to solve the model. First, the structural parameters of these algorithms are tuned by the Taguchi method. Then, numerous numerical test problems ranging from small to large scales are used to compare these algorithms considering Pareto front measuring indexes and various hypothesis tests. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine modal usage for shippers with limited transportation options to assess rail and truck quality of service. While service quality is an important consideration in shippers' mode choice decisions, freight studies often assume that shippers minimize total transportation costs subject to shipping rates. We test the cost minimization hypothesis using data on wheat shipments for individual grain elevators in the U.S. Great Plains where shippers are limited to rail and truck services with no direct access to navigable waterways, and find that shippers use a higher share of rail than they would if shipping rates alone determined their use of rail. This observation, in tandem with recent shipper surveys showing higher than expected ratings of service quality, suggests that shippers' modal choice of rail likely stems from a perception of higher quality of service provision. Moreover, this suggests that railroads have provided high service quality despite perpetual captivity concerns. Our results support the idea that even in markets with limited intermodal competition, other types of competition, including geographic, product, and intramodal competition are sufficient to compel railroads to provide a level of service that meets or exceeds expectations. • We find that grain shippers in the U.S. Great Plains ship more by rail than they would if they based their mode choices on transportation prices alone. • Results are consistent with the idea that railroad innovations have resulted in higher quality of service for relatively captive shippers. • Results are also consistent with the notion that railroads are compelled to provide high quality service, even in markets that are deemed to be relatively captive. • Grain shippers are willing to pay more in transportation costs in order to receive higher quality service. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, apart from leading to human cases and deaths, is also distracting the shipping stock market and the Baltic Indices. While event studies, as well as macroeconomic research has been conducted in the literature, we have not witnessed any effort yet to investigate how external shocks - and in particular the COVID-19 outbreak - may impinge on the shipping markets. Therefore, our research tries to fill in this gap by studying how a sanitary incident might influence shipping freight rates and stock values. We have used a market-model event study approach to investigate how fast and comprehensively shipping markets react upon certain latest evidence. To quantify the pandemic's economic impact, we estimated the abnormal returns; in a phase before and after the event, they may work as a measure of the unexpected effect of the event on a shipping firm's performance. The data that we have used in stock analysis come from a major shipping index, while for our freight study, time-series come from all main Baltic indices. Our results show that according to the key date set as the event window, different results appear of how pandemic-proof the dry market, the tanker market, and the shipping stock market have proven to be. [ABSTRACT FROM AUTHOR]

[Display omitted] • The freestanding BiOBr/CCFs composites photocatalyst has been constructed. • The BiOBr/CCFs exhibits the highest photogenerated carrier separation efficiency. • The BiOBr/CCFs shows excellent photocatalytic degradation RhB performance. The recycling efficiency of the photocatalyst is an important factor in practical application, which is one of the problems that most powder catalysts need to solve urgently. Herein, the freestanding photocatalyst that BiOBr nanosheets anchored on coal-based carbon fibers (CCFs) has been prepared. Integrating BiOBr to CCFs nanosheets can enlarge the specific surface area of materials, broaden the light absorption range, and increase the carrier transport rate. The optimum BiOBr/CCFs-2 sample exhibits excellent photocatalytic degrade Rhodamine B (RhB) efficiency of 92 % within 20 min under visible light, and the kinetic constant is 2.6 times higher than that of BiOBr. The photogenerated carriers generated by BiOBr nanosheets transfer to CCFs with excellent electrical conductivity and then synergistically improving the photocatalytic performance of BiOBr/CCFs-2. The BiOBr/CCFs-2 still remain excellent photocatalytic activity and cycling stability after five cycles, and the composite will be expected to be widely applied in other fields. [ABSTRACT FROM AUTHOR]

