<p>Accurate assessment of personal exposure to fine particulate matter (PM_2.5) and associated health risks requires integrating hyper-local, mobile monitoring data––collected across the full range of indoor and outdoor geographic contexts in which individuals are situated––with individuals’ daily mobility and dynamic inhalation rates, which vary with physical activity (PA) and physiological characteristics. However, most previous studies have not simultaneously considered all these key factors. This study addresses this gap by combining real-time PM_2.5 data collected via personal monitoring, along with individuals’ real-time locations, PA intensity, and physiological characteristics, to estimate mobility- and real-time PA-based average daily inhaled doses (ADD). This study compared ADD with traditional exposure metrics that fail to simultaneously account for these key factors to assess if group differences in exposure and non-carcinogenic risk are consistently identified in all these metrics. A three-dimensional geovisualization illustrated the spatiotemporal dynamics of exposure. Results showed significant gender differences only in ADD (men higher), highlighting the importance of accounting for both mobility and real-time PA intensity. Individuals with lower educational attainment exhibited higher exposure and risk in all mobility-based metrics––a difference not captured by the residence- and concentration-based metric. The 3D visualization confirmed that inhaled dose changes do not always align with exposure concentration changes, highlighting PA’s mediating role. Our findings demonstrate the advantages of mobile sensing for collecting individual-level data and emphasize the need for mobility- and PA-aware approaches for accurate, personalized health risk assessments, as well as for advancing environmental justice and health disparities research.</p>