New algorithms and their application for satellite remote sensing of surface PM2.5 and aerosol absorption

Abstract

Estimation of Particulate Matter (PM) concentration and aerosol absorption is very important in air quality and climate studies. To date, smoke, mineral dust and anthropogenic pollutants are the most uncertain aerosol components in their optical and microphysical properties. In this study, we retrieve the PM2.5 and Absorbing Aerosol Optical Depth (AAOD) from the Total Ozone Mapping Spectrometer (TOMS), the Moderate Resolution Imaging SpectroRadiometer (MODIS) and the Multiangle Imaging SpectroRadiameter (MISR) measurements. A global chemical transport model (GEOS-CHEM) is used to simulate the vertical profiles of PM2.5 and AAOD. We find that the 2003 heat wave has strong impact on PM2.5 across Europe and increased the average PM2.5 concentration by 18%. The aerosol species with the largest concentration increase are ammonium nitrate, black carbon and mineral dust. The Aerosol Robotic Network (AERONET) measurements have been used to validate our retrieval of AAOD. We find that there is a significant agreement between AERONET measurements and our retrievals with the correlation coefficient, slope and intercept of 0.91, 0.99 and 0.001, respectively. The absorbing aerosols can exert negative health effect, increase positive aerosol radiative forcing and contribute positive aerosol-climate feedbacks.