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

LGHAP v2 provides 22 years of gap-free daily aerosol optical depth (AOD) and near-surface PM2.5 concentration data at a 1-kilometer resolution covering global land areas from 2000 to 2021. The dataset was created by Kaixu Bai at East China Normal University using an improved big earth data analytic framework integrating satellite, ground monitor, and model data. Data is archived in NetCDF format with Python, MATLAB, R, and IDL codes provided 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 aerosol pollution at a 1-kilometer resolution.
• Validating regional air quality models using the gap-free, multi-source integrated data.
• Studying the relationship between satellite-derived AOD and ground-level PM2.5 concentrations.

Strengths

• 22-year temporal coverage from 2000 to 2021 provides a long-term record.
• Daily data at a 1-kilometer spatial resolution offers high granularity.
• Data is gap-free, addressing a common limitation in remote sensing products.
• Integration of multimodal sources (satellites, ground monitors, models) likely improves accuracy.

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

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

Time Range

2000 to 2021

Freshness

null

Geography

Global land area