Influence of Particulate Matter and Carbon Dioxide on Students’ Emotions in a Smart Classroom

The effects of air quality on health and cognition are well documented, but few studies have focused on its impact on emotions, leaving this area underexplored. This study investigates the influence of environmental factors—specifically particulate matter (PM1, PM2.5, and PM10) and carbon dioxide (CO2)—on students’ basic emotions in secondary school classrooms. For the collection of environmental data, we used low-cost sensors, which were carefully calibrated to ensure acceptable accuracy for monitoring air quality variables, despite inherent precision limitations compared to traditional sensors. Emotions were recorded via camera and analyzed using a custom-developed code. Based on these data, we found significant but modest correlations, such as the negative correlation between PM levels and happiness, and positive correlations of CO2 concentrations with fear and disgust. The regression models explained between 36% and 62% of the variance in emotions like neutrality, sadness, fear, and happiness, highlighting nonlinear relationships in some cases. These findings underscore the need for improved classroom environmental management, including the implementation of real-time air quality monitoring systems. Such systems would enable schools to mitigate the negative emotional effects of poor air quality, contributing to healthier and more conducive learning environments. Future research should explore the combined effects of multiple environmental factors to further understand their impact on student well-being.