GlobalHighPM₂.₅ (2018)

Here is the first big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D1K, M1K, and Y1K) global ground-level PM2.5 dataset over land for the year 2018. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R2) of 0.91 and a root-mean-square error (RMSE) of 9.20 µg m-3 on a daily basis. If you use the GlobalHighPM2.5 dataset in your scientific research, please cite the following reference (Wei et al., NC, 2023): Wei, J., Li, Z., Lyapustin, A., Wang, J., Dubovik, O., Schwartz, J., Sun, L., Li, C., Liu, S., and Zhu, T. First close insight into global daily gapless 1 km PM2.5 pollution, variability, and health impact. Nature Communications, 2023, 14, 8349. https://doi.org/10.1038/s41467-023-43862-3本数据集为首个基于大数据构建的空间全覆盖（空间覆盖率=100%）的2018年全球陆面逐日、逐月、逐年1公里分辨率近地面PM2.5数据集（分别记为D1K、M1K、Y1K）。该数据集品质优异，日尺度下的交叉验证决定系数（cross-validation coefficient of determination，CV-R²）达0.91，均方根误差（root-mean-square error，RMSE）为9.20 μg·m⁻³。 若您在科学研究中使用本GlobalHighPM2.5数据集，请引用如下参考文献（Wei等，《自然通讯》，2023）： Wei, J., Li, Z., Lyapustin, A., Wang, J., Dubovik, O., Schwartz, J., Sun, L., Li, C., Liu, S. 及 Zhu, T. 《首次深入解析全球逐日无间隙1公里分辨率PM2.5污染、变异性与健康影响》，《自然通讯（Nature Communications）》，2023, 14, 8349. https://doi.org/10.1038/s41467-023-43862-3