Retrieval of high-resolution atmospheric particulate matter concentrations from satellite-based aerosol optical thickness over the Pearl River Delta area, China

Abstract

Satellite remote sensing offers an effective approach to estimate indicators of air quality on a large scale. It is critically significant for air quality monitoring in areas experiencing rapid urbanization and consequently severe air pollution, like the Pearl River Delta (PRD) in China. This paper starts with examining ground observations of particulate matter (PM) and the relationship between PM 10 (particles smaller than 10 μm) and aerosol optical thickness (AOT) by analyzing observations on the sampling sites in the PRD. A linear regression (R 2 = 0.51) is carried out using MODIS-derived 500 m-resolution AOT and PM 10 concentration from monitoring stations. Data of atmospheric boundary layer (ABL) height and relative humidity are used to make vertical and humidity corrections on AOT. Results after correction show higher correlations (R 2 = 0.55) between extinction coefficient and PM 10. However, coarse spatial resolution of meteorological data affects the smoothness of retrieved maps, which suggests high-resolution and accurate meteorological data are critical to increase retrieval accuracy of PM. Finally, the model provides the spatial distribution maps of instantaneous and yearly average PM 10 over the PRD. It is proved that observed PM 10 is more relevant to yearly mean AOT than instantaneous values.