Method choice in children's exposure assessment for NO2, SO2 and O3

Assessing children's exposure to air pollutants remains a critical challenge due to their dynamic daily routines and the complexity of pollutant behaviour across microenvironments. This study compared seven methodologies for estimating personal exposure to nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and ozone (O₃): passive samplers (PS), fixed-site monitoring (FSM), the CALPUFF and CMAQ models, and their indoor-outdoor (I/O) ratio counterparts. Measurements were conducted across four urban sites, integrating questionnaire-based activity patterns and pollutant-specific I/O ratios. Evaluation metrics included the fraction of predictions within a factor of two (FAC2), the normalized mean square error (NMSE), and a multicriteria decision matrix ranking each method by accuracy, data requirements, and operational feasibility. Results showed that no single method was universally optimal. FSM × I/O achieved the highest overall balance between accuracy and feasibility for primary traffic-related pollutants (NO₂, SO₂), while CMAQ × I/O best represented secondary, regionally driven pollutants (O₃). CALPUFF captured near-road dispersion effectively but exhibited high sensitivity to local emissions and meteorology. Home environments dominated total exposure (82-91%), followed by schools (8-14%) and commuting pathways (<5%). The decision matrix confirmed FSM × I/O and CMAQ × I/O as the most reliable approaches for large-scale exposure assessments in indoor-dominated populations. These findings demonstrate the necessity of integrating I/O ratio and human activity data into exposure models and provide a transparent framework for selecting optimal methods according to pollutant behaviour, data availability, and research objectives.