源数据介绍：源数据来自于大气成分分析组（Atmospheric Composition Analysis Group)其目前已经将地表PM2.5数据更新至了2020年,源数据为栅格数据，我将数据匹配中国的行政区划矢量数据，处理得到了1998-2000中国省级 地市级 县级三级的年度PM2.5均值数据。（购买使用请拉至页底）
目前ACAG的负责人Prof. Aaron van Donkelaar似乎已经从加拿大达尔豪斯大学跳槽至了美国WUSTL(Washington University in St. Louis)即华大圣路易斯，ACAG的数据也整体在WUSTL网站（Surface PM2.5 | Atmospheric Composition Analysis Group | Washington University in St. Louis (wustl.edu)）上发布。对国内使用该数据的朋友来说，这可能是个好消息，毕竟WUSTL的世界排名和知名度都比较高一些。
数据的具体概况（摘取原网站）：
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.
（摘自Surface PM2.5 | Atmospheric Composition Analysis Group | Washington University in St. Louis (wustl.edu)）
Reference：Aaron van Donkelaar, Melanie S. Hammer, Liam Bindle, Michael Brauer, Jeffery R. Brook, Michael J. Garay, N. Christina Hsu, Olga V. Kalashnikova, Ralph A. Kahn, Colin Lee, Robert C. Levy, Alexei Lyapustin, Andrew M. Sayer and Randall V. Martin (2021). Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty Environmental Science & Technology, 2021, doi:10.1021/acs.est.1c05309.
link(Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty | Environmental Science & Technology (acs.org))
1998-2020县级PM2.5年度均值.zip
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