ChinaHighPMC: Daily Seamless 1 km Ground-Level PM₂.₅ Composition Dataset for China (2000–Present)

ChinaHighPMC 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 PM_2.5 chemical composition (i.e., SO₄^2-, NO₃^-, NH₄⁺, and Cl^-) dataset for Eastern China from 2013 to 2020. This dataset exhibits high quality, with cross-validation coefficients of determination (CV-R²) of 0.74, 0.75, 0.71, and 0.66, and root-mean-square errors (RMSEs) of 6.0, 6.6, 4.3, and 2.3 µg m^-3 for SO₄^2-, NO₃^-, NH₄⁺, and Cl^-, respectively, on a daily basis.

If you use the ChinaHighPMC dataset in your scientific research, please cite the following reference (Wei et al., EST, 2023):

• Wei, J., Li, Z., Chen, X., Li, C., Sun, Y., Wang, J., Lyapustin, A., Brasseur, G., Jiang, M., Sun, L., Wang, T., Jung, C., Qiu, B., Fang, C., Liu, X., Hao, J., Wang, Y., Zhan, M., Song, X., and Liu, Y. Separating daily 1 km PM2.5 inorganic chemical composition in China since 2000 via deep learning integrating ground, satellite, and model data. Environmental Science & Technology, 2023, 57(46), 18282–18295. https://doi.org/10.1021/acs.est.3c00272

More CHAP datasets for different air pollutants are available at: https://weijing-rs.github.io/product.html