| Summary: | Current PM<sub>2.5</sub> retrieval maps have many missing values, which seriously hinders their performance in real applications. This paper presents a framework to map full-coverage daily average PM<sub>2.5</sub> concentrations from MODIS C6 aerosol optical depth (AOD) products and fill missing pixels in both the AOD and PM<sub>2.5</sub> maps. First, a two-stage inversed variance weights (IVW) algorithm was adopted to fuse the MODIS C6 Terra and Aqua AOD products, which fills missing data in MODIS standard AOD data and obtains a high coverage daily average. After that, using the fused MODIS daily average AOD and ground-level PM<sub>2.5</sub> in all grid cells, a two-stage generalized additive model (GAM) was implemented to obtain the full-coverage PM<sub>2.5</sub> concentrations. Experiments on the Yangtze River Delta (YRD) in 2013−2016 were carefully designed to validate the performance of our proposed framework. The results show that the two-stage IVW could not only improve the spatial coverage of MODIS AOD against the original standard product by 230%, but could also keep its data accuracy. When compared with the ground-level measurements, the two-stage GAM can obtain accurate PM<sub>2.5</sub> concentration estimates (R<sup>2</sup> = 0.78, RMSE = 19.177 μg/m<sup>3</sup>, and RPE = 28.9%). Moreover, our method performs better than the inverse distance weighted method and kriging methods in mapping full-coverage daily PM<sub>2.5</sub> concentrations. Therefore, the proposed framework provides a good methodology for retrieving full-coverage daily average PM<sub>2.5</sub> concentrations from MODIS standard AOD products.
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