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Maritime piracy is a serious threat to the safety of cargo, ships, and crews, which can cause enormous losses to stakeholders, highlighting the significance of piracy risk assessment and prevention to the maritime industry. In this study, we propose a two-step analytical framework based on a Random Forest (RF) model, Generative Adversarial Nets (GANs), and Matrix Completion (MC) algorithm to assess the risks of successful piracy attacks. We consider different decision-makers in each step, namely, pirates first select which ships to attack and then ship operators determine the probability of a (un)successful attack. We propose different influencing factors for each step and, in the meantime, solving the problems of incomplete and imbalanced data. A case study in Southeast Asia is then conducted based on the proposed approach. The results show that, in mild wind weather, the likelihood of a piracy attack on a ship with a DWT not exceeding 50,000 tons is up to 90 %. Further, if the attack occurs between 0 and 6 a.m., the probability of success is over 90 %. These results provide more specific information for ship operators and local authorities to develop efficient anti-piracy strategies and policies.

Uncertainties in port handling efficiency can cause port delays in the liner shipping system. Furthermore, policies on carbon emission reduction, such as EEXI standards, restrict the potential for speed optimization in liner shipping operations. Traditional tactical planning speed optimization is unsuitable for operational-level decision making, leading to unreliable schedules. From a schedule-reliability and energy-efficiency perspective, we propose a real-time speed optimization method based on discrete hybrid automaton (DHA) and decentered model predictive control (DMPC). We use a dynamic adjustment of sailing speed to offset the disturbance caused by port handling efficiency uncertainties. First, we establish a DHA model that describes each ship's hybrid dynamics of state switching between sailing and berthing; then, we develop a prediction model for the DMPC controller, which is analogous to the DHA model. The schedule is transferred into time-position coordinates as controller reference trajectories in the receding horizon speed optimization framework. We consider determining tracking errors, carbon emissions, and fuel consumption as our objectives, and we carry out engine power limitation (EPL) analysis for the sample ship, which turns the EEXI standards into constraints. We attain the recommended speed by solving a mixed-integer optimization. We carry out a case study, and our results indicate the effectiveness of our proposed DHA-DMPC scheme in lowering port delays and achieving the best trade-off between schedule reliability and energy efficiency. Additionally, we conduct further experiments to analyze the impacts of various carbon reduction policies on the performance levels of liner shipping operations.

In 2020, China proposed the country's dual carbon goals of peaking carbon emissions by 2030 and achieving carbon neutrality by 2060. Under the dual carbon goals, the low-carbon transformation has become an important development direction for Chinese ports. Taking eight ports in China's Bohai-rim port group as an example, this study adopts the Slacks-Based Measure (SBM) model to evaluate the port efficiency considering the environmental factor of carbon dioxide (CO2) emissions. The results show that the average scale environmental efficiency of the eight ports during 2005-2020 is the highest, followed by local pure technical environmental efficiency and global technical environmental efficiency. The efficiency values of each port under different environmental efficiency categories vary greatly. Overall, each port is in a state of environmental inefficiency. From port technology, input-output optimization, supervision, and management of relevant departments, recommendations for improving the environmental efficiency of ports under the dual carbon goals are put forward.

Anthropogenic noise is a recent addition to the list of human-made threats to the environment, with potential and established negative impacts on a wide range of animals. Despite their economic and ecological significance, few studies have considered the impact of anthropogenic noise on crustaceans, though past studies have shown that it can cause significant effects to crustacean physiology, anatomy, and behaviour. Mating behaviour in crustaceans could potentially be severely affected by anthropogenic noise, given that noise has been demonstrated to impact some crustacean's ability to detect and respond to chemical, visual, and acoustic cues, all of which are vital in courtship rituals. To explore if noise has an impact on crustacean mating, we tested the responses of male green shore crabs (Carcinus maenas) from the southwest UK coast by exposing them to ship noise recordings while simultaneously presenting them with a dummy-female soaked in the female-sex pheromone uridine diphosphate (UDP) in an experimental tank setup (recording treatment: n = 15, control treatment: n = 15). We found a significant, negative effect of noise on the occurrence of mating behaviour compared to no noise conditions, though no significant effect of noise on the time it took for a crab to respond to the pheromone. Such effects suggest reproductive impairment due to anthropogenic noise, which could potentially contribute to decreased crustacean populations and subsequent ecological and economic repercussions. Given the findings of our preliminary study, more research should be undertaken that includes larger sample sizes, double blind setups, and controlled laboratory trials in order to more fully extrapolate the potential impact of noise on mating in the natural environment.

