10.1 Surface PM2.5 Global Estimates (V4.GL.02)
| metadata_field | |
|---|---|
| shortname | GlobalGWR_PM25_V4GL02 |
| title | Surface PM2.5 Global Estimates (V4.GL.02) |
| creator | A. van Donkelaar |
| contact_email | car.data@sydney.edu.au |
| abstract |
These data are estimated ground-level fine particulate matter (PM2.5) 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 global ground-based observations of PM2.5 using Geographically Weighted Regression (GWR) as detailed in the below reference. References: van Donkelaar, A., R.V Martin, M.Brauer, N. C. Hsu, R. A. Kahn, R. C Levy, A. Lyapustin, A. M. Sayer, and D. M Winker, Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors, Environ. Sci. Technol, doi: 10.1021/acs.est.5b05833, 2016. [Link] Estimates prior to 2008 incorporate temporal information from: Boys, B.L., Martin, R.V., van Donkelaar, A., MacDonell, R., Hsu, N.C., Cooper, M.J., Yantosca,R.M., Lu, Z., Streets,D.G., Zhang,Q., Wang,S., Fifteen-year global time series of satellite-derived fine particulate matter, Environ. Sci. Technol, 10.1021/es502113p, 2014. [Link] van Donkelaar, A., R. V. Martin, M. Brauer and B. L. Boys, Global fine particulate matter concentrations from satellite for long-term exposure assessment, Environmental Health Perspectives, 123, 135-143, DOI:10.1289/ehp.1408646, 2015. |
| additional_metadata | /home/public_share_data/ResearchData_CAR/Environment_General/Air_pollution_model_GlobalGWR_PM25/GlobalGWR_PM25_V4GL02 |
| alternate_identifier | https://cloudstor.aarnet.edu.au/plus/f/1748711523 |
| associated_party | Ivan Hanigan [role: creation of publishable derived data from data provided] |
| access_rules | |
| Recommended Citation | Hanigan, I.C., 2018. Surface PM2.5 Global Estimates (V4.GL.02). Derived from Aerosol Optical Depth (AOD) data from the NASA MODIS, MISR, and SeaWIFS instruments using the GEOS-Chem chemical transport model, calibrated to global ground-based observations of PM2.5 using Geographically Weighted Regression (GWR). Retrieved from Centre for Air pollution, energy, and health Research. https://cloudstor.aarnet.edu.au/plus/f/1748711523 |
| licence_code | other |
| accessibility | CAR |