GlobalHighNO2: Big Data Seamless 1 km Global Ground-level NO2 Dataset over Land

GlobalHighNO2 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 NO2 dataset over land. This dataset yields a high quality with a cross-validation coefficient of determination (CV-R2) of 0.86 and a root-mean-square error (RMSE) of 6.7 µg m-3 on a daily basis.

All the data will be made public online once our paper is accepted, and if you want to use the GlobalHighNO2 dataset for related scientific research, please contact us (Email: [e-mail]; [e-mail]).