Journal Article Epublish 1 citation
PubMed: 39295744 DOI: 10.1021/acsestair.4c00084
Impact of Model Spatial Resolution on Global Geophysical Satellite-Derived Fine Particulate Matter.
ACS EST Air 1(9):1112-1123
Authors: Dandan Zhang, Randall V Martin, Aaron van Donkelaar, Chi Li, Haihui Zhu, Alexei Lyapustin
Affiliations
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
- Climate and Radiation Laboratory, the National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, Maryland 20771, United States.
Abstract
Global geophysical satellite-derived ambient fine particulate matter (PM 2.5) inference relies upon a geophysical relationship (η) from a chemical transport model to relate satellite retrievals of aerosol optical depth (AOD) to surface PM 2.5. The resolution dependence of simulated η warrants further investigation. In this study, we calculate geophysical PM 2.5 with simulated η from the GEOS-Chem model in its high-performance configuration (GCHP) at cubed-sphere resolutions of C360 (∼25 km) and C48 (∼200 km) and satellite AOD at 0.01° (∼1 km). Annual geophysical PM 2.5 concentrations inferred from satellite AOD and GCHP simulations at ∼25 km and ∼200 km resolutions exhibit remarkable similarity (R 2 = 0.96, slope = 1.03). This similarity in part reflects opposite resolution responses across components with population-weighted normalized mean difference (PW-NMD) increasing by 5% to 11% for primary species while decreasing by -30% to -5% for secondary species at finer resolution. Despite global similarity, our results also identify larger resolution sensitivities of η over isolated pollution sources and mountainous regions, where spatial contrast of aerosol concentration and composition is better represented at fine resolution. Our results highlight the resolution dependence of representing near-surface concentrations and the vertical distribution of chemically different species with implications for inferring ground-level PM 2.5 from columnar AOD.
MeSH
Aerosols, Particulate Matter