Interpretable machine learning for occupant-specific PM2.5 exposure assessment in higher education buildings

Key Points

• Occupant-specific PM2.5 exposure showed significant variation based on machine learning analysis.
• Machine learning techniques provided insights into environmental factors influencing PM2.5 levels.
• Assessment involved applying predictive modeling tools to evaluate exposure levels across various building types.
• Findings suggest targeted interventions may improve air quality in higher education buildings.