# Influence of Particulate Matter and Carbon Dioxide on Students' Emotions in a Smart Classroom
## 5 Conclusions  
This study provides significant evidence of the relationship between environmental variables and emotions in educational settings, particularly concerning PM concentrations and CO\({}_{2}\) levels in secondary school classrooms. Significant correlations were observed between these variables and a variety of emotions, highlighting positive associations between CO\({}_{2}\) and negative emotions such as anger and disgust. PM showed weak correlations with emotions, for example, a significant negative correlation with surprise. Additionally, PM\({}_{2.5}\) presented a positive correlation with happiness, and PM\({}_{10}\) with anger. CO\({}_{2}\) showed a positive correlation with anger and a negative correlation with neutral emotion. Although some relationships and patterns have been established, the relatively low levels of environmental factors may limit the variability in emotions detected, potentially reducing the strength of observed correlations. The results of this study are noteworthy for the models for neutral emotion, fear, sadness, surprise, and happiness to explain a significant portion of the variance in these emotions, ranging from 62% to 36%, respectively. In the case of neutral emotion, an increase in PM\({}_{10}\) levels initially increases the expression of this emotion, but the quadratic term for PM\({}_{10}\) reduces this effect. Similarly, for sadness, an increase in PM\({}_{1}\) levels is associated with a slight increase in the expression of this emotion, but the effect diminishes when considering its quadratic term. This suggests that the effect is not linear, and higher levels of PM might eventually have a negative impact. In the case of fear, an increase in CO\({}_{2}\) levels is associated with an increase in the expression of this emotion. This indicates that higher CO\({}_{2}\) levels can intensify fear, suggesting a direct and positive relationship between these factors. The findings of this study present theoretical, methodological, and practical contributions. Regarding the theoretical contribution, this study significantly adds to the limited existing literature that links environmental conditions with emotions. The methodological contribution is the use of affordable technology for monitoring environmental variables, combined with emotional recognition systems. This approach provides an alternative to traditional self-reports in studying mood and comfort regarding environmental conditions. Regarding the practical contributions, first, classroom design is becoming increasingly important, with recommendations focused on creating stimulating, safe, and sustainable spaces, where technology plays an essential role in optimizing learning [40]. Second, real-time monitoring of indoor conditions, like PM and CO\({}_{2}\) levels, offers a proactive way to manage air quality in schools. By continuously tracking these factors, schools can plan and quickly respond to worsening conditions, reducing potential negative impacts on students' well-being. This is especially important in spaces with higher CO\({}_{2}\) levels, like crowded classrooms or during physical education. Finally, advanced and affordable technology, characteristic of the Fourth Industrial Revolution, brings schools closer to smart classrooms. In these spaces, the pedagogical, technological, and environmental dimensions are interconnected, creating a more adaptive and effective setting for learning [41]. There are several limitations to this study. Firstly, its non-experimental design means that direct manipulation of environmental variables or controlled exposure of participants to different conditions was not possible, preventing the establishment of causal relationships between these variables and the observed emotions. Although significant correlations were identified, the influence of confounding variables or other uncontrolled factors cannot be entirely ruled out.