ChinaHighNO2: Big Data Seamless 10 km Ground-level NO2 Dataset for China

ChinaHighNO2 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 10 km (i.e., D10K, M10K, and Y10K) ground-level NO2 dataset in China from 2013 to 2018. This dataset yields a 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.

Note that the ChinaHighNO2 dataset is 10 km before 2019, and improved to 1 km after 2019, which is available at https://doi.org/10.5281/zenodo.4641538. If you use the ChinaHighNO2 dataset for related scientific research, please cite the corresponding references (Wei et al., ACP, 2023; Wei et al., ES&T, 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

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