Geng et al.: Random forest models for PM2.5 speciation using MISR data
Random forest models were developed to predict ground-level daily PM2.5 speciation concentrations in California from MISR fractional AODs and other supporting data such as ground measurements, chemical transport model simulations, land use variables and meteorological fields. Sensitivity tests were also conducted to explore the influence of variable selection on model performance. Results shows...