The introduction of several alternative marine fuels is considered an important strategy for maritime decarbonization. These alternative marine fuels include liquefied natural gas (LNG), liquefied biogas (LBG), hydrogen, ammonia, methanol, ethanol, hydrotreated vegetable oil (HVO), etc. In some studies, nuclear power and electricity are also included in the scope of alternative fuels for merchant ships. However, the operation of alternative-fuel-powered ships has some special risks, such as fuel spills, vapor dispersion and fuel pool fires. The existing international legal framework does not address these risks sufficiently. This research adopts the method of legal analysis to examine the existing international legal regime for regulating the development of alternative-fuel-powered ships. From a critical perspective, it evaluates and predicts the consequences of these policies together with their shortcomings. Also, this research explores the potential solutions and countermeasures that might be feasible to deal with the special marine environmental risks posed by alternative-fuel-powered ships in the future.

Ocean-based industries like shipping, aquaculture, and wind energy are growing at an unprecedented rate resulting in challenges related to siting and environmental management. As marine aquaculture and other ocean-based industries continue to expand, robust marine spatial planning analyses that reconcile existing ocean uses and integrate pertinent environmental and planning data are critical for identifying compatible locations. In this study, a series of geospatial analyses were used for aquaculture siting within and around a heavily trafficked and highly utilized maritime port in the San Diego Bay area of California, USA. Using a centralized geodatabase representing key aquaculture planning spatial datasets, recommendations for specific areas for aquaculture were developed based on appropriate environmental conditions for candidate shellfish and algae aquaculture species culture systems. Areas that were known constraints were first identified to determine potentially usable areas for shellfish and macroalgae (i.e., seaweed) aquaculture using an exclusion analysis, a type of multi-criteria decision analysis, to eliminate all areas without compatibility. Within the remaining usable area, we further considered shellfish and macroalgae culture system-specific factors within a 'culture systems analysis' to determine where different culture systems have potential for success. This analysis provides a foundation of coastal intelligence for guiding the aquaculture industry and natural resource managers towards appropriate siting decisions. This study can serve as a replicable example of aquaculture spatial planning approaches for siting sustainable aquaculture and other blue economy industries.

As an important component of new western land-sea corridor, the construction of Pinglu Canal will effectively alleviated waiting time and congestion costs and enhance the reliability and resilience of the regional maritime transport network in the post-pandemic era in particular. From the perspective of competition and cooperation game, this paper investigates typical transportation routes from the port of Jakarta in Indonesia to the port of Nanning in China from the key factors of the changes in freight volume and the evolution of profits and subsidies, considering local government subsidies, environmental costs, marine emissions and other critical factors. The results demonstrated that in the centralized strategies adopted by two transport route operators, as the volume of goods transported through Pinglu Canal increased, so the corresponding profits increased. The increase in subsidies also contributed to generating the volume of freight through Pinglu Canal, but the social welfare under the decentralized strategy adopted by both transport route operators was more effective than that of the centralized strategy.

