GlobalHighNO₂: Global Daily Seamless 1 km Ground-Level NO₂ Dataset over Land (2018–Present)

GlobalHighNO2 is part of a series of long-term, seamless, global, high-resolution, and high-quality datasets of air pollutants over land (i.e., GlobalHighAirPollutants, GHAP). 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 gapless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D1K, M1K, and Y1K) global ground-level NO2 dataset over land from 2018 to the present. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R2) of 0.92 and a root-mean-square error (RMSE) of 4.76 µg m-3 on a daily basis. More GHAP datasets for different air pollutants are available at: https://weijing-rs.github.io/product.html