Your new experience awaits. Try the new design now and help us make it even better

ORIGINAL RESEARCH article

Front. Sustain. Cities

Sec. Urban Transportation Systems and Mobility

Volume 7 - 2025 | doi: 10.3389/frsc.2025.1643872

This article is part of the Research TopicClimate change and sustainable urban mobility: Low-Emission Zones (LEZ) challenges and experiences for the cities of the futureView all 6 articles

Saudi Arabia's Green Leap: Unlocking Climate Potential of Haramain High Speed Rail Through Occupancy Optimization and Renewable Energy Adoption

Provisionally accepted
  • Islamic University of Madinah, Medina, Saudi Arabia

The final, formatted version of the article will be published soon.

This study presents the first comprehensive evaluation of the CO₂ mitigation potential of Haramain High-Speed Rail (HHR) system of Saudi Arabia using a dynamic scenario-based mathematical modeling approach. Focusing on the 450 km Makkah-Madinah corridor, the analysis examines four operational parameters including train energy efficiency (0.03-0.07 kWh/pkm), grid carbon intensity (0.65-0.10 kgCO₂/kWh), renewable energy (RE) adoption (0-100%), and occupancy rates (25-100%) while accounting for a 15% real-world system efficiency loss. Three key findings challenge prevailing norms in high-speed rail (HSR) planning. First, the HHR may emit up to 187 kT more CO₂ per passenger than diesel buses when occupancy falls below 25% and the system depends on a fossil-heavy grid. However, under full renewable energy adoption and high occupancy, it can save up to 285 kT CO₂ annually (11.93 kg per passenger). Second, occupancy rates exert an outsized influence on carbon performance. In multiple scenarios, ridership optimization yields greater emissions reductions than RE integration alone, particularly when grid decarbonization is partial. Third, the study identifies scenario-specific climate-positive thresholds: net CO₂ savings are achieved when occupancy exceeds 70-75% under the current grid mix, or 45-50% when RE adoption reaches 50%. The above thresholds highlight the nonlinear interplay between energy sourcing and ridership dynamics. The findings inform Vision 2030 and transport planning in fossil-dependent economies. By moving beyond static lifecycle assessments, the methodology integrates operational variability and passenger dynamics offering policymakers a practical toolkit to align clean energy investment with ridership incentives and forecast emissions under real-world conditions. Contributing to UN-SDGs 9, 11, and 13, this study also establishes a foundational reference for future research on decarbonization thresholds in HSR systems particularly across Middle Eastern and arid-region contexts.

Keywords: Transportation engineering, Scenario-Based Mathematical Modeling, sustainable transportation, Optimal thresholds, UN-SDGs, Carbon emission reduction, Green Transformative Infrastructure, High speed rail (HSR)

Received: 09 Jun 2025; Accepted: 17 Aug 2025.

Copyright: © 2025 WAJID. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: HAFIZ Abdul WAJID, Islamic University of Madinah, Medina, Saudi Arabia

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.