
ChinaHighSO2 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 SO2 dataset for China from 2019 to the present. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R2) of 0.84, a root-mean-square error (RMSE) of 10.07 µg m-3, and a mean absolute error (MAE) of 4.68 µg m-3 on a daily basis. If you use the ChinaHighSO2 dataset in your scientific research, please cite the following reference (Wei et al., ACP, 2023): 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 Note that the ChinaHighSO2 dataset is also available for periods prior to 2019, but at a spatial resolution of 10 km: all (including daily) data for the years 2013–2018 are accessible at: https://doi.org/10.5281/zenodo.4641538 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 under room conditions (i.e., 298 K and 1013 hPa). 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).
Big data, Artificial intelligence, ChinaHighNO2, CHAP
Big data, Artificial intelligence, ChinaHighNO2, CHAP
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