Advancing Ocean Shipping: The Role of Vessel Trains in Enhancing Environmental Sustainability

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312).

Deadline for manuscript submissions: closed (31 August 2024) | Viewed by 697

Special Issue Editors


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Guest Editor
Maritime Intelligent Transportation Research Team, Department of Navigation College, Dalian Maritime University, Dalian, China
Interests: autonomous ship; traffic management; intelligent maritime supervision; traffic simulation
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Guest Editor
Navigation College, Dalian Maritime University, Dalian 116026, China
Interests: navigation and maritime technology; traffic safety and environment

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Guest Editor
School of Navigation, Wuhan University of Science and Technology, Wuhan, China
Interests: group ship intelligence mining and application; ship intelligence organization and scheduling; ship risk calculation and autonomous navigation

Special Issue Information

Dear Colleagues,

The maritime industry stands at a crossroads, facing significant challenges such as crew shortages, high carbon emissions, and the pressing need for sustainable and efficient transportation solutions. The concept of vessel trains, comprising a leader vessel followed by several follower vessels, presents a novel approach to addressing these issues.

In light of this background, a Special Issue (SI) is currently underway, entitled “Advancing Ocean Shipping: The Role of Vessel Trains in Environmental Sustainability", through the Journal of Marine Science and Engineering (JMSE) (https://www.mdpi.com/journal/jmse). This Special Issue seeks to explore the potential of vessel trains to revolutionize ocean shipping by reducing environmental impact and improving navigational safety.

The primary aim of this Special Issue is to gather and disseminate cutting-edge research on the application, challenges, and opportunities of vessel trains in the ocean shipping sector. It will focus on dynamic scheduling optimization and the environmental benefits of adopting vessel train technology. The Special Issue will provide a platform for multidisciplinary discussions, fostering innovation and collaboration among researchers and industry practitioners. Topics of interest include, but are not limited to, the following:

  • Organizational models and strategies for implementing vessel train operations;
  • Data-driven maritime traffic network extraction and analysis for vessel train routing;
  • Dynamic scheduling and decision-making models for vessel train operations under uncertainty;
  • Environmental impact assessments of vessel trains, focusing on carbon emissions and fuel consumption reduction;
  • Case studies on vessel train applications in major shipping routes, such as the Maritime Silk Road;
  • Technological advancements supporting vessel train operations, including autonomous navigation and AI-based scheduling.

Researchers are invited to submit original research articles, review articles, case studies, and technical reports that advance the understanding of vessel train technology in ocean shipping. Submissions should clearly articulate the research question, methodology, findings, and implications for practice and policy. Detailed submission instructions and manuscript formatting guidelines will be provided on the journal's website.

Dr. Mingyang Zhang
Prof. Dr. Xinyu Zhang
Dr. Xinjian Wang
Dr. Zhao Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • vessel train technology
  • environmental sustainability
  • ocean shipping

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Published Papers (1 paper)

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Research

14 pages, 6052 KiB  
Article
Exploring Carbon Emission Reduction in Inland Port Ship Based on a Multi-Scenario Model
by Chunhui Zhou, Wuao Tang, Zongyang Liu, Hongxun Huang, Liang Huang, Changshi Xiao and Lichuan Wu
J. Mar. Sci. Eng. 2024, 12(9), 1553; https://doi.org/10.3390/jmse12091553 - 5 Sep 2024
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Abstract
Assessing carbon emission reduction potential is vital for achieving carbon peak and neutrality in the maritime sector. In this study, we proposed a universal framework for assessing the effectiveness of different measures on carbon emission reduction from ships, including port and ship electrification [...] Read more.
Assessing carbon emission reduction potential is vital for achieving carbon peak and neutrality in the maritime sector. In this study, we proposed a universal framework for assessing the effectiveness of different measures on carbon emission reduction from ships, including port and ship electrification (PSE), ship speed optimization (SSO), and clean fuel substitution (CFS). Firstly, the projection method of future ship traffic flows and activity levels relies on a neural network, and the ARIMA model was proposed. Then, the potential of various emission reduction measures was detailed and analyzed under different intensity scenarios. The proposed model was applied to Wuhan port, the results indicate that CFS is the most effective for long-term decarbonization, potentially achieving a carbon peak by 2025 under an aggressive scenario. For the short to medium term, PSE is favored due to technical maturity. SSO primarily delays emissions growth, making it a suitable auxiliary measure. These findings guide emission reduction strategies for ports, fostering green and sustainable shipping development. Full article
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