A Pan-European, Quantile Machine learning (QML) based, Total, Fine-Mode and Coarse-Mode Aerosol Optical Depth dataset (QML AOD))

Given the limitations of existing Aerosol Optical Depth (AOD) datasets and their inability to provide size fraction information, we developed quantile machine learning (QML) models to produce an 18-year (2003-2020) daily AOD dataset for Europe with a high spatial resolution of 0.1°. This new dataset enables monitoring and analysis of both fine-mode (fAOD) and coarse-mode (cAOD) aerosols, providing a valuable tool to investigate their negative impacts on human health and the environment, including climate, visibility, and biogeochemical cycling. We have uploaded three QML AOD datasets in Geotiff format, covering the region from -27° to 72° latitude and from -25° to 45° longitude. These datasets will be useful for researchers and policymakers to better understand the impacts of aerosols on the environment and human health.