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Second, to improve the spatial resolution and accuracy of the global daily PM 2.5 estimation, we developed a machine-learning-based PM 2.5 retrieval model that combines data from multiple sources, including ground-monitoring measurements, satellite retrievals, reanalysis data and GEOS-Chem simulations, to estimate the global daily PM 2.5 concentrations at a spatial resolution of 0.1 0.1

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