Study on the relationship between aerosol anthropogenic component and air quality in the city of Wuhan

Problems with air pollution in urban areas have been known for a long time. The air quality has an enormous impact for people\´s daily life. The Wuhan Environmental Protection Bureau currently uses ground sensors to monitor air quality in the city of Wuhan. While this method provides accurate information at specific locations, it does not provide a clear indication of conditions over the whole region. Measurements from satellite imagery have the potential to provide timely air quality data for large swaths of land. Satellite remote sensing of air quality has evolved dramatically over the last decade. Global observations are now available for a wide range of species including aerosols, O₃, NO₂, CO and SO₂. Previous studies show strong correlations between MODIS-derived Aerosol Optical Depth (AOD) and surface PM (particulate matter) measurements, which is an important indicator for the air-quality. However, this relationship is not so significant from region to region. The reason is that, although the basic transfer theory in the atmosphere is well understood, its application in urban environments is less than adequate when the domain controlling parameters and their coupling mechanisms are not well defined. Satellite instruments do not measure the aerosol chemical composition needed to discriminate anthropogenic from natural aerosol components. But the ability of new satellite instruments to distinguish fine (submicron) from coarse (supermicron) aerosols over the oceans, serves as a signature of the anthropogenic component and can be used to estimate the fraction of anthropogenic aerosols. In this paper, we developed this method to continental area, the city of Wuhan. By collecting the MOD04 production over the city of Wuhan in 2005, we extracted the aerosol optical thickness(AOT) at the 550nm (τ_550nm) and the fine mode fraction (FMF), which were used to calculate out the aerosol anthropogenic component (τant). The ground-based air quality indexes, such as PM₁₀, NO₂ and SO₂, were also collected synchronously. The pre-processing of the MOD04 data were performed using external development of the IDL language. Statistical analysis was conducted in MATLAB (version 7.8) software to establish linear regression model of the τ_ant and the index of air-quality relationships. Correspondingly, the relationships between the τ_550nm and the index of air-quality were also explored. It showed that the relationships between the former were much stronger than the latter. And the main factor of the air quality in the city of Wuhan was changing from season to season.