Search Results (407)

Against the backdrop of the dual-carbon strategy promoting the green and low-carbon transformation of the shipping industry, pollutant emissions generated during vessel berthing operations have become a critical challenge in port environmental governance. To address the combined effects of the priority berthing policy for new energy vessels and time-of-use electricity pricing, a joint optimization model for berth and shore power allocation is developed with the objectives of minimizing the total economic cost of vessels and the environmental tax cost associated with pollutant emissions. An improved Adaptive Large Neighborhood Search algorithm (ALNS-II) is further designed to solve the model. Numerical experiments based on actual port data verify the effectiveness of the proposed model and the superiority of the algorithm. The results indicate that, under time-of-use electricity pricing, the priority berthing policy for new energy vessels can shorten their waiting time at anchorage and encourage fuel-powered vessels to shift toward electrification. When the peak-to-valley electricity price ratio increases from 4.1:1 to 7.5:1, the environmental tax cost of pollutant emissions decreases slightly, whereas the total economic cost of vessels rises by 4.17%, suggesting that the peak-to-valley electricity price ratio should not be set excessively high. In addition, increasing the proportion of new energy vessels to 70% is more conducive to improving the overall economic and environmental performance of ports. The findings provide a theoretical basis and decision support for the optimal allocation of port resources under the coordination of multiple policies. Full article

Background: This study examines the systemic barriers constraining the development of India’s shipbuilding industry and identifies leverage points for effective policy intervention. Methods: A mixed-methods design was adopted, combining the Delphi technique with fuzzy DEMATEL to capture expert consensus and causal interdependencies among barriers. A panel of 20 experts, drawn from academia, the government, shipbuilding and ship repair, ports, logistics, and maritime consultancy, participated in two iterative Delphi rounds. An initial list of 21 barriers was refined to 10 based on convergence thresholds. These barriers were then analysed using a seven-step fuzzy DEMATEL procedure to distinguish causal drivers from dependent factors. Results: High raw material costs emerged as the most dominant causal barrier, with the highest net influence (R−C = 0.540), followed by high working capital requirements (R−C = 0.103) and complex regulatory frameworks (R−C = 0.275). Shortages of skilled labour, inefficiencies in ship design, and delays in clearances were largely effect-type barriers shaped by upstream structural conditions. Sensitivity analysis confirmed the stability of barrier rankings under alternative expert weighting scenarios. Conclusions: Policy efforts should prioritise reducing input cost disadvantages, strengthening long-term policy support, and rationalising regulatory processes, rather than focusing solely on downstream operational symptoms. The study is limited to expert judgement in the Indian shipbuilding sector. Future research could extend this framework to comparative country settings or integrate causal analysis with econometric evidence to further strengthen policy design. Contribution: Unlike prior thematic studies, this research provides an integrated causal mapping of structural, financial, and institutional barriers specific to Indian shipbuilding, enabling policy sequencing rather than simple ranking. Full article

Achieving sustainable maritime transport requires comprehensive understanding of port-related emissions and evidence-based mitigation strategies. Maritime shipping significantly contributes to air pollution in port cities, threatening environmental sustainability and public health, yet comprehensive emission inventories remain scarce for major ports in developing economies. This study presents the first bottom-up emission inventory for Ambarlı Port, Turkey’s largest container port, utilizing AIS data from Global Fishing Watch for calendar year 2025. Emissions of CO₂, NO_x, SO₂, PM₁₀, PM_2.5, CO, and NMVOC were quantified using EMEP/EEA activity-based methodology with IMO Tier II emission factors and vessel type-specific load factors (75% for passenger, 45% for cargo) from ENTEC guidelines. Non-commercial vessels (tugs, service craft, fishing vessels) and lay-up vessels exceeding six months continuous berthing were excluded to focus on active commercial shipping operations, resulting in a validated dataset of 10,267 port visits from commercial cargo, passenger, and bunker vessels. Annual emissions from active commercial vessels totaled 404,766 tonnes CO₂, 8487 tonnes NO_x, 6724 tonnes SO₂, 914 tonnes PM₁₀, and 849 tonnes PM_2.5. Passenger vessels dominated the inventory (93.3% of CO₂) due to high auxiliary power demands for hotel services and elevated load factors, while cargo vessels contributed 6.5% despite representing 61.4% of port visits. Turkish-flagged vessels accounted for the majority of domestic ferry traffic. These findings provide baseline data for air quality management in the Istanbul metropolitan area and support policy development regarding shore power implementation, with particular emphasis on reducing emissions from passenger vessels with extended berth times. From a policy perspective, prioritized shore power investment at passenger ferry terminals emerges as the most cost-effective emission reduction strategy, with potential to eliminate over 90% of port-related air pollutant emissions through public-private partnership models. Full article