Emission trading is an efficient measure to combat climate change, which is one of the biggest threats to the international community and human health. The shipping industry has previously been considered an energy-saving industry but the growth rate of its emissions far exceeds that of other industries. On 10 May 2023, the EU enacted Regulation (EU) 2023/957, which officially included the shipping industry in the EU-ETS. Therefore, this may lead to investor-state disputes regarding emission trading in the marine industry due to the conflicts between the obligation to combat climate change and the obligation to protect investments of the host states. This has resulted in the breaching of International Investment Agreements. In this context, this study aimed to propose practical recommendations for global marine market practitioners to avoid the potential risks of disputes by reflecting on the existing practice regarding climate change-related investor-state dispute resolutions and identifying the trends and problems of the current dispute resolution mechanism. These included inconsistency in the review standard, inconsistency in the review scope, and broad interpretation by the tribunal. Finally, this study proposed that by setting public purpose and exception clauses in the preambles of the International Investment Agreements and incorporating the specific obligations of the foreign investors and the regulatory power of the hosting states in the drafting stage, the potential risks for disputes regarding the new EU directive in the global marine industry could be effectively reduced.

Efficient and rapid deployment of maritime search and rescue(MSAR) resources is a prerequisite for maritime emergency search and rescue, in order to improve the efficiency and accuracy of MSAR. This paper proposes an integrated approach for emergency resource allocation. The approach encompasses three main steps: identifying accident black spots, assessing high-risk areas, and optimizing the outcomes through a synergistic combination of an optimization algorithm and reinforcement learning. In the initial step, the paper introduces the iterative self-organizing data analysis technology (ISODATA) for identifying accident spots at sea. A comparative analysis is conducted with other clustering algorithms, highlighting the superiority of ISODATA in effectively conducting dense clustering. This can effectively carry out dense clustering, instead of the situation where the data spots are too dispersed or obvious anomalies that affect the clustering. Furthermore, this approach incorporates entropy weighting to reassess the significance of accident spots by considering both the distance and the frequency of accidents. This integrated approach enhances the allocation of search and rescue forces, ensuring more efficient resource utilization. To address the MSAR vessel scheduling problem at sea, the paper employs the non-dominated sorting genetic algorithm II combined with reinforcement learning (NSGAII-RL). Comparative evaluations against other optimization algorithms reveal that the proposed approach can save a minimum of 7% in search and rescue time, leading to enhanced stability and improved efficiency in large-scale MSAR operations. Overall, the integrated approach presented in this paper offers a robust solution to the ship scheduling problem in maritime search and rescue operations. Its effectiveness is demonstrated through improved resource allocation, enhanced timeliness, and higher efficiency in responding to maritime accidents.

The ocean industries are characterized by being export-driven. The exports of ocean industries (hereafter termed ocean exports) caused environmental pollution with amounts of CO2 emissions and thereby affected climate change. There is a need, therefore, for accurate assessments of CO2 emissions embodied in ocean exports-which can help policymakers adopt targeted emission-reduction measures to formulate sustainable ocean policies. However, few studies of ocean-industry emissions considered impacts in sectoral and trade pattern heterogeneity, especially from export perspective. To fill this gap, we measured and evaluated the export-embodied CO2 emissions from China's ocean industries, based on our newly developed high-resolution and comparable time-series environmentally extended input-output database, called EE-DPN-OEIOT. The results showed that China's ocean exports generated 94.3 Mt of embodied CO2 emissions in 2017, with nearly 40% originating from processing ocean exports. Regarding the evolution from 2007 to 2017, the total export-embodied CO2 emissions from ocean industries decreased by 7.3%, while the embodied CO2 emissions in processing ocean exports increased by 50.1%. From 2007 to 2017, the decrease in carbon emission intensity was the major driving factor of the downturn in export-embodied CO2 emissions across the total ocean economy and for seven ocean subsectors (60%), while the export-scale effect primarily drove the increases in CO2 emissions. Moreover, there were disparities in the driving factors behind changes in embodied CO2 emissions between processing and non-processing ocean exports. Based on our findings, we proposed three recommendations from a trade perspective to facilitate low-carbon sustainable transition of China's ocean economy, thus better fulfilling Sustainable Development Goal 14.

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