Satellite-Assisted Particulate Matter (SAPM) for the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group

Models, In situ, and Remote sensing of Aerosols (MIRA) is an international working group that aims to foster collaborations amongst these three major aerosol specialties. It consists of a collection of interdisciplinary and independently funded projects/topics with clearly-defined goals. Currently there are four MIRA topic areas, including Satellite-Assisted Particulate Matter (SAPM), which is focused specifically on fine particulate matter (PM2.5). The study of PM2.5 is important due to its significant contribution to air pollution and resultant, adverse human health effects. The goal of the SAPM topic group is to conduct and provide intercomparisons of various methods and techniques to obtain surface PM2.5 estimates assisted by satellite remote sensors, global aerosol models, and in situ aerosol measurements. Some benefits of space-based/model-assisted PM2.5 retrievals include providing PM2.5 approximations in regions with poor in situ ground station coverage and a means for assessing spatial/temporal PM2.5 variations on regional and/or global scales. Furthermore, benefits of spaceborne lidar/model-assisted PM2.5 retrievals include providing nighttime PM2.5 estimates and characterization of near-surface aerosol vertical structure. SAPM is seeking international datasets of mass scattering/absorption coefficient and aerosol hygroscopic properties for different aerosol species, as well as ground-based in situ PM2.5 measurements. In this poster presentation, we give an overview of SAPM, and show results from three recent/ongoing PM2.5 studies. These efforts involve deriving surface PM2.5 concentrations from two spaceborne lidars, the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud-Aerosol Transport System (CATS), and investigating key variables that impact the estimation of PM2.5 from model simulated aerosol optical depth (AOD) using the Goddard Earth Observing System (GEOS) model.