Search Results (1,216)

This study analyzes the econometric correlation between resale prices and CO₂ emissions of 832 bulk carriers sold from 2018 to 2025. It uses a cross-sectional hedonic pricing model to look at how environmental performance affects the value of sub-types of dry bulk vessels (Capesize, Panamax, Supramax, and Handysize) and age groups (0–5, 6–10, 11–15, and 16+). The findings show that emission efficiency has a statistically significant and negative effect on second-hand prices for all models. Results indicate that higher emission intensity (higher technical efficiency values) reduces vessel values. The magnitude of this effect varies by ship type and age group. Based on the Technical Efficiency Indicator (TEI), refers to Energy Efficiency Existing Ship Index (EEXI) or Energy Efficiency Design Index (EEDI) coefficients, the Supramax segment appears to be the most price-sensitive, followed by Panamax, Capesize, and Handysize. Age has a consistently negative and significant effect on prices, while vessel size positively affects asset values. Further analysis shows that TEI levels increase with vessel age, whereas they decrease with larger vessel size and more recent measurement years. These results are consistent with tightening regulatory pressures under the International Maritime Organization (IMO) frameworks. The economic implications of IMO’s environmental regulations on carbon intensity indicate that compliance with regulation standards creates a measurable price differential in the second-hand ship market. These findings have important implications for shipowners’ investment strategies, regulatory policy design, and the decarbonization path of the maritime sector. This study contributes to the growing research on environmental economics in maritime transport by providing empirical evidence on how carbon regulations translate into tangible asset value impacts. Full article

$Background$: In the grain logistics context, pre-processing operations such as reception, pre-cleaning, drying, storage, and shipping are performed at farm, collecting, intermediate, sub-terminal, and terminal storage units to preserve quality, reduce losses, and add value in the products. However, high transportation costs and limited static storage capacity reduce the selling prices. The objective of this article is to maximize profit associated with pre-processing, storage, and transportation along the grain flow in Brazil. $Methods$: A generic post-harvest logistics network is represented as a graph connecting producers, multi-level storage units, agribusiness facilities, and ports. A multi-period, multi-level mathematical model is applied in a case study framework explored in three scenarios, covering pre-cleaning, drying, storage, and transportation costs from production areas to commercialization nodes. $Results$: In all three scenarios, road transport resulted in transportation costs ranging from approximately US$ 49 million to US$ 492 million, mainly over long distances. $Conclusions$: The location and static capacity of collecting and intermediate storage units strongly influenced transport, storage use, CO₂ emissions, and post-harvest efficiency. Also, the flow concentration increased heavy-vehicle traffic, reducing overall logistics performance. 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

Shore-side electricity (SSE) is an effective approach to reduce the emissions of greenhouse gas (GHG) and air pollutants from at-berth ships. Governments are using subsidies to incentivize ports and vessels to use SSE. However, its utilization remains limited. This paper targets the problem of government subsidy optimization considering games between the government and ports. A two-stage tripartite game model and four subsidy scenarios are proposed to investigate the interactions between the government and two ports. The results show that the choice of subsidy recipients does not affect the overall effectiveness of the subsidies. The optimal unit subsidy should be linked to the environmental benefits of GHG reduction, electricity prices, and fuel oil prices. Port competition can further enhance SSE utilization and environmental performance. Thus, policies should encourage such competition. Furthermore, analysis indicates that the cost of enhancing SSE quality is a key factor affecting SSE performance. Based on the analytical findings, this study offers policy recommendations for designing effective subsidy schemes. Full article

