ChinaHighPM2.5: Annual 1-km PM2.5 Estimates for Eastern China, 2000-2020

Annual 0.01-degree gridded ground-level PM2.5 estimates for Eastern China from 2000 to 2020, with data for 2000 covering March to December. Jing Wei from the University of Maryland, College Park generated the dataset using MODIS/Terra+Aqua MAIAC AOD products and auxiliary data with artificial intelligence. The annual estimates show high correlation with ground-based measurements (R² = 0.94) and an average root-mean-square error of 5.07 µg m⁻³.

Use Cases

• Analyzing long-term trends in fine particulate matter pollution based on the 21-year time series from 2000 to 2020.
• Modeling population exposure to PM2.5 based on the high-resolution 1-km gridded data for Eastern China.
• Validating atmospheric chemistry and air quality models based on the satellite-derived estimates with ground-truth correlation metrics.
• Assessing the health and environmental impacts of air pollution policies based on the spatiotemporal PM2.5 concentration maps.

Strengths

• Covers a 21-year period from 2000 to 2020, providing a long-term record.
• High spatial resolution of approximately 1 km (0.01-degree grid).
• Strong validation performance with an R² of 0.94 and RMSE of 5.07 µg m⁻³ against ground measurements.

Limitations

• Row count and file size are unknown, which may limit suitability assessment.
• The dataset is noted as closed since a new version was published, suggesting this version may not be the latest.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

University of Maryland, College Park

Collection Method

Generated from MODIS/Terra+Aqua MAIAC AOD products and auxiliary data (ground measurements, satellite products, reanalysis, model simulations) using artificial intelligence.

Time Range

2000 to 2020

Geography

Eastern China