ChinaHighPM10 (Version 1)

The high-resolution (1 km) and high-quality PM₁₀ dataset in China (i.e., ChinaHighPM₁₀ dataset) from 2014 to 2019 are generated for the first time. This dataset is generated using a newly developed space-time extremely randomized trees (STET) model based on the newly released MODIS Collection 6 MAIAC 1 km AOD products, meteorological variables, emissions, and auxiliary data. The STET model can derive daily PM₁₀ concentrations with an average across-validation coefficient of determination of 0.86, a low root-mean-square error of 24.28 μg/m³, and a mean absolute error of 14.52 μg/m³. The ChinaHighPM₁₀ dataset can be greatly useful for air pollution studies in medium- or small-scale areas. <strong>Note that this dataset is closed since a new version is published at </strong>10.5281/zenodo.3752465<strong>.</strong>