Collaborative decarbonization between ports and shipping companies is critical to the low-carbon transition of maritime supply chains. Driven by the new energy transition, vertical technology spillovers have become a key force shaping vertical collaborative emission reduction. However, the mechanisms through which spillovers affect strategic interactions remain unclear, the theoretical basis for emission reduction strategies is insufficient, and practical issues such as benefit sharing and coordination mechanisms are underexplored. To fill these gaps, this study makes three contributions. Theoretically, we incorporate vertical technology spillovers and joint benefit–cost sharing into the port–shipping collaborative emission reduction framework, enriching supply-chain-level spillover theory. Methodologically, we combine an evolutionary game model with a scale-free network to simulate strategy diffusion and conduct scenario comparisons, linking theoretical modeling with industrial practice. Empirically, we confirm that ports act as leaders in collaborative decarbonization, and port-centered resource allocation drives the systemic low-carbon transition of the maritime sector. The findings show that the share of agents adopting active emission reduction strategies first rises and then falls with vertical technology spillover intensity, peaking at a moderate level. The impacts of core factors vary significantly across spillover scenarios. Port-centered resource allocation and benefit distribution are crucial to improving overall participation willingness. Ports are not merely participants but irreplaceable coordinators in the maritime supply chain. These results provide targeted policy and practical guidance for ports and shipping companies to promote global green and low-carbon maritime development. Full article

The liner shipping industry is thriving in the low-carbon transition, and optimizing operational strategies for liquefied natural gas (LNG) dual-fuel ships has become a research hotspot. This research examines the impacts of the carbon tax, emission control area (ECA) policies, fuel price discounts and methane slip rate on fuel management strategies. Firstly, to reduce liner operating costs and adhere to ECA policies, this study develops a basic optimization model. Further, the model is extended to take into account the impact of fuel price discounts. Secondly, by linearizing multiple nonlinear terms, the operational strategies are obtained. Thirdly, taking a real vessel sailing between the Far East and Northwest Europe as a case study, this study identifies the ports for LNG and very low sulfur fuel oil (VLSFO) bunkering, determines the bunkering amounts and calculates the planned speeds. Furthermore, sensitivity analyses are conducted on fuel price difference, carbon tax rate and methane slip rate. Results show that fuel price difference, carbon tax rate, methane slip rate and fuel price discount exert a significant impact on ship operational decisions. To ensure the effectiveness of maritime decarbonization regulations, authorities should monitor ship engines with high methane slip rates. This study offers important references for shipping enterprises to meet ship emission policies and simultaneously cut operational costs. Full article

This paper proposes a physics-informed hybrid digital CO₂ emission-control technology for maritime transport, designed for adaptive ship speed optimization along a predefined geographical route between two ports, discretized into quasi-stationary segments and evaluated under forecasted metocean conditions, subject to economic and regulatory constraints associated with maritime decarbonization. The framework integrates two exact optimization methods, Backtracking (BT) and Dynamic Programming (DP), with a reinforcement learning approach based on Proximal Policy Optimization (PPO), operating on a unified physical, economic, and regulatory modeling core. By reducing propulsion fuel demand, the system acts as an upstream CO₂ emission-control mechanism for ship propulsion. This operational stabilization of the engine load creates favourable boundary conditions for advanced combustion processes and reduces the volumetric flow of exhaust gas, thereby lowering the technical burden on potential post-combustion carbon capture systems. Segment-wise speed profiles are optimized subject to propulsion limits, Estimated Time of Arrival (ETA) feasibility, and regulatory constraints, including the Carbon Intensity Indicator (CII), the European Union Emissions Trading System (EU ETS) and FuelEU Maritime. The physics-based propulsion and energy model is validated using full-scale operational data from four real voyages of an oil/chemical tanker. A detailed case study on the Milazzo–Motril route demonstrates that adaptive speed optimization consistently outperforms conventional cruise operation. Exact optimization methods achieve voyage time reductions of approximately 10% and fuel and CO₂ emission reductions of about 9–10%. The reinforcement learning approach provides the best overall performance, reducing voyage time by approximately 15% and achieving fuel savings and CO₂ emission reductions of about 13%. At the route level, the Carbon Intensity Indicator is reduced by approximately 10% for the exact methods and by about 13% for PPO. Backtracking and Dynamic Programming converge to nearly identical globally optimal solutions within the discretized decision space, while PPO identifies solutions located on the most favourable region of the cost–time Pareto front. By benchmarking reinforcement learning against exact discrete solvers within a shared physics-informed structure, the proposed digital platform provides transparent validation of learning-based optimization and offers a scalable decision-support technology for pre-fixture evaluation of fixed-route voyages. The system enables quantitative assessment of CO₂ emissions, ETA feasibility, and regulatory exposure (CII, EU ETS, FuelEU Maritime penalties) prior to transport contracting, thereby supporting economically and environmentally informed operational decisions. Full article

