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Sustainability
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Sustainable Transport Planning: Reducing Emissions for a Greener Future
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Sustainable Transport Planning: Reducing Emissions for a Greener Future

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1680

Special Issue Editor

Dr. Hamad Al Jassmi

E-Mail Website
Guest Editor
Emirates Center for Mobility Research, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
Interests: traffic and crowds safety; infrastructure project lifecycle; AI and expert systems for mobility and infrastructure
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to provide a platform for researchers, policymakers, and stakeholders to present their latest research on sustainable transport planning, with a focus on reducing emissions and contributing to a greener future. High-quality research articles and reviews are welcome. This Issue seeks contributions that explore strategies, methodologies, and technologies to enhance sustainability in transportation, with a particular emphasis on minimizing environmental impact and improving efficiency. Papers on, but not limited to, the following topics are welcome:

  • Urban transport planning and emissions reduction;
  • Smart city initiatives for sustainable mobility;
  • Walking, cycling and micro-mobility integration;
  • Multi-modal transportation solutions;
  • Public transportation systems and sustainability;
  • Transit-oriented development;
  • Sustainable freight and logistics management;
  • Transportation policy and governance for sustainability;
  • Green infrastructure;
  • Low-emission vehicles;
  • Climate change mitigation in transport planning;
  • Emissions monitoring and reporting in transport systems.

This Special Issue aims to advance the field of sustainable transport planning by fostering discussions around emerging technologies, innovative practices, and policy frameworks that are essential to reducing emissions and enhancing environmental performance in the transportation sector.

Dr. Hamad Al Jassmi
Guest Editor

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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

  • urban transport planning
  • sustainable mobility
  • multi-modal transportation
  • low emission vehicles
  • green infrastructure

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Published Papers (3 papers)

