Assessing PM2.5 Concentrations Estimates from Column Optical Depth, Aeronet and Lidar PBL Height

Air pollution is a mixture of microscopic solids and liquid droplets suspended in air. It is made up of a number of components, including acids (such as nitrates and sulfates), organic chemicals, metals, soil or dust particles, and allergens (such as fragments of pollen or mold spores). Fine particles (PM2.5) correspond to more dangerous health conditions since their sizes are small (2.5 μm in diameter and smaller) enough to be absorbed by the human body and to cause health complications. Health studies have shown a significant association between exposure to fine particles and premature death from heart or lung disease. For remote sensing applications of PM2.5, it is often required to connect column properties of aerosols to PM2.5 at the surface. In converting satellite based AOD to surface PM2.5, current algorithms such as IDEA assume a static relationship between AOD and PM2.5 but such static relationships do not account for the complexities of the Planetary Boundary Layer Height and hygroscopic growth which are clearly modified during the diurnal cycle. In this paper, we demonstrate that accounting for aerosol type and PBL height as monthly values are crucial to reproduce the measured relationship between PM2.5 and AOD.