GlobalHighPM2.5: Big Data Seamless 1 km Global Ground-level PM2.5 Dataset over Land

GlobalHighPM2.5 is one of the series of long-term, full-coverage, global high-resolution and high-quality datasets of ground-level air pollutants over land (i.e., GlobalHighAirPollutants, GHAP). It is generated from 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. 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 from 2017 to 2022. This dataset yields a high quality with cross-validation coefficient of determination (CV-R2) values of 0.91, 0.97, and 0.98, and root-mean-square errors (RMSEs) of 9.20, 4.15, and 2.77 μg/m3 on the daily, monthly, and annual basises, respectively. Note that this dataset is closed since a new version is published at 10.5281/zenodo.10081359.