• Industry practice of filling up the "free" space on a truck may increase total logistics costs. • Joint optimization of transportation and inventory decisions may not be necessary when shipping costs are small relative to inventory costs and lost sales are not considered. • As shipping rates increase and lost sales are factored in, a joint optimization of transportation and inventory decisions can yield much greater savings. • A transportation cost function for the combined TL and LTL palletized shipment is presented. • A decision-support model integrates practical shipping rates, inventory holding costs, and lost sales to determine when and how much to order during inventory replenishment. • With the use of inner and outer approximations, the proposed MINLP inventory and transportation decision model with lost sales considered can be efficiently solved. Pallets are widely used for bulk shipping in the United States and Europe. In response to the call for more comprehensive research on inventory management that incorporates practical freight rates, this study investigates optimal inventory replenishment decisions by explicitly considering palletized shipping rates and lost sales in multi-product multi-period inventory system facing stochastic demand. We first introduce a stepwise transportation cost function that accurately captures real-world palletized less-than-truckload (LTL) and truckload (TL) shipment costs by accounting for both pallet quantity and truck capacity. We then formulate two novel inventory models that consider palletized freight transportation costs and the coexistence of LTL and TL shipments, with one model excluding lost sales and the other specifically incorporating lost sales. We apply both models to a wholesaler based in the Midwest, U.S., and analyze the effects of varying shipping rates and lost sales on inventory decisions. Our results show that the inclusion of lost sales in the inventory replenishment model can potentially reduce total costs for the company. Interestingly, our findings contradict prevailing industry practices of maximizing truck capacity, revealing that filling up the "free" space on a truck may increase total logistics costs. This holds true even when shipping rates are relatively high and lost sales are considered. Furthermore, our results suggest that joint optimization of transportation and inventory decisions may not be necessary when shipping costs are small relative to inventory costs and lost sales are not considered. However, as shipping rates increase and lost sales are factored in, a joint optimization that accounts for all factors can yield much greater savings. [ABSTRACT FROM AUTHOR]

Shore power (SP) can provide electricity from the land for ships instead of from ship engines; this approach can eradicate carbon emissions and foster green port development. However, due to the high SP installation cost and high electricity prices faced by shipping operators, the utilization rate of SP is still low. For the government, it is important and urgent to develop an effective policy to promote shore power usage. However, previous studies have not compared the effects of different government policies and have ignored the differences in SP usage stages. Therefore, in this study, three kinds of policies, subsidy, carbon tax and shipper green awareness improvement, are taken into consideration. The SP usage process is divided into two stages, namely, stimulating ship retrofitting for SP in the short term and sustaining SP usage in the long run. The purpose of this study is to provide policy-selection suggestions for short- and long-term SP promotion. Considering shipping supply chain competition, game theory is applied, and a series of Nash game models are formulated to investigate the equilibrium strategies of shipping operators on SP usage under different policies. A comparison of the results reveals that in the short run, the subsidy policy is superior to the carbon tax policy when both can promote SP usage. However, a moderate carbon tax is able to remedy the failure of subsidies. In the long run, a carbon tax may promote SP at the cost of diminishing social welfare. Improving shipper green awareness is more likely to be a preferable choice for both SP usage and social welfare. This paper also analyses the impacts of scale-based port congestion and green awareness. These findings can provide valuable suggestions for government and shipping operators to promote SP usage, reduce emissions and achieve the goal of green port construction. [Display omitted] • Explore policy selection to promote shore power usage in the short and long run. • Compare multiple policies and analyze their impacts on stakeholders' decisions. • Consider the shore power usage promotion and social welfare when selecting policy. • Study the impacts of port congestion and green awareness with scale effect. [ABSTRACT FROM AUTHOR]

• Semi-analytical models for two-dimensional multispecies transport of sequentially degradation products are developed. • The effect of rate-limited sorption on pollutant concentrations was determined. • Arbitrary time-dependent inlet boundary conditions strongly affect contaminant transport. • As the rate of sorption increases, the concentration of a constant pollutant tends to decrease under both constant and exponentially decaying time-dependent boundary conditions. • In the case of a pulsed boundary condition, the concentrations of contaminants such as PCE, TCE, and DCE increased sharply for high sorption rates. Most of the semi-analytical and analytical models employed to depict multidimensional, multispecies transport of sequentially degrading reaction products are built upon solving a set of coupled advection-dispersion equations (ADEs). Within these equations, sorption is considered as being equilibrium-controlled. However, it has been demonstrated that more realistic predictions of the transport of contaminants in the groundwater could be obtained by the use of a rate-limited sorption process instead of an equilibrium sorption assumption. This study is thus designed to devise semi-analytical models for the two-dimensional multispecies transport of a chemical mixture comprised of a parent compound and its degradation-daughter products which is influenced by rate-limited sorption subject to arbitrary time-dependent inlet boundary conditions. Three integral transforms are applied to generate a set of linear algebraic equations (AEs) resulting from the reductions of the ADEs. The contaminant concentration of each species is calculated by solving these AEs and then retransforming the solutions back to the original time-space domain. The simulation results obtained with our newly developed semi-analytical model are nearly identical to those generated using a numerical model based on the Laplace transform finite difference (LTFD) method. This confirms the validity of the new semi-analytical model. An investigation of the effect of rate-limited sorption on the migration of the contaminant plume is carried out using various time-dependent inlet boundary conditions. The sorption rate values vary from low to high, specifically, 0.05, 0.5, 5, and 50 years−1. The results show that the predicted concentrations of all contaminants within in the decay chain decrease as the sorption rate constant increases, for both constant and exponentially time-dependent boundary sources. However, under pulse loading boundary conditions, the concentrations of the later degradation products tend to increase with the sorption rate constant. The semi-analytical models created in this study, allow for different inlet boundary conditions, so can be utilized to simulate the transport of sequentially degrading reaction products. This greater accuracy makes them useful for many applications. [ABSTRACT FROM AUTHOR]

Shipping containers are increasingly adapted for modern modular construction of both permanent and mobile low-cost civilian-use structures, with the diversity and interchangeability of their uses suggesting the need for container-based modular structures to conform to standard fire safety requirements, notably insulation and integrity. Multi-storey structures in city centres consisting entirely of modified shipping containers, or shipping containers fitted into structural frames, are becoming more commonplace. Full-scale fire tests are generally rather expensive and can be complemented with systematic numerical studies of fire resistance times offered by a range of passive protection configurations and thermal transport properties. Noting that standardised fire resistance ratings have three components (structural, insulation, integrity), this study specifically considers fire resistance times offered by passive fire protection configurations, by performing a series of time-dependent finite element heat transfer analyses of passively protected side panel configurations. A set of reference curves with which to determine insulation resistance times in the context of the ISO 834–1 standard fire curve is presented, specifically for use in the rational fire safety design of modular structures constructed from shipping containers. Negligible literature is currently available on fire resistance ratings of shipping container structures. [ABSTRACT FROM AUTHOR]

Background: The coronavirus disease 2019 (COVID-19) pandemic directly affected the shipping industry globally, and South Africa experienced decreased cargo volumes and increased freight rates. In addition, National Ports Authority (NPA) charges are 69% and cargo dues 166% above the global benchmark mean. The NPA uses a rate of return (RR) model to calculate tariff increases that are contested by port stakeholders. Objectives: The study aimed to analyse the impact of COVID-19 trade disruptions and examine the associated higher liner freight rates, tariff applications for higher NPA tariffs and reduced investment in port infrastructure. It showed that adjusting the RR model variables can result in reduced tariffs and large cost savings for port users. Method: This study analysed the impact of the pandemic on South Africa's cargo volumes and freight rates. It critiqued the regulatory asset base, the asset beta, and the tax rate to be applied and calculated the adjustments to these RR model variables using five scenarios for FY2022/2023. Results: The results show a sharp decrease in cargo volumes during COVID-19 lockdowns, and a parallel increase in freight rates. The five-scenario results show how the NPA tariffs could be much lower, calculating a tariff decrease of 5.7% in scenario 4 and a 20% decrease in scenario 5. Conclusion: Amid the global rise of shipping rates and the economic impact of the pandemic on South Africa's trade, the results show that there is a potential to enhance South Africa's trade competitiveness through a decrease in NPA-weighted average tariff by 20%. [ABSTRACT FROM AUTHOR]

This study reports the high prevalence and molecular characterization of BoHV-1 infection in imported cattle with respiratory system disease after international transport. A high mortality rate of 14.16% (51/360) was reported in a group of animals imported from Hungary to Turkey in 2019. A total of 17 samples were evaluated (3 lung tissue and 14 nasal swab samples) from 15 cattle aged 6 to 9 months not vaccinated against BoHV-1. Virus isolation, polymerase chain reaction (PCR) and restriction endonuclease analysis (REA) procedures were performed within the scope of this study. By virus isolation in MDBK cells, cytopathologic effects was detected in 8 samples (3 lung tissue and 5 nasal swabs samples). The same eight samples were also found positive by BoHV-1 PCR targeting gC (UL44) gene region. According to the sequencing result, the sample (ID: 10054) dropped into a cluster of BoHV-1.1. The REA was applied to the samples to confirm the results of phylogenetic analysis. All of the isolates were identified in the subgroup BoHV-1.1 by REA. These results showed a high mortality risk for imported animals and the possibility for BoHV-1 entering the receiving country via imported animals after transport. This event is a serious problem both for the control of BoHV-1 as well as for animal health and welfare. [ABSTRACT FROM AUTHOR]

