Abstract
The spatial features and dynamics of mass concentration of ambient fine particulate matters smaller than 2.5 µm in aerodynamic diameter (PM 2.5 ) is a critical indicator to evaluate regional air quality. In this paper, a geographically and temporally weighted regression (GTWR) model is developed to depict the spatio-temporal dynamics in the PM 2.5 -AOD relationship and generate ground-level PM 2.5 concentrations from satellite-derived 500 m AOD. To test the performance of GTWR model, two case studies were carried out both in Central China and North China. Cross validations display that the performance of GTWR model is better than ordinary least squares (OLS) model, GWR model and temporally weighted regression (TWR) model. GTWR model obtains the highest value of coefficient of determination (R2) and the lowest values of mean absolute difference (MAD), root mean square error (RMSE).
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