ChinaHighPM2.5 is one of the series of long-term, full-coverage, high-resolution, and high-quality datasets of ground-level air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from the big data (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence by considering the spatiotemporal heterogeneity of air pollution. This is the big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D1K, M1K, and Y1K) ground-level PM2.5 dataset in China from 2000 to present. This dataset yields a high quality with a cross-validation coefficient of determination (CV-R2) of 0.92 and a root-mean-square error (RMSE) of 10.76 µg m-3 on a daily basis. Note that this dataset is continuously updated, and if you want to apply for more data or have any questions, please contact me (Email: weijing_rs@163.com; weijing@umd.edu). The data file contains four codes (Python, Matlab, IDL and R language) nc2geotiff codes for NC to GeoTiff.

ChinaHighPM2.5 is one of the series of long-term, full-coverage, high-resolution, and high-quality datasets of ground-level air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from the big data (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence by considering the spatiotemporal heterogeneity of air pollution.

This is the VIIRS derived yearly 6 km ground-level PM2.5 dataset in China from 2013 to 2018, and this dataset yields a high quality with a cross-validation coefficient of determination (CV-R2) reaching 0.88 and a root-mean-square error (RMSE) of 16.52 µg m-3 on a daily basis.

If you use the ChinaHighPM2.5 dataset for related scientific research, please cite the corresponding reference (Wei et al., TGRS, 2022):

Wei, J., Li, Z., Sun, L., Xue, X., Ma, Z., Liu, L., Fan, T., and Cribb, M. Extending the EOS long-term PM2.5 data records since 2013 in China: application to the VIIRS Deep Blue aerosol products. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60, 4100412. https://doi.org/10.1109/TGRS.2021.3050999

More CHAP datasets of different air pollutants can be found at: https://weijing-rs.github.io/product.html