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

Global land area daily gap-free aerosol optical depth (AOD) and near-surface PM2.5 concentration grids from 2000 to 2021 at 1-km resolution. The dataset was produced by Kaixu Bai of East China Normal University using an improved big earth data analytic framework integrating multimodal satellite, ground monitor, and numerical model data. It is archived in yearly NetCDF files with provided Python, MATLAB, R, and IDL codes for reading and visualization.

Use Cases

• Modeling long-term global PM2.5 exposure trends based on the 22-year daily time series
• Analyzing spatial patterns of air pollution based on the global 1-km resolution grids
• Validating atmospheric models using the gap-free AOD data derived from multi-source integration
• Assessing regional air quality management strategies based on high-resolution pollutant concentration maps

Strengths

• 22-year temporal coverage from 2000 to 2021
• High spatial resolution of 1 kilometer per grid cell
• Global land area coverage
• Gap-free data achieved via integration of multimodal sources and a tensor construction framework

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 integration of multimodal AODs and air quality measurements from diverse satellites, ground monitors, and numerical models using an attention-reinforced tensor construction framework.

Time Range

2000 to 2021

Geography

Global land area