ChinaHighPM2.5 (2022-2023)

Here is the big data-derived gapless (spatial coverage = 100%) daily, monthy, and annual 1 km (i.e., D1K, M1K, and Y1K) PM2.5 dataset in China for the years 2022 and 2023. This dataset yields a high quality with a cross-validation coefficient of determination (CV-R2) of 0.92, a root-mean-square error (RMSE) of 10.76 µg m-3, and a mean absolute error (MAE) of 6.32 µg m-3 on a daily basis.

If you use the ChinaHighPM2.5 dataset for related scientific research, please cite the below-listed corresponding references first (Wei et al., RSE, 2021; Wei et al., ACP, 2020), and the reference will be updated once our new paper is accepted.

Wei, J., Li, Z., Lyapustin, A., Sun, L., Peng, Y., Xue, W., Su, T., and Cribb, M. Reconstructing 1-km-resolution high-quality PM2.5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications. Remote Sensing of Environment, 2021, 252, 112136. https://doi.org/10.1016/j.rse.2020.112136

Wei, J., Li, Z., Cribb, M., Huang, W., Xue, W., Sun, L., Guo, J., Peng, Y., Li, J., Lyapustin, A., Liu, L., Wu, H., and Song, Y. Improved 1 km resolution PM2.5 estimates across China using enhanced space-time extremely randomized trees. Atmospheric Chemistry and Physics, 2020, 20(6), 3273–3289. https://doi.org/10.5194/acp-20-3273-2020

The data for the period 2000-2021 is accessible at: https://doi.org/10.5281/zenodo.3539349

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