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Updated: Aug 10, 2026
Real-World M3-BREATHE: Toward Multimodal Mobile Monitoring of Behaviour, Respiration, and Exposures for Treatment and Health Evaluation
Published on: June 5, 2026
Characterizing human exposure to traffic-related air pollution through daily activities using an agent-based
Michele Tirico1, Valentin Le Bescond2, Delphine Sengelin3
1INSA Lyon, CNRS, Ecole Centrale de Lyon, Univ. Claude Bernard Lyon 1, LMFA, UMR5509, 69621, Villeurbanne, France; EMob-Lab, ENTPE, Univ. Gustave Eiffel, Lyon, France.
This study introduces a dynamic model for human exposure to traffic pollution, considering daily activities and movement. While overall exposure is similar to static methods, the dynamic approach reveals crucial intra-day variations and activity-specific pollution impacts.
Area of Science:
- Environmental Health
- Computational Epidemiology
- Urban Planning
Background:
- Accurate human exposure assessment to traffic-related air pollution necessitates integrating pollutant variability with diverse human activities.
- Agent-based mobility models and synthetic populations offer a unified framework for this complex integration.
Purpose of the Study:
- To develop and validate an integrated modelling chain for dynamic human exposure assessment to traffic-related air pollution.
- To compare a novel agent-based dynamic exposure framework with conventional static approaches.
Main Methods:
- An integrated modelling chain was developed, combining synthetic population generation (EQASim), agent-based transport modeling (MATSim), emission modeling (COPERT), dispersion modeling (SIRANE), and an exposure module.
- The framework was applied to the Lyon metropolitan area, comparing dynamic exposure patterns with static methods.
Main Results:
- Cumulative daily exposure indicators were comparable between static and dynamic agent-based approaches at the metropolitan scale.
- The dynamic framework revealed significant intra-day exposure variability, activity-specific exposure patterns, and population redistribution effects.
- Individual trajectories highlighted how daily activities (work, education, leisure) influence exposure profiles, with many experiencing high pollution at home and exposure linked to traffic cycles.
Conclusions:
- The proposed dynamic agent-based framework enhances exposure analysis by capturing detailed human activity and mobility patterns.
- This approach provides a foundation for future research on travel exposure, environmental inequalities, and integration with health impact assessments.
