Air quality and thermal comfort conditions in train cabins: a systematic review

• Review of experimental and numerical studies related to train cabins. • Unified comparison indices to evaluate the HVAC efficiency across various cabins. • The effect of HVAC systems on airflow and pollution distribution. • Different respiratory actions modeling and pollutant sources in train cabins. This review explores recent developments in research on airflow, thermal comfort, and pollutant distribution within train cabins, emphasizing both numerical modeling and experimental measurement approaches. Given the complex geometry, fluctuating occupancy, and varying HVAC configurations of train environments, a systematic analysis of studies published between 2004 and 2024 has been conducted to identify the common evaluation methods and highlight critical knowledge gaps. Comfort indices, along with pollutant parameters, have been compared to ensure comparability across studies, given that several parameters have been used in various research works. Numerical studies have been evaluated based on the selection of turbulence models, heat transfer modeling approaches, and the effect of different parameters on thermal and pollutant indices. Experimental studies, including both quantitative measurements and passenger surveys, have been analyzed to assess how real-world conditions align with simulation results. Findings indicate that although CFD remains a valuable tool, it often oversimplifies key factors like transient events, solar radiation, and multi-source emissions. HVAC system performance varies widely, with hybrid ventilation strategies emerging as the most promising for enhancing both comfort and air quality. Despite the increasing interest in advanced comfort models, such as Corrected Predicted Mean Vote and Berkeley indices, their implementation in real applications is still limited. This review highlights the need for more comprehensive and integrated approaches that combine physiological data, subjective feedback, and detailed environmental modeling to improve the design of healthier, more energy-efficient train cabins