As critical conduits for pollutant enrichment and transformation, lake inlets govern the biogeochemical cycling of emerging contaminants. This study investigated the occurrence, spatiotemporal heterogeneity, and source–sink dynamics of 15 organophosphate esters (OPEs) in the major inflowing rivers of Poyang Lake, China. Using UPLC–MS/MS, positive matrix factorization (PMF), and risk quotient (RQ) modeling, we identified the mechanisms driving pollutant distribution across three hydrological periods. Alkyl-OPEs (58.19%) and chlorinated OPEs (40.42%) dominated the contaminant burden, with TCPP and TEP identified as the primary congeners. Concentrations exhibited a distinct seasonal gradient, with higher levels during the dry season and lower levels during the wet season, controlled by seasonal hydrological dilution versus evaporative and stagnant accumulation. PMF indicated that source contributions shifted with hydrology: intense wet-season precipitation flushed non-point sources from waste and electronic products (45.1%), while reduced dry-season flow concentrated mixed inputs from agricultural runoff and ship traffic (50.7%). Ecological risk assessment identified EHDPP, TCrP, and TCPP as high-risk contaminants (RQ ≥ 1.0), posing direct threats to aquatic population. These findings highlight the need for adaptive, season-specific management of emerging contaminants at the river–lake interface, specifically by implementing enhanced interception of surface runoff during the wet season and enforcing stringent regulations on localized shipping emissions during the dry season to protect freshwater ecosystems. Full article

Cruise ships and superyachts have experienced significant global expansion throughout the 21st century. Although the growth in cruise passenger numbers was temporarily disrupted by the COVID-19 pandemic, occupancy rates have since rebounded and even exceeded pre-pandemic levels. This study highlights the significant environmental impact of cruise ships and luxury yachts, particularly in terms of air emissions and marine pollution. Emission levels associated with different fuel types and marine engines are analysed, including the average emissions generated by the Norwegian Cruise Line fleet while docked in ports, as well as the estimated emission reductions achievable through the implementation of onshore power supply systems. To identify environmentally preferable fuel options, a hybrid ANN/MCDM framework is applied. The weighting coefficients of eight evaluation criteria are determined using the Artificial Neural Network/Extreme Learning Machine (ANN/ELM) model, ensuring an objective and data-driven assessment of their relative importance. The ANN/ELM model was trained using emission and fuel-related data collected from the literature and industry reports, and its performance was validated using standard validation procedures, achieving satisfactory predictive accuracy for determining the weighting coefficients. The final ranking of eight fuel alternatives is subsequently performed using the Ranking Alternatives by Weighting of Evaluated Criteria (RAWEC) method. The considered alternatives include conventional and emerging marine fuels currently used in practice or under technological development (A₁–A₈), while the optimization criteria (C₁–C₈) encompass major air pollutants (CO₂, NOx, SOx, CO, PM, CH₄), the fuel cost-to-consumption ratio, and the potential impact on water pollution. The water pollution criterion is assessed qualitatively using the Saaty scale. The integrated ANN/ELM–RAWEC approach enables a systematic comparison of marine fuels and supports the identification of options with the lowest overall environmental impact. Full article

This paper presents a novel Multi-Scale Temporal Uncertainty-aware Hierarchical Adaptive Ensemble (MSTU-HAE) algorithm for intelligent ship emission monitoring and prediction in maritime environmental compliance applications. The maritime shipping industry contributes approximately 3% of global CO₂ emissions and significant amounts of nitrogen oxides and sulfur oxides, necessitating advanced predictive monitoring systems. The proposed MSTU-HAE algorithm integrates three key innovations: multi-scale temporal feature extraction using causal convolutions at short-term (5 samples), medium-term (20 samples), and long-term (60 samples) windows; gas-specific attention mechanisms that automatically weight temporal scales based on individual emission gas characteristics; and three-level hierarchical uncertainty quantification encompassing individual model uncertainty, ensemble disagreement, and regulatory compliance risk assessment. Experimental validation was conducted using emission data collected from a fishing vessel over 3 operational days (1732 original samples), augmented to 17,320 samples via controlled replication with noise injection to support model training. Rigorous temporal data splitting with 70%/15%/15% train/validation/test partitioning ensures no data leakage. Comparative analysis against six baseline methods (XGBoost, LSBoost, AdaBoost, Ridge Regression, Random Forest, and K-Nearest Neighbors) demonstrates that MSTU-HAE achieves superior average performance, with R² = 0.9670 and NSE = 0.9670 across all emission gases. This research contributes a robust, interpretable, and scalable prediction framework that advances the state of the art in maritime environmental monitoring through novel algorithmic innovations in temporal feature learning and uncertainty quantification. Full article

