Search Results (196)

This study evaluates the cost competitiveness of the Northern Sea Route (NSR) relative to the Suez Canal Route (SCR) for a representative Asia–Europe voyage, using the Shanghai–Rotterdam route as the reference case. A scenario-conditioned stochastic Monte Carlo framework is developed to estimate the probability that the NSR incremental voyage cost is lower than that of the SCR, $P_{NSR}$. The analysis identifies the probabilistic threshold conditions under which the NSR can become cost-competitive under seasonal and geopolitical uncertainty. The model decomposes insurance-related costs into route-specific risk components and jointly incorporates seasonal conditions, Arctic geopolitical risk, and Red Sea war-risk exposure under five scenarios. The results show that $P_{NSR}$ remains below 50% in all scenarios, indicating that the NSR does not achieve cost competitiveness in the majority of simulations under the assumed cost structure. The summer-current base case yields $P_{NSR}$ = 16.6%, while geopolitical easing increases it to 23.5%. In contrast, the winter-current scenario reduces $P_{NSR}$ to 1.4%, confirming a strong seasonal constraint on NSR viability. Single-variable sensitivity analysis identifies icebreaker fees and Arctic navigation insurance premiums as the most influential NSR-side cost variables, whereas SCR war-risk exposure has the largest overall effect by increasing SCR-side costs. Further threshold analysis shows that no single variable within a plausible operating range is sufficient to raise $P_{NSR}$ to 50%. A combined two-variable analysis shows that simultaneous reductions in icebreaker fees and Arctic navigation premiums can bring $P_{NSR}$ close to 50% under less extreme individual parameter values than those required in the single-variable analysis. These findings suggest that NSR competitiveness is structurally constrained and is more likely to depend on coordinated changes in multiple cost components than on a favourable change in any single variable. Full article

This paper proposes an integrated routing framework for liner shipping networks in which the routing decision concerns the movement of one or more containers from an origin to a destination, jointly addressing topological feasibility, temporal consistency, and cost–time trade-offs. The methodology combines a label-setting routing algorithm with a post-processing phase that enables multi-criteria analysis and clustering of origin–destination pairs. Within this framework, each container route explicitly accounts for service schedules, frequencies, dwell time, transshipment constraints, and port-specific handling costs, thereby ensuring the generation of temporally feasible routes over large-scale liner shipping networks. Two optimality criteria are considered for the container routing problem: time and cost. Computational experiments on a real-inspired network demonstrate the scalability of the proposed approach and highlight the difference between optimal time and cost-routing choices for containers. Further insights are obtained through clustering analyses, which reveal heterogeneous routing profiles and distinct trade-off patterns across origin–destination pairs, providing additional management insights beyond aggregate performance indicators. Overall, the proposed procedure offers a flexible and extensible tool for analyzing container movements within liner shipping services and supports advanced decision-making in maritime network design and service planning. Full article

The rapid decline of Arctic sea ice is increasing the feasibility of trans-Arctic shipping along the Northern Sea Route (NSR)—a considerably shorter and potentially lower-emission alternative to the Suez Canal route—for which the Bering Strait is the first gateway chokepoint for vessels departing the Republic of Korea. Continuous optical monitoring of this region is fundamentally limited by cloud cover and polar night during the ice season; in 2025, no usable Sentinel-2 MultiSpectral Instrument (MSI) scene was available for January (mean cloud cover 56.9% in November). This study therefore used all-weather Sentinel-1 dual-polarization (VV, VH) C-band SAR, acquired monthly through Google Earth Engine for January–December 2025, to classify open water, thin ice (<30 cm), and first-year ice (FYI, ≥30 cm) with a Support Vector Machine (SVM); land was masked prior to classification. Three kernels (linear, radial basis function (RBF), and polynomial) were compared after $5\times 5$ Lee speckle filtering, using VV, VH, and the VV/VH ratio (in dB) as input features. The RBF kernel achieved the highest accuracy (overall accuracy 97.0%, $\kappa =0.954$), and the classification was cross-referenced against the U.S. National Snow and Ice Data Center (NSIDC) Multisensor Analyzed Sea Ice Extent (MASIE) mask. The monthly ice maps were then reclassified into World Meteorological Organization (WMO)/POLARIS ice types and converted into a POLARIS Risk Index Outcome (RIO) cost surface using simplified proxy weights consistent with the POLARIS risk ordering rather than the full Risk Index Value table; least-cost paths and a seasonal navigability assessment were derived for three representative ship ice classes—a non-ice-class vessel, an ice-class 1A merchant vessel (≈PC7), and the icebreaker Araon (≈PC5)—under risk-index, water-depth, and coastal-buffer constraints. For a representative refreezing-onset scene, the routing outcome was strongly ice-class dependent: the non-ice-class vessel and the ice-class 1A vessel were blocked (after 42 and 139 km, respectively), whereas only the icebreaker Araon completed the transit along a 124 km least-cost path within a 2 km safety corridor. The framework demonstrates how an interpretable SAR-based sea-ice classification can be coupled with a recognized international risk standard to support risk-informed navigation through the Bering Strait gateway. By indicating when shorter, lower-emission Arctic transits are feasible while limiting the risk of ice-related accidents in this sensitive polar environment, the framework also contributes to the safety and environmental sustainability of trans-Arctic shipping. Full article

