Sub-Saharan Africa (SSA) is rapidly urbanizing and ambient air pollution has emerged as a major environmental health concern in cities. However, limited air quality data hinders policy and health impact assessment in the region. This dissertation documents large-scale ambient fine particulate matter (PM2.5) and black carbon (BC) measurement campaign, the development of high-resolution space-time exposure models, and the association of exposures with blood pressure (BP) among schoolchildren in the Greater Accra Metropolitan Area (GAMA), Ghana. Chapter 1 introduces the current knowledge and gaps in ambient air pollution and childhood hypertension in SSA. Chapter 2 covers the feasibility of using low-cost sensors to bridge the air quality data gap in Accra. Chapter 3 describes space-time variations in PM2.5 and BC levels measured at 146 locations across the GAMA. Chapter 4 contains the integration of the measured data with geospatial and meteorological variables in land-use regression (LUR) models to predict and map PM2.5 and BC concentrations for the entire metropolis. Finally, Chapter 5 involves BP measurements in 502 schoolchildren from 50 elementary schools and analyses of their association with long-term PM2.5 and BC exposures at home and school environments. The results showed that residents of the GAMA were exposed to annual average PM2.5 concentrations at 5–10 times higher than the World Health Organization (WHO) guideline (5µg/m3). PM2.5 and BC levels were highest in commercial/high-density areas, poorer residential neighborhoods, and increased by 2–4 folds in the dry dusty Harmattan season. The LUR models explained 48–69% and 63–71% of the variance in PM2.5 and BC concentrations and performed similarly to models from other world regions. The prevalence of elevated BP among schoolchildren in the GAMA was 34% and half of those were hypertensive. Annual mean PM2.5 exposure of the children ranged from 27 to 41 µg/m3 (mean: 34 µg/m3) and BC ranged from 3 to 14 ´10-5m-1 (mean: 5 ´10-5m-1), but they were not associated with systolic, diastolic, or elevated BP in models adjusted for confounding factors. The data presented could form the basis for air pollution related policies as well as climate and health impact assessment in the SSA context.