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

22-year-long gap-free aerosol optical depth (AOD) and near-surface PM2.5 concentration data with daily 1-km resolution covering global land areas from 2000 to 2021. The dataset was created by Kaixu Bai of East China Normal University by integrating multimodal AODs and air quality measurements from satellites, ground monitors, and numerical models using an attention-reinforced tensor construction framework. Data for each year 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.
• Validating atmospheric models using the gap-free AOD data derived from multi-source integration.
• Studying environmental health impacts using the near-surface PM2.5 concentration estimates.

Strengths

• 22 years of daily temporal coverage from 2000 to 2021.
• Global land coverage at a 1-kilometer spatial resolution.
• Data is gap-free, addressing a common limitation in remote sensing products.

Limitations

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

Provenance

Source

Kaixu Bai, 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