Arctic shipping should not be understood as a sustainable transport outcome that will emerge automatically as sea ice declines. Rather, its long-term viability depends on whether stable operations can be achieved under persistent environmental and political uncertainties. Existing studies have examined Arctic shipping risks, governance arrangements, and route feasibility, but have paid limited attention to how cargo owners, shipping companies, and governments interact strategically under composite risk constraints. To address this gap, this paper develops a three-party evolutionary game model involving cargo owners, shipping companies, and the government under weather risk and political risk, and uses numerical simulation to examine system evolution, policy thresholds, and external shock responses. The results show that the system tends to converge toward a high-coordination equilibrium under low-risk conditions, whereas medium-risk conditions may lead to bistability and a low-coordination trap when government support remains below a critical threshold. Composite political shocks further amplify system vulnerability and weaken sustainable route operation. These findings suggest that the key challenge of Arctic shipping lies not in physical route accessibility alone, but in whether risk governance, market participation, and institutional support can jointly stabilize expectations and promote sustainable Arctic shipping operations. Full article

The industrial sector accounts for 34% of global energy consumption, of which heat accounts for 74%, predominantly derived from fossil fuels. Solar Heat for Industrial Processes (SHIP) offers a viable decarbonisation route for low-to-medium temperature applications (80–250 °C)—a range that includes processes such as tequila production. Yet integrated techno-exergo-economic assessments for small-scale, modular systems in agro-industrial contexts remain scarce. This study presents a technical, thermodynamic, and economic evaluation of a 2.5 MW_th parabolic trough collector system with thermocline thermal energy storage, integrated into a tequila production facility in Jalisco, México. A parametric analysis across seven solar multiple configurations identifies $SM=1.258$ as the economic optimum, yielding an annual solar fraction of 35%, a CO₂ reduction of 33.5%, a levelised cost of heat of 75.19 USD/MWh_th (16.3% below the fuel-oil baseline), and a payback period of 13.39 years under full accelerated depreciation. The system’s exergy efficiency (23–28%) is nearly four times that of the stand-alone boiler (6.31%); the analysis further quantifies diminishing returns beyond $SM\approx 1.4$ and demonstrates that México’s accelerated depreciation provision substantially broadens the economically feasible design space. These findings provide a replicable techno-exergo-economic framework for SHIP integration in gas-constrained, high-irradiation industrial regions, supporting decarbonisation efforts in emerging economies. Full article

Deep-sea transportation is faced with complex navigation environments, long voyages, limited emergency response resources, and interacting safety risks. Existing studies have mainly focused on individual risk factors, while the correlations and coupling effects among different factors have received insufficient attention. To identify the key risk factors affecting deep-sea transportation safety, this paper proposes a novel key factor identification model based on complex network theory. Firstly, 34 risk factors affecting deep-sea transportation safety are selected from five aspects using a literature analysis method. Secondly, a weighted directed network of risk factors is constructed based on complex network theory. Then, to evaluate the node importance, six node importance evaluation indicators are established, and a node importance evaluation method is proposed by integrating the analytic hierarchy process (AHP), technique for order preference by similarity to an ideal solution (TOPSIS), and gray relational analysis (GRA). Key risk factors are then determined according to the node importance evaluation results. Finally, the effectiveness of the proposed model is verified through a case study. The results show that the top five most critical risk factors are risk of leakage, emergency speed, physical and chemical properties of the cargoes, sense of personnel safety duty, and seasonal route. The findings can provide practical support for maritime authorities, shipping companies, and safety managers in formulating targeted prevention, control, and emergency response measures for deep-sea transportation safety. Full article

