LGHAP v2: Global Daily 1-km Gap-Free AOD and PM2.5 Grids (2000-2021)

A Long-term Gap-free High-resolution Air Pollutants concentration dataset provides global daily 1-km resolution aerosol optical depth and near-surface PM2.5 concentration grids from 2000 to 2021. The dataset was created by Kaixu Bai of East China Normal University using an analytic framework integrating satellite, ground monitor, and model data. It is archived in NetCDF format with Python, MATLAB, R, and IDL codes provided for reading and visualization.

Use Cases

• Modeling global PM2.5 exposure based on gap-free daily concentration grids
• Analyzing long-term aerosol optical depth trends based on the 22-year time series
• Training geospatial models for air quality prediction based on the 1-km resolution global land data
• Validating satellite-derived air pollution products based on the integrated multimodal data sources

Strengths

• 22-year temporal coverage from 2000 to 2021
• Daily 1-km resolution covering global land area
• Gap-free aerosol optical depth grids derived from multimodal sources

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Last update date is unknown; freshness unverified

Provenance

Source

East China Normal University

Collection Method

Derived via an integration of multimodal AODs and air quality measurements from diverse satellites, ground monitors, and numerical models using an improved big earth data analytic framework.

Time Range

2000 to 2021

Geography

Global land area