V5.NA.03
North American Regional Estimates
- retired -
We estimate ground-level fine particulate matter (PM₂.₅) total and compositional mass concentrations over North America by combining Aerosol Optical Depth (AOD) retrievals from the NASA MODIS, MISR, and SeaWIFS instruments with the GEOS-Chem chemical transport model, and subsequently calibrated to regional ground-based observations of both total and compositional mass using Geographically Weighted Regression (GWR) as detailed in the below reference for V4.NA.02. V4.NA.03 further modified the V4.NA.02 GWR method with additional developments as part of the MAPLE (Mortality–Air Pollution Associations in Low-Exposure Environments) project, and uses V4.GL.03 PM₂.₅ estimates as geophysical input. The GWR method of individual components remains unchanged from V4.NA.02, but are provided are percentages to ensure mass closure and recommended to be applied to the V4.NA.03 total PM₂.₅.
Reference:
Hammer, M. S.; van Donkelaar, A.; Li, C.; Lyapustin, A.; Sayer, A. M.; Hsu, N. C.; Levy, R. C.; Garay, M. J.; Kalashnikova, O. V.; Kahn, R. A.; Brauer, M.; Apte, J. S.; Henze, D. K.; Zhang, L.; Zhang, Q.; Ford, B.; Pierce, J. R.; and Martin, R. V., Global Estimates and Long-Term Trends of Fine Particulate Matter Concentrations (1998-2018)., Environ. Sci. Technol, doi: 10.1021/acs.est.0c01764, 2020. [Link]
van Donkelaar, A., R. V. Martin, et al. (2019). Regional Estimates of Chemical Composition of Fine Particulate Matter using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors. Environmental Science & Technology, 2019, doi:10.1021/acs.est.8b06392. [Link]
Scientific Datasets:
Annual datasets are provided in NetCDF [.nc] or a zipped ArcGIS-compatible ASCII [.asc.zip] file. Note that the unzipped ASCII files can be cumbersome. Gridded files use the WGS84 projection. Compositional estimates, based on V4.NA.02, are provided for sulfate (SO4), nitrate (NO3), ammonium (NH4), organic matter (OM), black carbon (BC), mineral dust (DUST), and sea-salt (SS). A slight change in file name has been included for 2017, corresponding to minor internal changes compared to earlier years. Overall, however, the dataset is consistent throughout its entire time period and can be appropriately used for trend analysis. Please contact our Support Team (support@satpm.org) for further information.
Note that these estimates are primarily intended to aid in large-scale studies. Gridded datasets are provided to allow users to agglomerate data as best meets their particular needs. Datasets are gridded at the finest resolution of the information sources that were incorporated (0.01° × 0.01°), but do not fully resolve PM₂.₅ gradients at the gridded resolution due to influence by information sources at coarser resolution.
Annual mean PM₂.₅ [µg/m3]: [.nc] [.asc.zip]
Annual mean SO4^2+ [%]: [.nc] [.asc.zip]
Annual mean NO3^– [%]: [.nc] [.asc.zip]
Annual mean NH4^+ [%]: [.nc] [.asc.zip]
Annual mean OM [%]: [.nc] [.asc.zip]
Annual mean BC [%]: [.nc] [.asc.zip]
Annual mean SOIL [%]: [.nc] [.asc.zip]
Annual mean SS [%]: [.nc] [.asc.zip]
Monthly V4.NA.03 total mass PM₂.₅ is available from: https://wustl.box.com/v/ACAG-V4NA03-PM25.
Monthly V4.NA.02 PM₂.₅ composition described in van Donkelaar et al., ES&T 2019 are also available [here]. Percentages are denoted with a ‘p’ after component identifiers within filenames and recommended to be used with the V4.NA.03 dataset. Users are reminded that these datasets are intended for long-term, large-scale studies. Increased uncertainties are expected when used at finer spatial/temporal resolution.
SatPM₂.₅ data V4.NA.03 are licensed under CC BY 4.0