The rapid cryospheric transformation of the Arctic presents complex challenges for global supply chains, necessitating data-driven decision-making frameworks to optimize route planning and resource allocation. Standard aggregate statistics fail to capture the structural nuances required for operational research models in this evolving landscape. This study analyzes the spatiotemporal dynamics of Arctic navigation intensity to determine the extent of the operational window expansion and the spatial displacement of shipping routes. We deployed the Arctic Traffic Intensity Framework (ATIF) to generate a high-resolution spatiotemporal dataset spanning 2012–2024. To address variance instability and inform strategic forecasting, a log-linear regression model was applied to calculate the Annual Percentage Change, allowing for a dual analysis of absolute linear trends (volume) versus relative growth (proportional intensity) across heterogeneous baselines. A bilateral expansion of the high-intensity window to nearly five months (June–October) was observed, driven by earlier spring break-up and delayed autumn freeze-up. Spatially, the geometric navigational centroid has shifted southwestward, highlighting a concentration of activity in the Barents and Kara Seas rather than a uniform Transpolar dispersion. It can be concluded that the Arctic shipping system has transitioned from a seasonally restricted frontier to a standardized resource extraction corridor. However, the traffic is heavily clustered in the western sector, creating high-density logistic bottlenecks rather than a homogenized international transit route. Full article

Electric vehicle (EV) transport by ship is expanding beyond industrial logistics centred on automobile production, trade, and pure car and truck carriers (PCTCs) into daily transportation for island tourism, commuting, and essential mobility. According to Korea Maritime Transportation Safety Authority (KOMSA) vessel status data as of March 2026, 104 of 146 domestic passenger ships were car-ferry passenger ships, accounting for 71.2% of the fleet and operating on 75 of 99 designated routes nationwide. Korea Shipping Association (KSA) operational records show that the EV transport rate on these routes increased from 0.76% in 2024 to 1.21% in 2025, with some routes exceeding 2.0–4.7%. Unlike enclosed multi-deck PCTC vehicle spaces, Korean coastal car-ferry passenger ships generally have single-tier open vehicle decks and bow ramp gates. Crosswinds on open decks may reduce smoke detector activation probability by 60–75%. Although Article 97 of the Standard for Ship Fire-Fighting Appliance newly requires dedicated EV fire-fighting equipment for car-ferry ships, it remains primarily equipment-prescriptive and does not yet provide open-deck-specific performance requirements for wind-resistant detection, fixed EV-zone cooling, EV-designated stowage arrangements, or passenger–operator safety management obligations. This study applies the five-step International Maritime Organization (IMO) Formal Safety Assessment (FSA) procedure to support improvements to EV fire-fighting equipment standards for coastal car-ferry passenger ships. Hazard identification (HAZID) was conducted with a 15-member advisory panel, and probability elicitation was performed through a Delphi survey with 10 core experts, showing strong consensus (Kendall’s W = 0.74, p < 0.01). Fault tree analysis (FTA) and event tree analysis (ETA) probabilities were derived from the Delphi results and the international literature. H-07, representing wind-induced smoke dilution, was identified as the dominant single-point vulnerability within the detection-failure branch. Monte Carlo-based FTA–ETA analysis (n = 10,000) estimated annual fire frequencies of 5.9 × 10⁻², 1.8 × 10⁻¹, and 2.9 × 10⁻¹ yr⁻¹ at EV loading ratios of 10%, 30%, and 50%, respectively, with 2.47 expected fatalities per fire. Risk entered the IMO ALARP band above a 30% EV loading ratio and exceeded the maximum tolerable crew risk above 50%. The combined application of risk control options (RCOs) 2, 3, and 4 reduced annual expected fatalities by 85.6%. Based on these results, six RCOs and institutional recommendations are proposed, including strengthened safety management obligations for passenger ship operators. Full article

