Performance Assessment of Energy-Efficient Ventilation in Highway Tunnels

Abstract

This study investigates the integration of energy-efficient ventilation strategies for maintaining optimal air quality in road tunnels. With increasing emphasis on sustainability and the urgent need to reduce energy consumption in infrastructure systems, the research aims to evaluate and optimize tunnel ventilation by balancing pollutant control with minimal energy use. The study is designed to simulate airflow and pollutant dispersion under different traffic and environmental conditions, assess the energy consumption of conventional and demand-controlled ventilation (DCV) systems, and identify optimal control strategies that satisfy air quality standards while minimizing power usage. The methodology involves developing a three-dimensional tunnel model, incorporating real-world geometry, traffic-induced emission profiles (focusing on CO and NOx), and ventilation system configurations. Different scenarios are analyzed, including fixed-speed and variable-speed fan operations, with DCV strategies implemented using pollutant thresholds to regulate fan performance. Energy demands are computed based on airflow dynamics and fan duty cycles, while the model outputs are validated against existing regulatory standards such as those set by PIARC and the World Health Organization. Results indicate that DCV strategies can reduce ventilation energy consumption by up to 35% without compromising on air quality, offering a more sustainable alternative to traditional ventilation practices. The study concludes that CFD-based evaluation offers a practical framework for the development of intelligent ventilation systems, enhancing operational efficiency and environmental performance. However, the study is limited by the assumption of uniform traffic flow and static emission profiles, and does not incorporate real-time sensor feedback, which could be explored in future work through integration with IoT-based monitoring systems. This research provides significant practical benefits by offering validated insights that support the design, retrofitting, and operation of energy-efficient tunnel ventilation systems, particularly for application in urban and congested settings where air quality and energy management are critical concerns.

Introduction

Tunnel ventilation is essential for maintaining air quality and safety in urban tunnels, where vehicle emissions like CO, NOx, and particulate matter accumulate. Traditional fixed-speed ventilation systems, while effective at peak traffic, are energy-intensive and inefficient during low traffic periods. This has driven interest in demand-controlled ventilation (DCV) systems that adjust fan speeds based on real-time pollutant levels and traffic density, achieving substantial energy savings without compromising air quality.

Advances in Computational Fluid Dynamics (CFD) have allowed detailed simulation of airflow and pollutant dispersion in tunnels, enabling optimized ventilation designs. Recent developments include AI and IoT integration for smart, adaptive control aligned with global air quality standards (WHO, PIARC).

This study developed a 3D CFD model of a highway tunnel with realistic geometry and traffic emissions to compare fixed-speed and DCV strategies. Results showed DCV could reduce ventilation energy consumption by up to 35% while maintaining over 95% compliance with air quality standards. The model provides a validated framework for implementing intelligent, energy-efficient ventilation in urban tunnels.

Challenges remain in capturing dynamic traffic fluctuations, integrating real-time controls, and practical deployment. However, the research marks a significant step towards sustainable, adaptive tunnel ventilation systems that balance safety, environmental compliance, and operational efficiency.

Conclusion

This study presented a comprehensive CFD-based framework for evaluating and optimizing tunnel ventilation systems using demand-controlled strategies, with a focus on balancing energy consumption and air quality compliance. A hypothetical 1 km national expressway tunnel was modelled to simulate airflow and pollutant dispersion under both fixed-speed and demand-controlled ventilation (DCV) scenarios. The results demonstrated that DCV systems can significantly reduce energy usage—by approximately 25% under moderate load and up to 35% during peak load—without compromising compliance with air quality standards set by PIARC (2012) and WHO (2021). The findings confirm that pollutant-responsive fan control is a viable strategy for achieving operational sustainability in tunnel environments, especially in energy-intensive transportation infrastructure. Air quality compliance remained high across all cases, with only marginal differences observed between fixed-speed and DCV operations, suggesting that intelligent control can maintain environmental safety while optimizing resource use. Despite its strengths, the study was subject to several limitations. Emissions were modelled as distributed line sources with simplified profiles, and traffic flow was assumed uniform, excluding peak congestion or vehicle acceleration effects. The study also did not incorporate real-time sensor feedback or simulate fan activation delays, which are critical to practical implementation. Moreover, complex thermal interactions, secondary chemical reactions, and particulate matter dynamics were outside the scope of the current model. Looking ahead, future work should integrate real-time traffic modelling, IoT-based sensor networks, and machine learning algorithms for predictive ventilation control. Expanding pollutant tracking and conducting full life-cycle cost analysis will further enhance the model’s applicability for tunnel operators and policymakers. Practically, this research contributes a scalable and validated modelling approach that can inform the design and retrofitting of ventilation systems in urban tunnels. It supports the development of low-energy, smart infrastructure aligned with environmental regulations and climate targets. By demonstrating how DCV systems can reduce energy demand while safeguarding air quality, this study offers a strategic pathway toward sustainable tunnel operation in both developed and emerging transportation networks.

References

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Copyright

Copyright © 2025 Shrirang Deshpande, Shilpa Deshpande, Nilesh Pawar, Sachin Shinde, Ashish Lanje. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.