Recognizing the critical impact of environmental factors on individuals, this study explores the relationship between environmental indoor pollutants (PM1, PM2.5, PM10, and CO₂) and students' basic emotional responses based on Ekman’s categorization. Conducted in a secondary school in Spain, it integrates IoT and image processing technologies to monitor air quality and emotions in real-time. Participants included 76 secondary school students and three teachers, with data collected over two months. The results showed significant correlations between PM levels and negative emotions such as anger and disgust, while CO₂ levels were associated with both negative and positive emotions, including happiness. Regression models demonstrated that environmental variables significantly predict basic emotions, highlighting the influence of indoor air quality. These findings emphasize the need for proactive air quality management in educational settings to enhance learning environments and support students' emotional well-being.
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Fretes et al. (2024) studied this question.
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