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MERRA2_CNN_HAQAST bias corrected global hourly surface total PM2.5 mass concentration, V1 (MERRA2_CNN_HAQAST_PM25) at GES DISC

Published by NASA/GSFC/SED/ESD/TISL/GESDISC | National Aeronautics and Space Administration | Metadata Last Checked: February 21, 2026 | Last Modified: 2026-02-17
This product provides MERRA-2 bias-corrected global hourly surface total PM2.5 mass concentration with the same horizontal spatial resolution as MERRA-2, covering a temporal range from 2000 to 2024. It is derived using a machine learning (ML) approach with a convolutional neural network (CNN) method and is specifically developed for the NASA Health and Air Quality Applied Sciences Team (HAQAST).The dataset consists of two parameters: MERRA2_CNN_Surface_PM25 and QFLAG. MERRA2_CNN_Surface_PM25, a 3-dimensional variable (time, latitude, longitude), represents the surface PM2.5 concentrations in µg/m³. QFLAG denotes the quality of data at each grid point, where 4 indicates the highest quality and 1 indicates the lowest quality. It is recommended to use QFLAG values of 3 and 4 for quantitative analysis.

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