This study develops an integrated vessel-level framework for assessing logistics performance and operational energy efficiency in container shipping. The novelty of the study lies in the development of a unified analytical approach that explicitly integrates logistics indicators with fuel consumption and emissions within a consistent system boundary, including auxiliary engine operation during both sea passages and port stays. The framework is applied to four medium-sized container vessels (6000–7500 TEU; 20-foot equivalent unit) under normalised operating conditions. The results show that higher capacity utilisation and economies of scale significantly improve both cost and energy performance, while emissions intensity varies by more than twofold across vessels. A deterministic sensitivity analysis is applied to evaluate the influence of key operational parameters. The analysis identifies service speed as the dominant driver, followed by vessel loading rate, while port-related parameters—such as auxiliary engine load and port productivity—have a lower yet still measurable influence, reducing emissions by up to 5% under improved conditions. The main contribution of the study is the development of a practical vessel-level benchmarking tool that captures logistics–energy interactions and supports operational decision-making under current regulatory frameworks, including EU ETS, FuelEU Maritime, and the IMO Carbon Intensity Indicator (CII). Full article

With increasingly stringent greenhouse gas emission regulations in the shipping industry, there is an urgent need for an efficient energy management strategy for new energy ship power systems. However, existing dispatch models often overlook the dynamic energy-saving potential of active drag reduction technologies and lack effective optimization algorithms capable of handling high-dimensional, multi-constrained problems. To address these problems, this paper proposes a novel integrated dispatch framework for hybrid energy ship power systems that incorporates air lubrication systems. First, a unified multi-energy dispatch model is established, coupling the dynamic operation of air lubrication systems with electrical, thermal, and propulsion energy flows. Second, an Improved Traffic Jam Optimizer algorithm is proposed, which enhances global exploration and local exploitation through a nonlinear parameter adaptation mechanism, differential mutation strategy, and dynamic hybrid search architecture. Convergence analysis based on Markov chain theory is provided to guarantee algorithmic reliability. Simulation results demonstrate that the proposed algorithm outperforms existing methods in terms of convergence speed, solution accuracy, and stability. Furthermore, integrating air lubrication systems into the ship power system reduces total operating costs and greenhouse gas emissions by up to 20.569% and 6.310%, respectively. Full article

To address ship-sourced water pollutant issues resulting from shipping industry growth and achieve precise supervision and effective management in coastal ports, this study develops a method for calculating and predicting the generation volume of oily sewage, domestic sewage and solid waste based on Automatic Identification System (AIS) data. First, a questionnaire survey (“Survey on Ship Water Pollutants”) is designed and implemented. Through analysis of questionnaire data, the ranges of values for the generation of oily sewage, domestic sewage, and solid waste from different ship types at China’s coastal ports are established. Additionally, onboard sampling is conducted to determine average emission factors for domestic sewage and oily sewage from typical ship types. Second, ship activities are derived from AIS data and combined with the established generation volume ranges for spatiotemporal calculation. Finally, a ConvLSTM (Convolutional Long Short-Term Memory) model is developed to predict the generation volume of water pollutant based on their spatiotemporal characteristics. Taking a major Chinese port area as a case study, the results indicate that pollutant generation volumes are significant in coastal port zones and main navigation channels, particularly between 15:00 and 16:00. chemical oxygen demand (COD), suspended solids (SS), and 5-day biochemical oxygen demand (BOD₅) levels in domestic sewage exceeded China’s national regulatory limits by 0.35 times, 2.88 times and 1.07 times, respectively, which can easily lead to a decrease in dissolved oxygen content in the water, affecting the respiration and survival of aquatic organisms. Petroleum content in oily sewage remained below the standard threshold. For pollutant generation volume prediction, the proposed ConvLSTM model achieved MAE and RMSE values of 0.0824 and 0.1433, respectively, outperforming other prediction models such as LSTM and CNN-LSTM. This research provides technical support for the prevention and control of water pollution from ships in coastal ports. The proposed AIS-driven framework and ConvLSTM prediction method are transferable and globally applicable, offering a reference for the environmental sustainability of port ecosystems, the global maritime pollution prevention, and the sustainable development of the shipping industry worldwide. Full article