Ships are an important source of SO 2 and NO x , which are key parameters of air quality. Monitoring of ship emissions is usually carried out using in situ instruments on land, which depend on favourable wind conditions to transport the emitted substances to the measurement site. Remote sensing techniques such as long-path differential optical absorption spectroscopy (LP-DOAS) measurements can supplement those measurements, especially in unfavourable meteorological conditions. In this study 1 year of LP-DOAS measurements made across the river Elbe close to Hamburg (Germany) have been evaluated. Peaks (i.e. elevated concentrations) in the NO 2 and SO 2 time series were assigned to passing ships, and a method to derive emission rates of SO 2 , NO 2 and NO x from those measurements using a Gaussian plume model is presented. A total of 7402 individual ship passages have been monitored, and their respective NO x , SO 2 and NO 2 emission rates have been derived. The emission rates, coupled with the knowledge of the ship type, ship size and ship speed, have been analysed. Emission rates are compared to emission factors from previous studies and show good agreement. In contrast to emission factors (in grams per kilogram fuel), the derived emission rates (in grams per second) do not need further knowledge about the fuel consumption of the ship. To our knowledge this is the first time emission rates of air pollutants from individual ships have been derived from LP-DOAS measurements. [ABSTRACT FROM AUTHOR]

This study proposes a two-tier cross-validation and backtesting procedure, including expanding and rolling-window test metrics in predictive analytics of container freight rates by utilizing the system dynamics approach. The study utilized system dynamics to represent the nonlinear complex structure of container freight rates for predictive analytics and performed univariate and multivariate time-series analysis as benchmarks of the conventional approach. In particular, the China containerized freight index (CCFI) has been investigated through various parametric methodologies (both conventional time-series and system dynamics approaches). This study follows a strict validation process consisting of expanding window and rolling-window test procedures for the out-of-sample forecasting accuracy of the proposed systemic model and benchmark models to ensure fair validation. In addition to the predictive features, major governing dynamics are presented in the analysis which may initiate further theoretical discussions on the economics and structure of the container shipping markets. Empirical results indicate that postsample accuracy can be affected by the sample size (training data size) in a given set of methodologies. Considering the economic challenges in the container shipping industry, the proposed methodology may help users to improve their cash-flow visibility and reduce the adverse effects of volatility in container shipping rates. [ABSTRACT FROM AUTHOR]

The tremendous diversity of life in the ocean has proven to be a rich source of inspiration for drug discovery, with success rates for marine natural products up to 4 times higher than other naturally derived compounds. Yet the marine biodiscovery pipeline is characterized by chronic underfunding, bottlenecks and, ultimately, untapped potential. For instance, a lack of taxonomic capacity means that, on average, 20 years pass between the discovery of new organisms and the formal publication of scientific names, a prerequisite to proceed with detecting and isolating promising bioactive metabolites. The need for "edge" research that can spur novel lines of discovery and lengthy high-risk drug discovery processes, are poorly matched with research grant cycles. Here we propose five concrete pathways to broaden the biodiscovery pipeline and open the social and economic potential of the ocean genome for global benefit: (1) investing in fundamental research, even when the links to industry are not immediately apparent; (2) cultivating equitable collaborations between academia and industry that share both risks and benefits for these foundational research stages; (3) providing new opportunities for early-career researchers and under-represented groups to engage in high-risk research without risking their careers; (4) sharing data with global networks; and (5) protecting genetic diversity at its source through strong conservation efforts. The treasures of the ocean have provided fundamental breakthroughs in human health and still remain under-utilised for human benefit, yet that potential may be lost if we allow the biodiscovery pipeline to become blocked in a search for quick-fix solutions. [ABSTRACT FROM AUTHOR]