Battery-based electrification is increasingly recognised as a key pathway for reducing greenhouse-gas emissions in maritime transport, particularly for vessel segments characterised with short, predictable operation profiles. To ensure an environmentally sustainable transition, it is essential to quantify the potential environmental benefits of these solutions. Life Cycle Assessment (LCA), standardised by ISO 14040 and ISO 14044, is the internationally recognised methodology for evaluating environmental impacts across the entire life cycle and for consistently comparing options providing the same function. This study presents a methodological review of LCA applications to battery-based ship electrification, with the objective of analysing key assumptions, comparability issues, and limitations across the existing literature. A systematic review was conducted on 24 studies, focusing on core methodological aspects, including product system definition, functional unit selection, system boundaries, life cycle inventory modelling, and impact assessment methods, while considering contextual elements such as fleet segmentation and propulsion configurations to support the interpretation of methodological choices. The analysis reveals significant methodological heterogeneity across studies, particularly in product-system definitions, functional unit selection, modelling detail, and impact category coverage, which limits cross-study comparability. This review also highlights a strong concentration of applications on short-route passenger ferries, while other vessel categories remain underrepresented, further constraining the generalisability of the findings. Although a direct quantitative comparison of results is not methodologically appropriate due to this heterogeneity, climate change mitigation consistently emerges as a key benefit across the analysed studies. At the same time, the multi-impact perspective of LCA highlights relevant trade-offs related to material use, toxicity, and resource depletion. Overall, the findings underline the need for more harmonised methodological approaches and a holistic life cycle perspective to support robust and comparable environmental assessments as battery-based solutions expand within the maritime sector. This review provides a structured interpretation of methodological variability and identifies priorities for future LCA applications. Full article

As sea ice recedes, the strategic importance of Arctic shipping routes has intensified, yet the complex polar environment poses severe challenges to navigational safety. Through a systematic search of the Scopus database, relevant key studies in both English and Chinese were identified and selected based on predefined inclusion criteria for in-depth review. The present study establishes a systematic categorization framework to parse existing research on Arctic navigational risk assessment. It structurally analyzes the literature across three core dimensions: sea ice characteristics, accident statistical analysis, and risk modeling methodologies. Addressing current limitations in data sparsity, factor coupling, and dynamic forecasting, this study proposes that future research should focus on the construction of structural models for risk interdependencies, multi-source data-driven environmental risk learning, and intelligent small-sample assessment based on Case-Based Reasoning (CBR), which extracts effective risk solutions from limited historical samples by interpreting past navigational successes and failures to improve decision quality. This review aims to provide a comprehensive reference for developing a systematic and intelligent risk assessment architecture for Arctic shipping. Full article

Low-visibility environments induced by sea fog severely constrain the navigational efficiency and safety in narrow waterways, where traditional radar and Automatic Identification Systems (AIS) frequently encounter challenges such as perception blind spots and information lag. To address this critical issue, this study proposes a UAV-based perception and decision-making methodology for main navigational routes in fog, integrating physical priors with unmanned aerial vehicle (UAV) vision. Firstly, a joint physical dehazing and fog-domain adaptive detection network is constructed. This network addresses the overcomes the interference of non-uniform fog through feature-level enhancement, generating a spatio-temporally continuous visibility field and ship probability grids under a bird’s-eye view (BEV). Subsequently, a quantified “Sailability Score” model is established, providing a scientific basis for the dynamic diversion, speed limitation, and safe distance maintenance of main navigational routes. Simulation-based verifications using real-world fog navigation scenarios in the Qiongzhou Strait, coupled with a joint analysis of Vessel Traffic Service (VTS) and AIS data, suggest that at the critical visibility threshold (≤500 m), the proposed method improves the recall rate of long-distance small target detection by approximately 16.2% and reduces the visibility estimation error by 19.3%. Furthermore, the consistency between the proposed Sailability Score and the actual VTS navigation restriction windows reaches 82.1%, exhibiting a conservative preference for safety (i.e., risk preference ratio $\gamma >1$). Additionally, by introducing a temporal anti-jitter mechanism (parameterized by a smoothing window $\Delta t$), the proposed method extends the navigable time window of the main routes by approximately 12.4% while ensuring navigational safety. The simulation results indicate the framework’s potential perception capabilities and engineering applicability, providing reliable technical support for smart shipping and intelligent VTS systems. Full article

Solid oxide fuel cells (SOFCs) are a promising near-zero-emission propulsion source for Northern Sea Route (NSR) vessels, but their yttria-stabilized zirconia (YSZ) electrolyte and Ni-cermet anode are susceptible to thermomechanical degradation under repetitive start–stop thermal cycling. We develop a hierarchical Bayesian competing-risk framework built on a dual degradation model that decomposes area-specific resistance (ASR) growth into cycle-induced fatigue and time-dependent electrochemical aging and apply it across six NSR duty-cycle scenarios spanning f = 1–27 cycles/month. Posterior inference via the No-U-Turn Sampler (NUTS) yields 17 estimated parameters meeting standard convergence criteria (R^ ≤ 1.01, ESS_bulk ≥ 479, zero divergent transitions). The analysis identifies a failure-mode transition at f ≈ 3–6 cycles/month: high-frequency routes are crack-dominated (S1a: 10/15 cells fail by crack within the 600-cycle window with 5/15 right-censored), whereas low-frequency routes are ASR-dominated (S3b: 100% ASR). Global sensitivity analysis indicates the time-dependent rate coefficient k_time as the primary remaining-useful-life driver (S_T = 0.37–0.46). Cycle-based maintenance thresholds span 160 cycles (S3b) to ≥600 cycles (S2b), bracketed by S1a (270 cycles, 10.0 months, crack-dominant) and S3a (480 cycles, 160 months, transition regime); qualitative consistency with published experimental data supports physical plausibility. Full article

