SatPM V6.GL.03
This version is recommended for users interested in our most state-of-the-science global algorithm, and is available for 1998-2024
We estimate annual and monthly ground-level fine particulate matter (PM₂.₅) for 1998-2024 by combining Aerosol Optical Depth (AOD) retrievals (Dark Target, Deep Blue, MAIAC) that make use of observations from numerous satellite-based NASA instruments (MODIS/Terra, MODIS/Aqua, MISR/Terra, SeaWiFS/SeaStar, VIIRS/SNPP, and VIIRS/NOAA20) with the GEOS-Chem chemical transport model, and subsequently calibrating to global ground-based observations using a residual Convolutional Neural Network (CNN), as detailed in the below reference for SatPM V6.GL.01. SatPM V6.GL.03 follows the methodology of V6.GL.01 and V6.GL.02.04, but updates the ground-based observations used to calibrate the geophysical PM₂.₅ estimates for the entire time series, extends temporal coverage through 1998 – 2024, and includes retrievals from the SNPP VIIRS instrument. Also, the GEOS-Chem information (and the geophysical PM2.5) includes the latest updates on dust size and distribution.
Reference:
Shen, S. Li, C. van Donkelaar, A. Jacobs, N. Wang, C. Martin, R. V.: Enhancing Global Estimation of Fine Particulate Matter Concentrations by Including Geophysical a Priori Information in Deep Learning. (2024) ACS ES&T Air. DOI: 10.1021/acsestair.3c00054 [Link]
Scientific Datasets:
Annual and monthly datasets are provided in NetCDF [.nc] format. Gridded files use the WGS84 projection.
Note that these estimates are primarily intended to aid in large-scale studies. Annual and coarse-resolution averages correspond to a simple mean of within-grid values. Gridded datasets are provided to allow users to agglomerate data as best meets their particular needs. High-resolution (0.01° × 0.01°) datasets are gridded at the finest resolution of the information sources that were incorporated, but are unlikely to fully resolve PM₂.₅ gradients at the gridded resolution due to the influence of information sources at coarser resolution.
Annual and monthly mean PM₂.₅ [µg/m3] at 0.01° × 0.01°:
[https://wustl.box.com/v/V6GL03-FineResolution]
Annual and monthly mean PM₂.₅ [µg/m3] at 0.1° × 0.1°:
[https://wustl.app.box.com/v/V6GL03-CoarseResolution]
Processed Datasets:
These summary files are processed from the Scientific Datasets above for ease of accessibility. Population-weighted estimates and total population describe only those people covered by the SatPM V6.GL.03 dataset and are provided by GPWv4. Country borders are defined following GAD3.6.
Annual Global country-level mean PM₂.₅
Annual Canada provincial-level mean PM₂.₅
Annual China regional-level mean PM₂.₅
Annual India regional-level mean PM₂.₅
Annual United States state-level mean PM₂.₅
SatPM₂.₅ V6.GL.03 are licensed under CC BY 4.0