To provide integrated communication-navigation means for maritime distress and safety communication, China has established the BDMSS (BeiDou Message Service System) based on the BeiDou system's regional short message capability. After five years of operation, BDMSS has been successfully recognized by the IMO (International Maritime Organization) as a GMDSS (Global Maritime Distress and Safety System) service provider. This paper outlines the evaluation and recognition procedures for mobile satellite systems used in GMDSS, as defined by the IMO and the IMSO (International Mobile Satellite Organization). It examines BDMSS's application process for IMO recognition and the technical and operational assessment conducted by IMSO. Key assessment points for BDMSS, including availability, restoration and spare satellite arrangements, priority mode, on-site demonstration scenario design, and additional considerations, are analyzed. The results enhance understanding of the international approval and evaluation criteria for potential GMDSS mobile satellite systems. Furthermore, they provide valuable references for future revisions of IMO Resolution A.1001(25) and for incorporating international maritime requirements into the design of new mobile satellite systems.

A stochastic programming model is devised for the multi-base, multi-drone location and routing problem, considering the simultaneous movements of drones and ships as well as ship movement uncertainty. A decoding algorithm is developed to divide a sequence into sub-routes using ship-based and drone-based strategies. Furthermore, a bi-stage heuristic algorithm is proposed, combining a genetic algorithm and Tabu search. In the bi-stage algorithm, the first stage addresses ship movement uncertainty and employs Tabu search to solve the drone base station location problem. The second stage uses the genetic algorithm to route the drones for detection based on the location results. Numerical experiment results show that, in the same application scenario, the drone-based (D) strategy can optimize flying distance by 7% while reducing computing time by 50% compared to the ship-based (S) strategy. Considering ship movement uncertainty can reduce flying distance by 10% for the drone base station location solution. Flying distance is sensitive to the number of available drones. For example, in a scenario with two base stations and 3-5 drones, adding one drone may increase flying distance by 15%. Speeding up the drones by 5% may reduce flying distance by 5%. This method can effectively generate multi-UAV inspection paths that meet the requirements of moving ships, providing technical support for maritime supervision.

In response to the IMO Preliminary Strategy for Greenhouse Gas Emission Reduction from Ships and the domestic "3060 Double Carbon Goal", carbon reduction routes applicable to the domestic fleet are proposed. Using the fleet carbon reduction analysis model, the carbon reduction amount, carbon intensity and carbon reduction cost of a domestic shipping company's fleet based on the above fuel routes are analyzed by defining the fossil fuel, methanol fuel and ammonia fuel routes. The results of the study show that the fleet based on methanol and ammonia fuel paths can meet the requirements of the "Preliminary Strategy for Ship Temperature IMO Room Gas Emission Reduction" and the domestic "3060 Double Carbon Goal", and that the fleet can be transitioned from the traditional bunker fuel type to the methanol/ammonia ready type as soon as possible in the near future, and then to methanol/ammonia powered type in the medium and long term. In the near future, we can transition from traditional fuel oil ships to methanol/ammonia fuel ready (methanol/ammonia fuel power system preset) ships as soon as possible, and in the middle and long term, we can gradually transition to methanol/ammonia fuel-powered ships; green methanol and green ammonia have their own advantages, and the number of future medium and long term commercial applications mainly depends on the differences between green methanol and green ammonia in the aspects of availability and economy.

Study on the location selection problem of multi-level offshore ship oil spill emergency equipment depots is of great guiding significance for the effective utilization of oil spill emergency resources, the improvement of regional oil spill emergency response capabilities, and the perfection of the oil spill emergency response system. According to the distribution of oil spill risk points and the predicted oil spill volume, combined with the characteristics of the emergency service radius and comprehensive removal and control capabilities of oil spill emergency equipment depots at different levels, a location selection model for multi-level offshore ship oil spill emergency equipment depots is established with the objectives of achieving the best coverage, the highest reliability, and the strongest timeliness for different risk waters. Then, the MOPSO algorithm and NSGA- Ⅱ algorithm are used to solve the model, and the Pareto optimal solution set is obtained. Starting from the perspective of coordinated rescue and based on the emergency service capabilities of equipment depots at different levels, the location selection model realizes the best multiple coverage of different risk waters, aiming to share emergency resources and further enhance the regional emergency response capabilities.

All-electric tugboats (AETs) produce fewer carbon emissions, but their battery charging requirements can lead to ship delays, which may increase the overall carbon emission costs in ports. Therefore, it is essential to study the carbon emission reduction performance of AETs in ports and compare their effectiveness with that of diesel tugboats (DTs). This paper establishes scheduling optimization models for AETs and DTs, respectively, using the sum of tugboat carbon emissions and ship delay carbon emissions as the objective function. Taking a day's data from three port areas in Ningbo-Zhoushan Port as an example, the Gurobi solver is employed to find the optimal solution. A comparative study is conducted on the minimum tugboat carbon emission cost and total carbon emission cost when AETs and DTs with the same horsepower and quantity are used to handle the same ships. The results show that if only the carbon emission cost of tugboats is considered, AETs can reduce carbon emission costs by 9.5% to 22.9% compared to DTs. However, when considering the overall carbon emission cost of the port areas, AETs still demonstrate good carbon emission reduction effects when handling fewer than 8 ships. When the number of ships exceeds 8 and the port is busy, the charging requirements of AETs increase the overall carbon emission cost of the port by 24.68%, which is not conducive to port carbon emission reduction.