LGHAP v2: Global Daily 1-km Gap-free AOD and PM2.5 Grids

LGHAP v2 provides a 22-year-long, gap-free dataset of aerosol optical depth (AOD) and near-surface PM2.5 concentrations with daily 1-km resolution covering global land areas from 2000 to 2021. It was produced by Kaixu Bai of East China Normal University using an improved big earth data analytic framework integrating multimodal AODs and air quality measurements from satellites, ground monitors, and models. The data is archived in NetCDF format with Python, MATLAB, R, and IDL codes provided for reading and visualization.

Use Cases

• Modeling long-term global air pollution trends based on the 22-year daily time series.
• Analyzing spatial patterns of PM2.5 concentrations based on the global 1-km resolution grids.
• Studying aerosol optical depth variability based on gap-free daily AOD data derived from multi-source integration.
• Developing earth system science models based on the high-resolution, gap-free pollutant concentration data.

Strengths

• 22-year temporal coverage from 2000 to 2021.
• High spatial resolution of 1 kilometer for global land areas.
• Gap-free data derived from integration of satellite, ground monitor, and model measurements.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

East China Normal University

Collection Method

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