Growing evidence links traffic-related air pollution (TRAP) to adverse health effects. We designed an innovative and extensive mobile monitoring campaign to characterize TRAP exposure levels for the Adult Changes in Thought (ACT) study, a Seattle-based cohort. The campaign measured particle number concentration (PNC) to capture ultrafine particles (UFP), black carbon (BC), nitrogen dioxide (NO2), fine particulate matter (PM2.5), and carbon dioxide (CO2) at 309 stop sites representative of the cohort. We collected about 29 two-minute visit measures at each site during all seasons, days of the week, and most times of day during a one-year period. Validation showed good agreement between our BC, NO2, and PM2.5 measurements and regulatory monitoring sites (R2 = 0.68-0.73). Universal kriging–partial least squares models of annual average pollutant concentrations had cross-validated mean square error-based R2 (and root mean square error) values of 0.77 (1,177 pt/cm3) for PNC, 0.60 (102 ng/m3) for BC, 0.77 (1.3 ppb) for NO2, 0.70 (0.3 µg/m3) for PM2.5, and 0.50 (4.2 ppm) for CO2. Overall, we found that the design of this extensive campaign captured the spatial pollutant variations well and these were explained by sensible land use features, including those related to traffic.SynopsisWe develop well-performing, long-term average pollutant exposure prediction models for epidemiologic application from an innovative and extensive short-term mobile monitoring campaign.Abstract Figure