Hirst, Kennedy, authorCarter, Ellison, advisorL'Orange, Christian, committee memberBareither, Christopher, committee member2025-06-022025-06-022025https://hdl.handle.net/10217/241000Exposure to air pollution is a major public health concern, with PM2.5 and black carbon (BC) linked to adverse health outcomes. To reduce emissions of PM2.5 and BC, the Chinese government implemented the Coal-to-Clean Energy Policy (CCEP) in 2016, reducing indoor PM2.5 concentrations. However, its effect on personal exposure remains unclear. This study evaluated the role of time-activity patterns in personal exposure to PM2.5 and BC in the context of the policy. Data from the Beijing Household Energy Transition study (winters of 2018-2022) included 252 participants with concurrent indoor and personal PM2.5 measurements and GPS- based time-activity data. Geofencing classified participant locations, and generalized linear models assessed exposure determinants. Model performance was evaluated using indoor PM2.5 data with and without time-activity adjustments. Personal PM2.5 exposure averaged 52.9 μg/m3, while BC averaged 1.6 μg/m3. The best PM2.5 model used indoor PM2.5 over the full sampling period (AIC: 489.06, adjusted R2: 0.59). The top BC model used indoor PM2.5 averaged only while participants were home (AIC: 407.59, adjusted R2: 0.25). On average, participants spent 20.0 hours at home per day (95% CI: 19.4, 20.7). Despite these time-activity trends, the lack of reductions in personal exposure were not explained by time-activity patterns, indicating that other influential factors may be impacting exposure, or the available data was insufficient to fully capture exposure variability. Enhanced time-activity monitoring is necessary to improve exposure assessments and better inform air quality interventions.born digitalmasters thesesengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.Text