Population-weighted exposure is a foundational metric in air pollution, health impact, and environmental justice research, yet many studies still rely on static residential populations and coarse environmental fields. These assumptions may obscure important spatial and temporal variation in exposure. At the same time, advances in mobility-informed population data, satellite remote sensing, data fusion, portable sensors, and ecological momentary assessment (EMA) create new opportunities to characterize dynamic exposures at both population and individual levels.

This session invites studies that develop, compare, or apply dynamic exposure assessment methods for air pollution, temperature, greenspace and co-exposures across scales. We welcome work on mobility-aware population-weighted metrics, refined environmental surfaces, personal sensing, GPS-based movement, time-activity patterns, and integration with EMA or related repeated surveys. Topics may include exposure misclassification, uncertainty and validation, neighborhood heterogeneity, environmental justice and implications for epidemiology, intervention and policy.