ChinaHighNO2 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 10 km (i.e., D10K, M10K, and Y10K) ground-level NO2 dataset for China from 2008 to 2018. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R2) of 0.84, a root-mean-square error (RMSE) of 7.99 µg m-3, and a mean absolute error (MAE) of 5.34 µg m-3 on a daily basis. If you use the ChinaHighNO2 dataset in your scientific research, please cite the following references (Wei et al., ACP, 2023; Wei et al., EST, 2022): Wei, J., Li, Z., Wang, J., Li, C., Gupta, P., and Cribb, M. Ground-level gaseous pollutants (NO2, SO2, and CO) in China: daily seamless mapping and spatiotemporal variations. Atmospheric Chemistry and Physics, 2023, 23, 1511–1532. https://doi.org/10.5194/acp-23-1511-2023 Wei, J., Liu, S., Li, Z., Liu, C., Qin, K., Liu, X., Pinker, R., Dickerson, R., Lin, J., Boersma, K., Sun, L., Li, R., Xue, W., Cui, Y., Zhang, C., and Wang, J. Ground-level NO2 surveillance from space across China for high resolution using interpretable spatiotemporally weighted artificial intelligence. Environmental Science & Technology, 2022, 56(14), 9988–9998. https://doi.org/10.1021/acs.est.2c03834 Note that the ChinaHighNO2 dataset was improved to a 1 km resolution after 2019: all (including daily) data for the years after 2019 are accessible at: https://doi.org/10.5281/zenodo.4571660 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).