Particulate matter with aerodynamic diameters smaller than 2.5 mum (PM2.5) contributes greatly to air pollution and poses significant threats to human health. Space-borne passive aerosol measurements, with their large spatial coverage, have been applied for estimating surface-based PM 2.5 concentrations. Specifically, column-integrated aerosol optical thickness (AOT) observations, like those from the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) instruments, have been leveraged for this task. In this doctoral research study, the issues and limitations with estimating PM2.5 from passively-retrieved MODIS and MISR AOT over the contiguous United States (CONUS) were first explored. Second, the potential of using active space-borne NASA Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) near-surface aerosol extinction retrievals for PM2.5 estimation is studied. This includes exploration of various factors that affect CALIOP aerosol data processing, including the retrieval fill value (RFV) issue that results from CALIOP minimum aerosol detection limits. Next, an innovative approach for deriving PM2.5 concentrations directly from CALIOP near-surface aerosol extinction data has been explored using a bulk-mass-modeling-based method, and were validated against in situ PM2.5 from U.S. Environmental Protection Agency (EPA) ground stations. Lastly, temporal variations of CALIOP-based aerosol vertical distribution, including trends of near-surface aerosol loading, were examined globally and regionally to infer possible changes in surface air quality.