Daily Concentrations of PM2.5 in the Valencian Community Using Random Forest for the Period 2008–2018

Abstract

Fine particulate matter (PM2.5) is a global problem that affects the population health and contributes to climate change. Remote sensing provides useful information for the development of air quality models. This work aims to obtain a daily model of PM2.5 levels in the Valencian Community with a resolution of 1 km for the period 2008–2018. MODIS-MAIAC images, meteorological parameters of the MERRA-2 project, land cover information and ground level measurements of PM2.5 levels were analysed with Random Forest. The verification of the model was carried out using cross-validation repeated ten times, and an evaluation of a test set with 20% of the collected information. The final model was used to generate maps of the daily concentrations of PM2.5 for the area of the Valencian Community throughout the study period.