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Research

32 pages, 3616 KiB  
Article
Can Urban Rail Transit in China Reduce Carbon Dioxide Emissions? An Investigation of the Resource Allocation Perspective
by Shengyan Xu, Yibo Chen and Miao Liu
Sustainability 2025, 17(9), 3901; https://doi.org/10.3390/su17093901 - 25 Apr 2025
Viewed by 361
Abstract
The construction of urban rail transit plays a crucial role in improving traffic conditions in large cities, promoting green urban development, and reducing carbon dioxide emissions. Based on Chinese urban data, this paper employs a time-varying difference-in-difference model combined with the Heckman two-step [...] Read more.
The construction of urban rail transit plays a crucial role in improving traffic conditions in large cities, promoting green urban development, and reducing carbon dioxide emissions. Based on Chinese urban data, this paper employs a time-varying difference-in-difference model combined with the Heckman two-step method to control the sample selection problem. The objective of this methodology is to ascertain whether urban rail transit exerts a traffic creation effect or a traffic substitution effect. The following results were found: (1) Urban rail transit notably reduces the bus ridership per capita and the carbon dioxide emissions per capita in cities, a finding which passes a series of robustness tests, and the traffic substitution effect increases as the number of urban rail transit lines increases. (2) Heterogeneity analysis reveals that the traffic substitution effect in terms of carbon reduction in urban rail transit is greater in non-resource-based cities, cities with large carbon emissions, and cities with low fiscal pressure. (3) Urban rail transit reduces the carbon dioxide emissions per capita by improving the allocation efficiency of factor resources and further generating technological innovation and structural upgrading effects. (4) Spatial econometric analysis shows that urban rail transit has a significant spatial spillover effect on the reduction in carbon dioxide emissions per capita in neighboring cities. In short, urban rail transit can reduce the carbon dioxide emissions per capita by improving resource allocation and support the attainment of carbon peak and carbon neutrality goals. This effect is greater in large cities where urban rail transit networks have been established. Therefore, cities should actively promote the construction of metro and other rail transit within the scope of urban financial resources and make full use of the carbon reduction and efficiency enhancement functions of urban rail transit. In this way, urban rail transit can become an effective tool for the realization of sustainable development. Full article
(This article belongs to the Special Issue Sustainable Transport Planning: Reducing Emissions for a Greener Future)
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30 pages, 4557 KiB  
Article
An Integrated Approach to Schedule Passenger Train Plans and Train Timetables Economically Under Fluctuating Passenger Demands
by Chang Han, Leishan Zhou, Zixi Bai, Wenqiang Zhao and Lu Yang
Sustainability 2025, 17(6), 2703; https://doi.org/10.3390/su17062703 - 18 Mar 2025
Viewed by 338
Abstract
High-speed railways (HSRs), with their advantages of safety, energy conservation, and convenience, are increasingly becoming the preferred mode of transportation. Railway operators schedule full-schedule timetables to operate as many trains and serve as many passengers as possible. However, due to the fluctuation in [...] Read more.
High-speed railways (HSRs), with their advantages of safety, energy conservation, and convenience, are increasingly becoming the preferred mode of transportation. Railway operators schedule full-schedule timetables to operate as many trains and serve as many passengers as possible. However, due to the fluctuation in passenger demands, it is not necessary to operate all trains in full-schedule timetable, which results in high operation costs and too much energy consumption. Based on this, we propose an integrated approach to schedule passenger train plans and train timetables by selecting trains to operate from the full-schedule timetable, adjusting their stopping scheme and operation sequence to reduce operation costs and energy consumption and contribute to sustainable development. In the scheduling process, both operation costs and passenger service quality are considered, and a two-objective model is established. An algorithm is designed based on Non-dominated Sorting Genetic Algorithms-II (NSGA-II) to solve the model, containing techniques for acceleration that utilize overtaking patterns, in which overtaking chromosomes are used to illustrate the train operation sequence, and parallel computing, in which the decoding process is computed in parallel. A set of Pareto fronts are obtained to offer a diverse set of results with different operation costs and passenger service quality. The model and algorithm are verified by cases based on the Beijing–Shanghai HSR line. The results indicate that compared to the full-schedule timetable, the operation costs under three sets of passenger demands decreased by 35.4%, 27.7%, and 15.7% on average. Compared to the genetic algorithm with weighting multiple objectives and NSGA-II without acceleration techniques, the algorithm proposed in this paper with the two acceleration techniques of utilizing overtaking patterns and parallel computing can significantly accelerate the solution process, with an average reduction of 42.9% and 38.3% in calculation time, indicating that the approach can handle the integrated scheduling problem economically and efficiently. Full article
(This article belongs to the Special Issue Sustainable Transport Planning: Reducing Emissions for a Greener Future)
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30 pages, 3530 KiB  
Article
A Hybrid Optimization Approach Combining Rolling Horizon with Deep-Learning-Embedded NSGA-II Algorithm for High-Speed Railway Train Rescheduling Under Interruption Conditions
by Wenqiang Zhao, Leishan Zhou and Chang Han
Sustainability 2025, 17(6), 2375; https://doi.org/10.3390/su17062375 - 8 Mar 2025
Viewed by 673
Abstract
This study discusses the issue of train rescheduling in high-speed railways (HSR) when unexpected interruptions occur. These interruptions can lead to delays, cancellations, and disruptions to passenger travel. An optimization model for train rescheduling under uncertain-duration interruptions is proposed. The model aims to [...] Read more.
This study discusses the issue of train rescheduling in high-speed railways (HSR) when unexpected interruptions occur. These interruptions can lead to delays, cancellations, and disruptions to passenger travel. An optimization model for train rescheduling under uncertain-duration interruptions is proposed. The model aims to minimize both the decline in passenger service quality and the total operating cost, thereby achieving sustainable rescheduling. Then, a hybrid optimization algorithm combining rolling horizon optimization with a deep-learning-embedded NSGA-II algorithm is introduced to solve this multi-objective problem. This hybrid algorithm combines the advantages of each single algorithm, significantly improving computational efficiency and solution quality, particularly in large-scale scenarios. Furthermore, a case study on the Beijing–Shanghai high-speed railway shows the effectiveness of the model and algorithm. The optimization rates are 16.27% for service quality and 15.58% for operational costs in the small-scale experiment. Compared to other single algorithms or algorithm combinations, the hybrid algorithm enhances computational efficiency by 26.21%, 15.73%, and 25.13%. Comparative analysis shows that the hybrid algorithm outperforms traditional methods in both optimization quality and computational efficiency, contributing to enhanced overall operational efficiency of the railway system and optimized resource utilization. The Pareto front analysis provides decision makers with a range of scheduling alternatives, offering flexibility in balancing service quality and cost. In conclusion, the proposed approach is highly applicable in real-world railway operations, especially under complex and uncertain conditions, as it not only reduces operational costs but also aligns railway operations with broader sustainability goals. Full article
(This article belongs to the Special Issue Sustainable Transport Planning: Reducing Emissions for a Greener Future)
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