ChinaHighO3 is part of a series of long-term, seamless, high-resolution, and high-quality datasets of air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from big data sources (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence, taking into account the spatiotemporal heterogeneity of air pollution. Here is the big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D1K, M1K, and Y1K) ground-level maximum daily 8-hour average (MDA8) O3 dataset for China from 2000 to the present. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R2) of 0.89, a root-mean-square error (RMSE) of 15.77 µg m-3, and a mean absolute error (MAE) of 10.48 µg m-3 on a daily basis. If you use the ChinaHighO3 dataset in your scientific research, please cite the following references (Yang et al., RSE, 2025; Wei et al., RSE, 2022): Yang, Z., Li, Z., Cheng, F., Lv, Q., Li, K., Zhang, T., Zhou, Y., Zhao, B., Xue, W., and Wei, J. Two-decade surface ozone (O3) pollution in China: enhanced fine-scale estimations and environmental health implications. Remote Sensing of Environment, 2025, 317, 114459. https://doi.org/10.1016/j.rse.2024.114459 Wei, J., Li, Z., Li, K., Dickerson, R., Pinker, R., Wang, J., Liu, X., Sun, L., Xue, W., and Cribb, M. Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China. Remote Sensing of Environment, 2022, 270, 112775. https://doi.org/10.1016/j.rse.2021.112775 More CHAP datasets for different air pollutants are available at: https://weijing-rs.github.io/product.html

Note that the data are recorded in local time (i.e., Beijing time: GMT+8), and measured at the standard condition (i.e., 273 K and 1013 hPa). The concentrations can be converted to the room condition (i.e., 298 K and 1013 hPa) by dividing by a factor of 1.09375 (MEE, 2018). This dataset is continuously updated. If you require additional data for related scientific research, please contact us (weijing_rs@163.com or weijing.rs@gmail.com).