Satellite-Derived Surface PM2.5 (ACAG/WashU)

Satellite-Derived Surface PM2.5 (ACAG/WashU)

MH Subset Needed

Global annual mean surface PM2.5 concentrations at 0.01° (~1km) resolution derived from satellite AOD, GEOS-Chem model, and ground stations. Maharashtra subset maps air pollution exposure across all districts, enabling health impact assessment.

Build an air quality exposure map for Maharashtra showing population-weighted PM2.5 levels at village resolution.
Maharashtra subset not yet extracted. This is a global dataset that contains data covering Maharashtra. A regional subset can be extracted by filtering on geographic coordinates or administrative boundaries.

Quick Start

import xarray as xr
# Download from https://sites.wustl.edu/acag/datasets/
# ds = xr.open_dataset('acag_pm25.nc')
# mh = ds.sel(lat=slice(15.5, 22.5), lon=slice(72.5, 81))
print('ACAG PM2.5 data: https://sites.wustl.edu/acag/datasets/')
Modality
raster-gridded
Size
~2 GB (global), ~20 MB (MH subset)
License
Format
NetCDF / GeoTIFF
Language
en
Update Frequency
annual
Organization
Washington University in St. Louis (ACAG)

Schema

FieldTypeDescription
latitudefloatGrid cell latitude (0.01° resolution)
longitudefloatGrid cell longitude (0.01° resolution)
PM25floatAnnual mean surface PM2.5 concentration (µg/m³)

Build With This

Create a health risk estimator correlating PM2.5 exposure with respiratory disease rates across Maharashtra districts
Develop a clean air corridor planner for Maharashtra urban areas using high-resolution PM2.5 surface data
Build a school air quality alert system that identifies Maharashtra schools in high-pollution zones

AI Use Cases

Air pollution health impact modelingRespiratory disease burden estimation by districtUrban planning and green corridor designSchool and hospital site selectionEnvironmental justice analysis
Last verified: 2026-03-07