Small and medium-sized ports are currently underutilised within supply and logistics chains, yet many can be successfully integrated through optimisation. A significant share is located near large cities and industrial zones, a situation that can be exploited not only to make better use of the ports themselves but also to develop nearby cities and regions. The “integration” of small and medium-sized ports into the Motorways of the Sea (MoS) system encompasses technical, technological, organisational, and legal aspects. This article primarily analyses the adaptation of small and medium-sized ports to the MoS objectives from a technical and technological perspective. The adaptation of the technical capabilities of small and medium-sized ports, linking them with major ports, focuses on bypassing “overloading” in land transport systems, optimising the costs of transporting goods by up to 25–30%, and reducing environmental impact compared with road transport by up to 50%. The article presents a mathematical model for adapting small and medium-sized ports to the MoS system, assessing the cost of cargo transportation, the reduction in environmental impact, and the technical and technological utilisation of these ports. Full article

With the accelerated transformation of green shipping and the advancement of ship electrification, lithium-ion batteries have become the core solution for ship propulsion due to their advantages of high energy density and zero emission. Efficient thermal management serves as a key technical support to ensure the safe and stable operation of batteries, extend their service life, and mitigate the risk of thermal runaway. Lithium-ion batteries accumulate heat during discharge, and pure phase change material (PCM) cooling systems are limited by low thermal conductivity, leading to excessive battery temperature rise and poor temperature uniformity. To address this problem, RT42 (a paraffin-based PCM with a melting temperature range of 311.15–316.15 K) was selected as the PCM in this study. The battery thermal management system (BTMS) coupling RT42 with a three-dimensional fin network structure was designed. Numerical simulations were conducted via ANSYS Fluent, and the enthalpy-porosity method was adopted to simulate the PCM phase change process. The effects of fin distribution, spacing and layer number on BTMS performance were systematically investigated and compared. Results show that the heat transfer process in the PCM can be significantly improved due to the three-dimensional fin network, and the battery maximum temperature can be reduced by 7.53 K compared with the pure PCM system. This study provides theoretical support for the design and optimization of high-efficiency BTMS. Full article

Carbon emission regulations and customers’ green preferences require ports and shipping companies to develop green services, but green investments entail significant costs. Vertical alliance cooperation between ports and shipping companies through sharing costs can address this issue. Most studies use non-cooperative game to analyze the competitive relationship between ports and shipping companies. Although such research can capture price competition, they struggle to address the distribution of cooperative benefits within an alliance. They also fail to simultaneously reflect the coexistence of competition and cooperation. So, we constructed a non-cooperative–cooperative biform game to analyze green investment under vertical alliance. In the non-cooperative stage, the model captures vertical price competition between ports and shipping companies, as well as horizontal competition among supply chains. In the cooperative stage, the Shapley value is used to allocate the coalition profits from green investment cooperation. The results indicate that alliance cooperation can promote the green development of shipping. Moderate green competition can promote the green development of shipping. Route substitution competition will increase service prices and green investment level and reduce the cost-sharing ratio for shipping companies. Port congestion prompts ports to increase green investment level. These findings offer references for the green collaborative development of ports and shipping companies across different countries, thereby enriching the research framework for global sustainable development in shipping. Full article

In recent decades, cruise tourism has emerged as a key economic driver for port cities, while simultaneously intensifying environmental pressures and socio-spatial inequalities. Despite growing scholarly attention, research exploring how these pressures are distributed within urban contexts and how they interact with pre-existing vulnerability patterns remains scarce. This study addresses this gap by proposing a GIS-based integrated methodological framework, the Port-city Risk Integrated Spatial Method (PRISM), applied to the Mediterranean port city of Malaga, Spain. The approach combines socio-demographic indicators and data related to spatial amenities with environmental pressures from cruise ship emissions to construct an Urban Socio-Environmental Complexity Index. Emission scenarios for peak cruise days were estimated using a bottom-up methodology and spatialized through atmospheric dispersion modeling, enabling their integration with exposure, vulnerability, and urban capacity indicators. The results reveal marked intra-urban heterogeneity and highlight the emergence of cumulative risk hotspots in areas adjacent to the port and along prevailing inland dispersion corridors. This study demonstrates the potential of integrated spatial indices as decision support tools for urban planning, offering a replicable framework for other port cities facing similar tourism-driven transformations. Full article