Documentation for the Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), 1998-2019, V4.GL.03

The Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), 1998-2019, V4.GL.03 consists of annual concentrations (micrograms per cubic meter) of all composition ground-level fine particulate matter (PM2.5). This data set combines AOD retrievals from multiple satellite algorithms including the NASA MODerate resolution Imaging Spectroradiometer Collection 6.1 (MODIS C6.1), Multi-angle Imaging SpectroRadiometer Version 23 (MISRv23), MODIS Multi-Angle Implementation of Atmospheric Correction Collection 6 (MAIAC C6), and the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) Deep Blue Version 4. The GEOS-Chem chemical transport model is used to relate this total column measure of aerosol to near-surface PM2.5 concentration. Geographically Weighted Regression (GWR) is used with global ground-based measurements from the World Health Organization (WHO) database to predict and adjust for the residual PM2.5 bias per grid cell in the initial satellite-derived values.These estimates are primarily intended to aid in large-scale studies. Gridded data sets are provided at a resolution of 0.01 degrees to allow users to agglomerate data as best meets their particular needs. Data sets are gridded at the finest resolution of the information sources that were incorporated, but do not fully resolve PM2.5 gradients at the gridded resolution due to influence by information sources at coarser resolution. The data are distributed as GeoTIFF files and are in WGS84 projection.

本数据集为1998-2019年V4.GL.03版基于MODIS、MISR与SeaWiFS气溶胶光学厚度（Aerosol Optical Depth, AOD）的全球年度PM2.5网格数据集，包含所有组分的近地面细颗粒物（PM2.5）年度浓度数据，单位为微克每立方米。本数据集整合了多颗卫星传感器的气溶胶光学厚度反演结果，涵盖美国国家航空航天局（National Aeronautics and Space Administration, NASA）中分辨率成像光谱仪6.1版（MODIS C6.1）、多角度成像光谱辐射计23版（MISRv23）、MODIS大气校正多角度实现方案6版（MAIAC C6）以及宽视场海洋观测传感器（Sea-Viewing Wide Field-of-View Sensor, SeaWiFS）深蓝算法4版的数据。本研究采用GEOS-Chem化学传输模型，将气溶胶整柱含量反演结果与近地面PM2.5浓度建立关联。同时结合世界卫生组织（World Health Organization, WHO）数据库的全球地面实测数据，采用地理加权回归（Geographically Weighted Regression, GWR）对卫星反演初始值中每个网格单元的PM2.5残余偏差进行校正与预测。该数据集主要服务于大尺度相关研究。数据集采用0.01度的空间分辨率进行网格化处理，以便用户可根据自身研究需求灵活聚合数据。数据集的网格化分辨率采用整合数据源中的最高分辨率，但由于受低分辨率数据源的影响，无法完全还原该网格尺度下的PM2.5浓度梯度。数据集以GeoTIFF格式存储，采用WGS84坐标系。