Ship domain is an important theory in ship collision avoidance and an effective collision detection method. First, several classical ship domain models are used in experiments. The results show that the alarm rate is too high in busy waters, leading to greatly reduced practicality of the model. Potential collision risk cannot be detected effectively, especially for a ship with restricted manoeuvrability, which is usually regarded as an overtaken ship due to its navigation characteristics. Therefore, it is necessary to fully consider the interference of other ships to ships with limited manoeuvrability in an encounter situation. A novel ship domain model for ships with restricted manoeuvrability in busy waters is proposed. Considering the navigation characteristics of a ship with restricted manoeuvrability and the influence of the ship–ship effect, an algorithm to determine the boundary of the ship domain model is given by force and moment equations. AIS trajectory data of the North Channel of the Yangtze River Estuary are used to perform a comparative experiment, and four classical ship domain models are employed to perform comparative experiments. The results show that the alarm rates of the novel ship domain model are 7⋅608%, 15⋅131%, 55⋅785% and 7⋅608% lower than those of the other four classical models, and this outcome can effectively reduce the high false alarm rate produced by other models in this environment. [ABSTRACT FROM AUTHOR]

This paper develops an analytical model allowing one to better understand the relationship between the 'Belt' and the 'Road' in China's Belt and Road Initiative (BRI). Firstly, we establish the link between the minimum subsidies received by the rail operators from the Chinese governments and the market conditions in the maritime sector. Then, we characterize the relationship between the new rail and the existing port. We show that the minimum subsidies are influenced by the external shipping demand and the shipping freight rate. Furthermore, the local economy will benefit from the BRI if the firm providing the services via rail can compete with the operator of the maritime routes in the future. Specifically, our analysis shows that competition will improve the service quality by reducing the delay costs, the transportation costs, and the shipping price and time, and that the magnitude of the welfare gain will mainly depend on the shippers' sensitivity to time and price. The policy and economic implications of separate and joint management of the port and rail facilities are discussed. [ABSTRACT FROM AUTHOR]

Many factors affect ship values, but the most important is freight rates. This effect is more dynamic, especially in the dry bulk market, which has characteristics close to a perfectly competitive market. The literature does not provide a complete answer about whether the effects of freight on ship values differ by ship type and age in the market; therefore, this study examined the effect of changes in the freight rates of the main ship types used in the dry bulk market on their values in different age groups. The ship types included in the study are Capesize, Panamax, and Handymax vessels, while the age groups are newbuilds, 5-year-old, and 10-year-old ships. Individual regression models were established and analyses were applied for each category. According to the obtained results, smaller vessels were more affected by changes in freight rates, and the effect of changes in freight rate increased with the age of the ship. Also, the price volatility of smaller ships was lower, while it was higher for older ships. It is hoped that these results may provide comparative results by ship type and guide industry stakeholders in reducing risks. [ABSTRACT FROM AUTHOR]

Ships are an important source of SO2 and NOx, which are key parameters of air quality. Monitoring of ship emissions is usually carried out using in situ instruments on land, which depend on favourable wind conditions to transport the emitted substances to the measurement site. Remote sensing techniques such as long path DOAS (LP-DOAS) measurements can supplement those measurements, especially in unfavourable meteorological conditions. In this study one year of LP-DOAS measurements made across the river Elbe close to Hamburg (Germany) have been evaluated. Peaks (i.e. elevated concentrations) in the NO2 and SO2 time series were assigned to passing ships and a method to derive emission rates of SO2, NO2 and NOx from those measurements using a Gaussian plume model is presented. 7402 individual ship passages have been monitored and their respective NOx, SO2 and NO2 emission rates have been derived. The emission rates, coupled with the knowledge of the ship type, ship size and ship speed have been analysed. Emission rates are compared to emission factors from previous studies and show good agreement. In contrast to emission factors (in gram per kilogram fuel) the derived emission rates (in gram per second) do not need further knowledge about the fuel consumption of the ship. To our knowledge this is the first time emission rates of air pollutants from individual ships have been derived from LP-DOAS measurements. [ABSTRACT FROM AUTHOR]

Pricing strategies and tactics and itinerary design are some of the most important decisions faced by cruise companies in order to maximize their profits. This research aims both at analyzing factors that determine the price of a cruise package and at classifying cruise companies according to their pricing tactical decisions. In order to do so, we have gathered more than 84,000 cruise prices corresponding to around 9,200 departures for 2019, which belong to eight of the most important cruise companies. This paper combines two methodologies. On the one hand, hedonic regressions, which are commonly used in the tourism industry in order to identify factors affecting prices. On the other hand, cluster analysis, which allows us to classify cruise companies' pricing tactical decisions. The results obtained allow us to conclude that a few factors are able to explain more than 76% of the variance of the price: number of nights, type of cabin, month of departure, destination, cruise company and ship rating. Another relevant contribution of this paper is the definition of three clusters when analyzing tactical pricing decisions for cruise companies jointly and eight clusters when the analysis is carried out with ships. [ABSTRACT FROM AUTHOR]

