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