The Gulf of Mexico and the Caribbean Sea are key regions of the western Atlantic, where sea-state conditions are critical for coastal safety and offshore operations. This study analyzes wave climate trends (1981–2022) using WAVEWATCH III simulations validated against buoy observations. The Mann–Kendall test and Theil–Sen estimator were employed to quantify trends in significant wave height (Hs), energy period (Te), and wave power (P), while correlation analysis was performed to explore teleconnections with the Oceanic Niño Index (ONI), Atlantic Multidecadal Oscillation (AMO), and North Atlantic Oscillation (NAO). The results reveal basin-wide increases in mean Hs and P, characterized by pronounced spatial and seasonal heterogeneity. The most robust positive trends occur during winter and spring; in summer and fall, the weaker or negative tendencies, particularly in Te, suggest an intensification of seasonal contrasts rather than uniform change. Teleconnection analysis demonstrates that, among the climate indices considered in this study, ENSO is the primary driver of interannual wave variability in the Caribbean, particularly modulating wave power through remotely generated swell. While the NAO exerts regionally dependent control associated with storm-track modulation, the AMO plays a secondary role, affecting swell-dominated sectors. In contrast, the Gulf of Mexico shows limited sensitivity to large-scale climate modes, with wave variability largely governed by local wind–sea processes. These findings highlight the contrasting wave dynamics between these two basins, providing critical insights for coastal hazard assessments, maritime traffic along major shipping routes, oil spill management, and regional wave energy planning. Full article

With the formal inclusion of the shipping industry in the European Union Emissions Trading System (EU ETS), the speed optimization of ocean-going container ships must simultaneously balance operating costs, incorporating carbon emission costs and shipper satisfaction with transportation timeliness. Taking ocean-going container liner routes as the research object, this paper establishes a ship navigation resistance model based on meteorological and hydrological conditions, and constructs a route segmentation mechanism and a ship fuel consumption model on this basis. The spatially differentiated carbon accounting rules of the EU ETS are introduced, a fuzzy membership function is adopted to quantify shipper satisfaction, and a Q-learning-based solution algorithm for ship speed optimization that balances operating costs and shipper satisfaction is designed. Numerical experiments on a 20,150 Twenty-foot Equivalent Unit (TEU) container ship demonstrate that the proposed framework reduces total operating costs by 5.56%, EU ETS carbon compliance costs by 18.72%, and total voyage carbon emissions by 11.01% compared with the conventional constant-speed strategy. Meanwhile, the algorithm can spontaneously form an optimal speed strategy adapted to meteorological conditions and policy rules. Through parameter sensitivity analysis, this paper further extracts management implications for liner-operating companies. Full article

Maritime transport is under increasing pressure to cut greenhouse gas and pollutant emissions to meet global decarbonization goals and tighter environmental standards. Ship electric propulsion systems offer a promising solution for short-range maritime operations, particularly for small vessels and coastal activities. Full-electric vessels can significantly reduce operational emissions; however, a key challenge is the extensive charging time for onboard energy storage, which can affect operational continuity and logistical efficiency. This study examines mission planning and energy management for a hybrid multi-source electric mail boat operating in the Aeolian archipelago. It evaluates the viability and performance of a daily inter-island route powered by a high-temperature methanol fuel cell, batteries, and photovoltaic panels. A routing and simulation framework was developed to model the boat’s itinerary among seven islands, accounting for realistic navigation speeds, scheduled stops, solar energy availability, and battery state-of-charge constraints. The study analyzes distance, travel time, energy consumption, solar power generation, and fuel–electric usage with high temporal resolution, enabling detailed analysis of power flows during sailing and docking. Several operational strategies were assessed, including periods of increased speed supported by battery assistance and fuel–electric cell output, combined with coordinated energy management to keep battery levels above a lower acceptable threshold while completing the route in a single day. The methodology provides a practical tool for planning low-emission island networks and supports the integration of innovative energy systems into small electric workboats operating in specific maritime regions. Full article