“Abstract

Background: Increasing regulatory pressure for maritime decarbonization (e.g., IMO CII, FuelEU) drives adoption of low-carbon fuels and prompts reassessment of regional ports’ competitiveness. This study aims to evaluate the economic and environmental viability of rerouting deep-sea container services to regional ports in a decarbonizing world. Methods: A scenario-based analysis is used to evaluate total costs and CO2 emissions across the entire container shipping supply chain, incorporating deep-sea shipping, port operations, feeder services, and inland rail/road transport. The Port of Liverpool serves as the primary case study for rerouting Asia–Europe services from major ports. Results: Analysis indicates Liverpool’s competitiveness improves with shipping lines’ slow steaming, growth in hinterland shipment volume, reductions in the emission factors of alternative low-carbon fuels, and an increased modal shift to rail matching that of competitor ports (e.g., Southampton). A dual-port strategy, rerouting services to call at both Liverpool and Southampton, shows potential for both economic and environmental benefits. Conclusions: The study concludes that rerouting deep-sea services to regional ports can offer cost and emission advantages under specific operational and market conditions. Findings on factors and conditions influencing competitiveness and the dual-port strategy provide insights for shippers, ports, shipping lines, logistics agents, and policymakers navigating maritime decarbonization.”

 

The full report is accessible via: https://doi.org/10.3390/logistics9030103

For related publications please see Resources – UK National Clean Maritime Research Hub

“Abstract

Persistent bottlenecks at container ports have significantly disrupted global supply chains, necessitating more efficient operations at seaports to address yard density and port congestion. An untapped but potentially critical approach to mitigating these challenges is to leverage container characteristics and machine learning to predict the out-terminals of containers upon their discharge from vessels. The predicted results can then guide the development of a more effective container storage strategy. To formulate such a strategy, this research developed a data-enabled methodological framework that integrates four key components: 1) Utilization of structured and unstructured data to enhance prediction accuracy. 2) Practice and knowledge-informed feature engineering to construct relevant features for the machine learning models. 3) Explanatory machine learning based classification models to understand the factors influencing terminal predictions. 4) Model-induced cost analysis to capture the monetary value of the prediction model including assessing the cost implications of misclassifications. An empirical study conducted at a seaport shows that our framework yields cost savings ranging from 14.90% to 30.45% compared to the Business-as-Usual scenario. Incorporating unstructured data as an additional feature in the machine learning models improves prediction performance by up to 6%. Moreover, integrating this framework into the existing operational system poses minimal risk and can be seamlessly executed. Additionally, the proposed methodological framework and its four components has broad applications beyond the shipping industry.”

 

The full report is accessible via: https://doi.org/10.1016/j.tre.2025.104331

For related publications please see Resources – UK National Clean Maritime Research Hub

“Abstract

Measures towards net-zero transition need to ensure the well-functioning of the market. This paper focuses on shipping where the existing environmental regulations lack considerations for the industry’s economic performance. We apply a stochastic frontier analysis to estimate the carbon, production, cost, and allocative efficiencies for 14 major shipping segments and 664 individual vessels. Our findings suggest that carbon and production efficiencies have increased but cost efficiency has decreased from 2021 to 2024. There is scope for the average vessel to reduce its carbon emissions by 31%. Additionally, fuel is underused by 37% and capital is overused by 58%. Technical and operational inefficiencies increase the total cost by 6%, with market price dynamics increasing it by 17%. The results suggest that, without further policy intervention and clear economic incentivisation, there is limited potential for the industry to follow the energy transition pathway.”

 

Shi, Yao and Moutzouris, Ioannis, The Economics of Decarbonisation Regulation: The Case of Shipping Efficiency (March 31, 2025). Available at SSRN: https://ssrn.com/abstract=5205272 or http://dx.doi.org/10.2139/ssrn.5205272

The full report is also accessible via: Page-48_56-CID-Summer-2025-IM-YS-061925.pdf

For related publications please see Resources – UK National Clean Maritime Research Hub

“Abstract

In 2020, the International Maritime Organization implemented a limit to the sulphur content emitted by vessels. To comply with it, a vessel should either incur the capital cost to be retrofitted with a scrubber or burn fuels that emit less sulphur but are more expensive. We examine this dilemma by developing a Vector Error Correction Model that links freight rates, fuel prices, and the green investment decision of scrubber installation. The results, across the tanker and dry bulk sectors from 2021 to 2024, suggest that the freight premium of scrubber-fitted vessels positively depends on the spread between very low-and high-sulphur fuel oil prices and negatively on the size of the scrubberfitted fleet. Scrubber investment, in turn, is determined by the past freight premium and the fuel spread. Being the first to investigate the interplay between green shipping investment and price uncertainty, our findings yield significant industry and policy implications.”

 

For related publications please see Resources – UK National Clean Maritime Research Hub