Lee, S.-Y. and Lee, N.-Y., 2023. Improvement of the port development system through the Port Service Index (PSI). In: Lee, J.L.; Lee, H.; Min, B.I.; Chang, J.-I.; Cho, G.T.; Yoon, J.-S., and Lee, J. (eds.), Multidisciplinary Approaches to Coastal and Marine Management. Journal of Coastal Research, Special Issue No. 116, pp. 294-298. Charlotte (North Carolina), ISSN 0749-0208. Korea's port development adjusts the completion time and size of port facilities according to the future port throughput. The current port development system, which is referred to as "throughput-linked port development (Trigger Rule)", has received positive evaluation for efficiently executing the limited port development budget. Recently concerns have been growing over deteriorating service levels in port facilities in Korea due to accelerated aging of terminal facilities. However, the current port development system does not possess any standard for assessing the level of service and utilizing development indicators. The purpose of this paper is to calculate the Port Service Index (PSI) by selecting indicators to measure the Level of Service (LOS) of ports and deriving weights between the indicators, so that the current "throughput-linked port development (Trigger Rule)" can be linked with the level of service. Based on the result of analysis on a variety of preceding studies, the ship waiting rate, berth productivity, ship port time and ship productivity were selected as four indicators to constitute the Port Service Index. The AHP and entropy methodologies were used to derive weights for each of four indicators which were later combined to calculate the comprehensive weight. The calculation formula of the Port Service Index (PSI) was derived by using the aggregated weights of each indicator, based on which the LOS of domestic container and bulk terminals were evaluated and this measurement result was divided into 6 classes to define each LOS. This paper contributes to draw the improvement measures for port development system that are able to connect the quantitative indicator of throughput, as well as a qualitative indicator of the level of "service". [ABSTRACT FROM AUTHOR]

• A reasonable method of ship route segmentation is proposed. • A practical iterative method for ship speed optimization is developed. • The error between optimized fuel consumption and actual fuel consumption is reduced. • The developed method can achieve a ship fuel-saving rate of 2.4 % to 5.4 %. An iterative optimization method that combines the principle of ordered clustering was proposed to address the strong correlation among route segmentation, weather loading, and ship speed optimization. Focusing on a single voyage task on a given route, the speed of an ocean-going container ship was optimized to achieve the minimum fuel consumption of the ship. The verified data-driven method was used to build a ship fuel consumption prediction model, and the Fisher optimal segmentation method was applied to segment ship routes. Subsequently, the speed optimization problem was solved using an iterative optimization method. The optimization results confirmed that the iterative optimization method has significant advantages in realizing route segmentation with the highest weather similarity within the segment. Extensive empirical studies on six case routes revealed the significant fuel-saving potential of the proposed iterative optimization method. Under different routes and weather conditions, the proposed iterative optimization method achieves a ship fuel-saving rate of 2.4 %–5.4 % and provides a reliable technical reference for the shipping industry to reduce the energy consumption and emissions of ships. [ABSTRACT FROM AUTHOR]

Transporting energy in liquefied forms results in reduction in volume, which enables energy to be transported economically over long overseas distances. In this study, liquefied natural gas, liquid ammonia and methanol are proposed to transport the energy of natural gas in different forms to overseas. Due to temperature difference between the energy storage medium and the ambient, a portion of liquefied energy carriers mass is lost as boil-off gas (BOG). Therefore, a technical assessment based on energy and exergy analyses is conducted in this work to assess the total required energy and losses due to BOG for each energy carrier. To make a fair comparison among the energy carriers, the ship volume capacity is the fixed factor. The results show that the total daily energetic BOGs for LNG, ammonia, and methanol are calculated as 0.610%, 0.098%, 0.034% while the exergetic BOGs are 0.491%, 0.068%, 0.032%, respectively. Ammonia and methanol generate significantly less daily BOG, respectively, compared to LNG during the full supply chain, which make them alternative for efficient energy carrier transport. Image 1 • Boil-off gas determination of potential energy carriers for overseas transportation. • Energy required for production of LNG: 6.73 MJ/kg and ammonia: 6.73 MJ/kg. • Daily sea shipping BOG rates are LNG: 0.12%, ammonia: 0.024%, methanol: 0.005%. • Comparison of LNG, ammonia, and methanol using energy losses within supply chain. [ABSTRACT FROM AUTHOR]