GlobalHighCO: Big Data Seamless 1 km Global Ground-level CO Dataset over Land

GlobalHighCO 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. 

This 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 CO dataset over land. This dataset yields a high quality with a cross-validation coefficient of determination (CV-R2) of 0.93 and a root-mean-square error (RMSE) of 213.5 µg m-3 on a daily basis.