A Long-term Gap-free High-resolution Air Pollutants concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and earth system science analysis. In the current release of LGHAP aerosol dataset (LGHAP.v1), we provide a 21-year-long (2000–2020) gap free AOD product with daily 1-km resolution covering the land area of China. The dataset was generated via a seamless integration of the tensor flow based multimodal data fusion with ensemble learning based knowledge transfer in statistical data mining. The proposed method transformed a set of data tensors of AOD and other related datasets such as air pollutants concentration and atmospheric visibility that were acquired from diversified sensors or platforms via integrative efforts of spatial pattern recognition for high dimensional gridded data analysis toward data fusion and multiresolution image analysis. The daily gap free AOD was provided in the NetCDF format, while data in each individual year were archived in a zip file. Python, Matlab, R, and IDL codes were also provided to help users read and visualize the LGHAP data.