Given the context of the COVID-19 pandemic disrupting global logistics, coupled with the Russia–Ukraine war causing global energy price changes, examining both the linear and nonlinear associations between shipping cost and oil price is crucial in a global context. This study empirically exhibits the association among Global Commodity Prices Index (GPI), Oil Price (OP), Gold Future Price (GFP), and Baltic Dry Index (BDI) by employing Linear Autoregressive Distributive Lag (ARDL) as well as Nonlinear Autoregressive Distributive Lag (Nonlinear ARDL) from January 2003 to January 2023. The findings indicate that the influence of OP on BDI has a negative impact in the long run and a positive impact in the short run. Furthermore, the OP has an asymmetric effect on BDI in both the long and short terms. Finally, the predictive performance of the NARDL model outperforms the ARDL model in forecasting OP and BDI. The empirical findings derived from the ARDL and NARDL algorithms offer valuable insights for policymakers in designing public policies and for investors in portfolio construction. Full article

Shore power (SP) is a critical solution for decarbonizing maritime transport, yet its adoption is hindered by the “high investment, low utilization” paradox, driven by high initial costs and misaligned incentives between ports and ships. While government subsidies are essential, traditional static policy designs often fail to adapt to the complex, non-linear dynamics of technology diffusion. To address this, the study proposes a dynamic evaluation framework combining System Dynamics (SD) with Evolutionary Game Theory (EGT), embedding a Rolling Horizon Optimization algorithm. Using Shanghai Port as a case study, simulation results demonstrate that optimal subsidies are highly state-dependent. Specifically, effective promotion requires prioritizing ship-side incentives during the early start-up phase, followed by facilities subsidies supporting the coordinated evolution of both ships and berths, and finally a market-driven exit. Furthermore, the proposed dynamic strategy demonstrates superior robustness against oil price volatility and demand shocks compared to static policies, while strictly complying with fiscal budget caps. This framework provides a foundation for the adaptive management of green port infrastructure, facilitating the advancement of energy-saving and environmental protection initiatives within the maritime industry. Additionally, it contributes to the forecasting and evaluation of the policy outcomes of green technology adoption. Full article

The maritime shipping industry faces the challenge of decarbonising its operations while maintaining economic viability. We present a comprehensive techno-economic review of four alternative energy carriers, liquid hydrogen (LH₂), ammonia (NH₃), liquefied natural gas (LNG), and methanol, evaluating their suitability for maritime applications within the context of global decarbonisation policy. Through the comparative assessment of physicochemical properties, hazard profiles, storage requirements, and regulatory compliance mechanisms, this review demonstrates that fuel selection is highly route-dependent, with methanol emerging as the most practical near-term solution for short-sea corridors, ammonia emerging as the primary pathway for long-term deep-sea decarbonisation, leveraging existing production infrastructure to achieve up to 90% lifecycle GHG reduction when produced from renewable hydrogen, and hydrogen serving as an alternative option pending cryogenic infrastructure maturation. The integration of digital twin technologies and port call optimisation provides a realistic pathway to achieving International Maritime Organisation (IMO) decarbonisation targets by 2030 and beyond. The findings are contextualised within current and emerging regulatory frameworks, including MARPOL Annex VI and FuelEU Maritime, to support evidence-based fuel selection and infrastructure investment decisions. Full article

This study proposes a health-aware energy management strategy based on the twin delayed deep deterministic policy gradient (TD3) algorithm for hybrid fuel cell/battery-powered ships. Unlike traditional approaches that treat multiple fuel cell stacks as homogeneous units, this strategy innovatively implements differentiated power allocation based on the real-time state of health of each stack. The research first validates the superiority of the TD3 framework over the deep Q-learning framework at the algorithmic level. Further comparative experiments conducted across three scenarios with varying degrees of state of health differences show that, compared to the TD3 baseline strategy employing average power allocation, the health-aware differentiated TD3 strategy significantly reduces the total voyage cost of the system, with the cost-saving effect becoming more pronounced as the state of health disparity between stacks increases. Additionally, by incorporating rule-based constraints, the convergence speed of the TD3 algorithm is effectively enhanced, improving its feasibility for real-time control. Tests under dynamic and fluctuating load conditions further confirm the strategy’s effectiveness and applicability. In summary, the health-aware TD3 strategy proposed in this study not only provides an efficient and reliable energy management solution for hybrid-powered ships but also promotes the application of machine learning in the field of ship energy management. Full article

