Abstract
Air quality in public transportation systems, particularly in subway networks, has become an important factor in passenger health and well-being. The development of advanced monitoring technologies, such as IoT sensors, has enabled the real-time measurement of air quality parameters like CO2, PM2.5, and PM10, allowing for a better understanding of environmental conditions in enclosed spaces. However, the impact of varying passenger density on air quality throughout the day, especially during peak hours, has not been sufficiently studied. This study addresses this gap by comparing air quality measurements in subway stations during peak hours and quieter periods. Here, we show that air quality parameters, including CO2, PM2.5, and PM10, significantly worsen during peak hours due to the higher passenger density, which contrasts with prior assumptions that air quality remains relatively constant throughout the day. These findings expand our understanding of how crowded conditions affect air quality, highlighting the need for more effective air circulation and filtration systems during peak times. This research emphasizes the importance of incorporating real-time air quality monitoring into subway system management to improve health outcomes for passengers and workers. Ultimately, the integration of advanced sensor networks could lead to the development of more efficient, responsive systems for managing air quality in urban transit environments.