Exposure to ambient air pollution is a major risk factor for global disease. Assessment of the impacts of air pollution on population health and evaluation of trends factors requires accurate estimates of exposures experienced by populations. The recently developed Data Integration Model for Air Quality (DIMAQ) uses estimates from satellite retrievals of aerosol optical depth and chemical transport models, population density estimates, and topography, and calibrates them with ground monitoring data in order to provide estimates of exposures to PM2.5 at a high spatial resolution (10km x 10km) globally. Based on summaries of the posterior distributions for each grid cell, it is estimated that 92% of the world's population reside in areas exceeding the World Health Organization's Air Quality Guidelines. DIMAQ was also used to produce global estimates of annual average fine particle (PM2.5) for five-year intervals from 1990 to 2010 and yearly from 2011-2015. These estimates are used to examine trends in population exposures toPM2.5 for each of 184 countries.