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Sustainable Air Transport Operations and Planning: Digital Twin Pathways to Net-Zero Aviation

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

Deadline for manuscript submissions: 10 September 2026 | Viewed by 481

Editors


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Guest Editor
Centre for Digital and Design Engineering, Faculty of Engineering and Applied Sciences, Cranfield University, Cranfield MK43 0AL, UK
Interests: systems engineering; net-zero engineering; cost engineering; digital twins
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Centre for Digital and Design Engineering, Faculty of Engineering and Applied Sciences, Cranfield University, Cranfield MK43 0AL, UK
Interests: multi-agent and system-of-systems modelling and simulation; resilience engineering; decarbonisation systems engineering; digital twins

E-Mail Website
Guest Editor
Centre for Digital and Design Engineering, Faculty of Engineering and Applied Sciences, Cranfield University, Cranfield MK43 0AL, UK
Interests: machine learning; artificial intelligence; ontologies; digital twins

Special Issue Information

Dear Colleagues,

Achieving net-zero aviation requires more than cleaner fuels or efficient aircraft; it demands a digital transformation of the entire air transport ecosystem. Digital twins and their foundational layers, digital models and digital shadows, are emerging as critical enablers of this transition, enhancing system understanding, operational efficiency, and lifecycle optimisation across aircraft, airport, and airspace domains.

This Special Issue focuses on how digital technologies and data-driven systems engineering can accelerate the aviation sector’s path to net zero by integrating AI, IoT, cyber–physical systems (CPS), and real-time analytics into planning and operations. It seeks contributions that demonstrate how digital models support emission forecasting, scenario analysis, and strategic planning; how digital shadows enable right-time performance, energy, and carbon monitoring; and how digital twins deliver predictive maintenance, adaptive control, and closed-loop optimisation of sustainable air systems.

Research topics may include green fleet and infrastructure management, sustainable MRO, intelligent routing and scheduling, energy and fuel integration, and whole-system lifecycle analysis. This Special Issue aims to bridge engineering innovations, data science, and operational excellence, establishing a digital foundation for resilient, efficient, and truly net-zero air transport operations.

Dr. Maryam Farsi
Dr. Christina Latsou
Dr. Bernadin Namoano
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • digital twin-enabled aviation systems
  • digital models and digital shadows
  • net-zero aviation and air system sustainability
  • smart and sustainable air transport operations
  • predictive and autonomous maintenance
  • AI, CPS, and IoT integration in aviation
  • data-driven fleet and route optimisation
  • lifecycle carbon and energy performance assessment
  • sustainable MRO and infrastructure resilience

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Published Papers (1 paper)

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Research

26 pages, 7993 KB  
Article
Toward Sustainable Airport Surface Operations: A Multi-Objective Collaborative Scheduling Method for Runway-Taxiway Systems Balancing Punctuality, Efficiency, and Carbon Footprint Control
by Mei Tao and Hongchen Liu
Sustainability 2026, 18(13), 6837; https://doi.org/10.3390/su18136837 - 5 Jul 2026
Abstract
Surface congestion and taxiing delays at high-density airports increasingly constrain aviation sustainability, as ground-phase fuel consumption and emissions constitute a significant share of total airport emissions. Existing studies typically decouple air traffic flow management from ground resource scheduling, hindering coordinated optimization of punctuality, [...] Read more.
Surface congestion and taxiing delays at high-density airports increasingly constrain aviation sustainability, as ground-phase fuel consumption and emissions constitute a significant share of total airport emissions. Existing studies typically decouple air traffic flow management from ground resource scheduling, hindering coordinated optimization of punctuality, environmental benefits, and resource utilization. This paper proposes a multi-objective optimization method for runway-taxiway systems oriented toward air–ground collaborative decision-making, integrating Calculated Take-Off Time (CTOT) compliance constraints. A tri-objective mixed-integer programming model is formulated to minimize CTOT deviation, total taxiing time, and runway workload imbalance. A hybrid intelligent algorithm, SSA-SCA-NSGA-II, is designed with a bidirectional elite feedback mechanism to address this NP-hard problem. Validation uses real operational data of 58 departure flights during a peak period at Beijing Daxing International Airport. The results demonstrate that the proposed method achieves effective trade-offs on the Pareto front: CTOT compliance rate increased from 77.6% to 89.7–96.6%; total taxiing time decreased from 692 min to 551–635 min; and dual-runway utilization imbalance declined from 5.2% to 1.7–3.8%. These improvements translate into quantifiable sustainability gains: fuel consumption is reduced by 1425–3525 kg and CO2 emissions by 4503–11,139 kg per peak hour, alongside a 19-percentage point improvement in punctuality that lowers passenger delay costs and reduces controller coordination workload. By simultaneously advancing environmental sustainability (carbon footprint reduction), economic sustainability (fuel and operational cost savings), and social sustainability (service punctuality and labor efficiency), the framework provides a measurable, monitorable, and policy-relevant decision-support tool for green airport surface operations aligned with sustainable development goals (SDGs). Full article
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