TY  - Data
T1  - Gap-free 1-km PM2.5 dataset in China (2000-2022)
A1  - he Qing Qing
DO  - 10.12072/ncdc.atmosphere.db7401.2026
PY  - 2026
DA  - 2026-05-28
PB  - National Cryosphere Desert Data Center
AB  - This study uses a random forest-based retrospective simulation method to generate a PM2.5 dataset with daily full coverage of 1 kilometer in China from 2000 to 2020.Before 2013, there was a lack of available PM2.5 ground observation data in China and could not be directly used for model construction and accuracy verification. Therefore, this method focuses on optimizing the PM2.5 estimation effect during this period.For the first time, the study incorporated observed prediction factors before 2013 into the model operation. The model input data covers multiple types of data sources: MAIAC aerosol optical thickness, meteorological observation data from China Meteorological Administration, ERA-5 reanalysis data and other land-related data.This dataset is monthly average data from 2000 to 2022 in the format GEOTIFF; the data from 2021 to 2022 are independently estimated using the model constructed in the above documents. After cross-verification with ten folds of samples, the model's coefficient of determination R2 in 2021 is 0.91, and the root-mean-square error RMSE is 8.84 μg/m3; in 2022, the R2 is 0.93, and the RMSE is 7.42 μg/m3.
DB  - NCDC
UR  - http://www.ncdc.ac.cn/portal/metadata/54dbfe3d-56a6-41e9-8de6-321dca692329
ER  -