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As a new generation of polar-orbiting satellites, NPP VIIRS (National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite) provides important supports for the studies of local and global scale climate change, environmental monitoring, and radiant energy balance. This paper proposed an improved deep blue aerosol retrieval algorithm over complex regions based on NPP VIIRS observations. Two improvements were proposed and implemented to the traditional aerosol optical depth (AOD) retrieval algorithm in order to improve the retrieval accuracy, including the construction of the surface reflectance conversion model and aerosol optical parameter acquisition. The retrieval results were extensively evaluated. First, the accuracy of the algorithm was evaluated using AErosol RObotic NETwork ground-based observations, including conditions over different underlying surfaces, different seasons, and different AOD values. Then, the cross validation was carried out between our AOD retrievals and NPP VIIRS aerosol products. The verification results show that our AOD retrievals agree very well with the AErosol RObotic NETwork AOD with coefficient of determination (R-2)similar to 0.85. The improved deep blue algorithm performs well overall under different surface conditions and seasons, while the quality of performance gradually decreases with the increase of AOD. Moreover, the improved algorithm is robust with less bias, root-mean-square error, and relative mean bias in the AOD retrievals and can provide more detailed aerosol information compared with the NPP VIIRS aerosol products. These results suggest that the improved deep blue algorithm can obtain high-precision AOD information, providing better data basis for related researches on air pollution and climate change.