Here is the big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D1K, M1K, and Y1K) ground-level PM10 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 0.90, a root-mean-square error (RMSE) of 21.12 µg m-3, and a mean absolute error (MAE) of 11.22 µg m-3 on a daily basis. If you use the ChinaHighPM10 dataset for related scientific research, please cite the below-listed corresponding reference first (Wei et al., EI, 2021), and the reference will be updated once our new paper is accepted. Wei, J., Li, Z., Xue, W., Sun, L., Fan, T., Liu, L., Su, T., and Cribb, M. The ChinaHighPM10 dataset: generation, validation, and spatiotemporal variations from 2015 to 2019 across China. Environment International, 2021, 146, 106290. https://doi.org/10.1016/j.envint.2020.106290 The data for the period 2000-2021 is accessible at: https://doi.org/10.5281/zenodo.3752465 More CHAP datasets of different air pollutants can be found at: https://weijing-rs.github.io/product.html

Note that the data are recorded in local time (i.e., Beijing time: GMT+8). 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).