ChinaHighPM₂.₅: Hourly 5 km Ground-Level PM₂.₅ Dataset for China (2018)
Authors/Creators
- 1. University of Maryland
Description
ChinaHighPM2.5 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 satellite-derived hourly 5 km (i.e., H5K) ground-level PM2.5 dataset for Eastern China for the year 2018. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R2) of 0.85 and a root-mean-square error (RMSE) of 13.62 on a daily basis.
If you use the ChinaHighPM2.5 dataset in your scientific research, please cite the following references (Wei et al., ACP, 2021):
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Wei, J., Li, Z., Pinker, R., Wang, J., Sun, L., Xue, W., Li, R., and Cribb, M. Himawari-8-derived diurnal variations of ground-level PM2.5 pollution across China using the fast space-time Light Gradient Boosting Machine (LightGBM). Atmospheric Chemistry and Physics, 2021, 21, 7863–7880. https://doi.org/10.5194/acp-21-7863-2021
More CHAP datasets for different air pollutants are available at: https://weijing-rs.github.io/product.html
Notes
Files
Wei_et_al-ACP-2021.pdf
Files
(546.2 MB)
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Additional details
Related works
- Is referenced by
- Journal article: 10.5194/acp-21-7863-2021 (DOI)
References
- Wei, J., Li, Z., Pinker, R., Wang, J., Sun, L., Xue, W., Li, R., and Cribb, M. Himawari-8-derived diurnal variations of ground-level PM2.5 pollution across China using the fast space-time Light Gradient Boosting Machine (LightGBM). Atmospheric Chemistry and Physics, 2021, 21, 7863–7880. https://doi.org/10.5194/acp-21-7863-2021