This paper investigates the coordination between logistics and policy decisions for electric vehicle (EV) exports under the Belt and Road Initiative. Focusing on the two modes—maritime shipping and the China Railway Express (CR Express)—along with government production subsidies, import tariffs, and service premium, a Stackelberg game model for a cross-border supply chain comprising a domestic manufacturer and an overseas retailer is constructed. The equilibrium outcomes under four scenarios formed by combining subsidy policies and transportation modes (Models NM, NR, GM and GR) are compared theoretically and numerically, with further evaluation of capacity constraints and power structures, as well as the robustness verification of the core findings. Results show that the CR Express mode exhibits a service-driven nonlinear cost pattern, where its service premium amplifies positive market responses. Its appeal to the manufacturer, however, is tightly constrained by fixed cost. Furthermore, government subsidies can overcome this barrier by synergizing with the service premium, turning the CR Express into a relatively advantageous strategy. Moreover, subsidy efficacy is conditional, depending heavily on the service premium level and logistics cost coefficient, leading to a proposed differentiated subsidy framework. This study offers a theoretical basis for corporate logistics strategy and targeted policy design. Full article

This paper presents an MAUT-based decision-support framework, developed within the NAVGREEN project, to enable the evaluation of alternative fuels and technologies in shipping decarbonization pathways toward zero-emission targets. The framework integrates stakeholder-derived weights elicited through the Analytic Hierarchy Process (AHP) and systematically evaluates alternatives across five criteria: cost, technological maturity, safety and regulatory compatibility, carbon footprint, and social acceptability. Alternatives are mapped into a common utility space through criterion-specific utility functions and aggregated into a composite utility score, enabling transparent and reproducible comparison of single and combined solutions. To strengthen applicability beyond a single illustrative application, the study incorporates a structured scenario and sensitivity analyses (policy stringency, infrastructure constraints, conservative regulatory environments, and weight and parameter perturbations) to assess ranking stability under plausible future conditions. A case study on an Ultramax bulk carrier is used solely to demonstrate the operability and workflow of the method, rather than to empirically validate technology choices across all ship types. Optional AI-assisted elicitation may be used as a supporting aid to harmonize indicative inputs when data are incomplete; however, validation of AI-generated estimates is outside the scope of the present study and is identified as future work. Full article

The maritime transport sector is vital for global trade, yet it continues to be a significant source of air pollution in port cities due to its reliance on fossil fuels. This review summarizes empirical and epidemiological evidence on the emissions of Heavy Fuel Oil and transitional alternatives, such as Liquefied Natural Gas, with a focus on their contribution to local concentrations. Shipping-related emissions account for a substantial proportion of air pollution across multiple coastal urban regions, particularly during maneuvering and hoteling operations. The reviewed studies consistently associate these emissions with an increased risk of respiratory and cardiovascular morbidity and premature mortality among populations living near ports. While sulphur-focused regulations, notably IMO 2020, have achieved significant reductions in SO₂ emissions, the literature indicates that nitrogen oxides and fine particulate matter remain largely unmitigated. This review concludes that existing regulatory frameworks only partially address the health-related externalities of maritime transport. To address this market failure, the review argues for an integrated policy approach that combines market-based measures with port-level incentives and operational controls to reduce emissions at berth, thereby aligning shipping practices with public health objectives and the sustainable development goals. Full article

The promotion of shore power is a key pathway for reducing port-related emissions and achieving sustainable maritime development. This study analyzes the strategic interactions among governments, ports, and shipping companies by constructing a tripartite evolutionary game model. Specifically, it addresses three core questions: (1) how stakeholders’ initial intentions and strategic choices influence the system’s evolutionary path and eventual equilibrium; (2) how critical parameters—including subsidies for shore power infrastructure, wind turbine installation, and ship retrofitting, as well as electricity price support, carbon pricing, and policy implementation costs—shape the dynamics of the system and the equilibrium strategies of the three parties; and (3) how heterogeneity in national energy mixes, particularly the roles of wind turbine, affects decision-making behaviors across different countries. Simulation experiments are conducted to explore the effects of varying policy interventions and energy conditions on the stability of cooperative strategies. The results provide insights into the design of differentiated policy instruments that promote shore power adoption while accounting for the structural characteristics of national energy systems. This research enriches the theoretical application of evolutionary game theory to maritime sustainability and offers practical guidance for governments and stakeholders in advancing decarbonization in the port and shipping sectors. Full article

Star ratings alone are noisy, manipulable, and ignore aspect-level sentiment. We present Scrape2Repute, a compact and reproducible pipeline that ingests Yelp reviews under policy constraints; cleans and normalises text/metadata; learns a calibrated text sentiment per review; fuses stars and text via a tunable hybrid label; downweights suspicious reviews with unsupervised anomaly scoring; and aggregates evidence into a time-decayed business reputation with uncertainty bounds. The system is explainable (top-k rationales, aspect summaries), runs on commodity hardware, and ships with CLI/GUI. On the Yelp Open Dataset, we show strong predictive validity for forecasting future ratings and stable behaviour under sensitivity sweeps. We release implementation and an ethics checklist for compliant use. Full article