Development of a dimensionless thermal comfort index for metro systems: Empirical modeling and validation in Nanjing’s subway network

The thermal comfort in subway carriages directly affects passengers’ travel experience and health, while optimizing it enhances energy efficiency and reduces operational costs. The overarching goal of this research is to develop a novel, metro-specific thermal comfort index that overcomes the predictive limitations of existing indices and provides a practical tool for evaluating and optimizing thermal environments in underground railway systems. To achieve this goal, this study investigated passengers’ thermal comfort across Nanjing’s six busiest metro lines through on-site thermal-humidity measurements and subjective questionnaires, yielding 1067 valid datasets. The database covers parameter ranges of air temperature (20.27°C–31.63°C), mean radiant temperature (7.92°C–35.47°C), relative humidity (45.4%–90.1%), and air velocity (0.06–3.74 m/s), with both environmental data and subjective votes exhibiting approximately normally distributed. Analysis revealed significant limitations in existing thermal comfort indices, evidenced by a 17.8% mean absolute deviation (MAD) for the best-performing existing model. To address this deficiency, dimensional analysis and least squares regression established mathematical relationships between environmental parameters and passengers’ thermal comfort responses, deriving a novel metro-specific thermal comfort index. The proposed index comprises three dimensionless parameters: relative humidity, mean radiant temperature to air temperature ratio, and air velocity water vapor partial pressure product to metabolic rate ratio, accounting for key comfort determinants. Demonstrating high predictive accuracy, it achieves a 13.2% MAD across the entire database with 88.2% predictions maintaining errors within ±30%, while showing a systematic 2.4% overprediction tendency. This empirically validated correlation provides valuable references for optimizing metro environmental design and operational strategies.