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Published March 26, 2021 | Version 1 (GeoTIFF)
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ChinaHighCO: Big Data Seamless 10 km Ground-level CO dataset for China

  • 1. University of Maryland

Description

ChinaHighCO 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 CO dataset in China from 2013 to 2020. This dataset yields a high quality with a cross-validation coefficient of determination (CV-R2) of 0.80, a root-mean-square error (RMSE) of 0.29 mg m-3, and a mean absolute error (MAE) of 0.16 mg m-3 on a daily basis.

If you use the ChinaHighCO dataset for related scientific research, please cite the corresponding reference (Wei et al., ACP, 2023):

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

Notes

Note that this dataset is continuously updated, and if you want to apply for more data or have any questions, please contact me (Email: weijing_rs@163.com; weijing@umd.edu).

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Additional details

Related works

Is referenced by
Journal article: 10.5194/acp-23-1511-2023 (DOI)

References

  • 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