Multiresolution Analysis of HRRR Meteorological Parameters and GOES-R AOD for Hourly PM_2.5 Prediction.

ABSTRACT: High-resolution, comprehensive exposure data are crucial for accurately estimating the human health impact of PM_2.5. In recent years, satellite remote sensing data have been increasingly utilized in PM_2.5 models to overcome the limited spatial coverage of ground monitoring stations. However, data gaps in satellite-retrieved parameters such as aerosol optical depth (AOD), the sparsity of regulatory air quality monitors for model training, and nonlinear relationships between PM_2.5 and meteorological conditions can affect model performance and cause data gaps in most existing PM_2.5 models. In this study, spatial gaps in AOD obtained from Geostationary Operational Environmental Satellite-16 are filled using Goddard Earth Observing System Composition

SUBMITTER: Pruthi D 

PROVIDER: S-EPMC11562723 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature