ChinaHighPM₁: Daily Seamless 1 km Ground-Level PM₁ Dataset for China (2000–Present)
Description
ChinaHighPM1 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 PM1 dataset for China from 2000 to the present. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R2) of 0.83, a root-mean-square error (RMSE) of 9.50 µg m-3, and a mean absolute error (MAE) of 6.17 µg m-3 on a daily basis.
If you use the ChinaHighPM1 dataset in your scientific research, please cite the following reference (Wei et al., EST, 2019):
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Wei, J., Li, Z., Guo, J., Sun, L., Huang, W., Xue, W., Fan, T., and Cribb, M. Satellite-derived 1-km-resolution PM1 concentrations from 2014 to 2018 across China. Environmental Science & Technology, 2019, 53(22), 13265–13274. https://doi.org/10.1021/acs.est.9b03258
More CHAP datasets for different air pollutants are available at: https://weijing-rs.github.io/product.html
Notes
Note that the data are recorded in local time (i.e., Beijing time: GMT+8).
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).
Files
Wei_et_al-EST-2019.pdf
Files
(141.1 MB)
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Additional details
Related works
- References
- Journal article: 10.1021/acs.est.9b03258 (DOI)
References
- Wei, J., Li, Z., Guo, J., Sun, L., Huang, W., Xue, W., Fan, T, and Cribb, M. Satellite-derived 1-km-resolution PM1 concentrations from 2014 to 2018 across China, Environmental Science & Technology, 2019, 53(22), 13265-13274. https://doi.org/10.1021/acs.est.9b03258