GHAP Daily PM2.5 (1km, 2017-2022)

GHAP Daily PM2.5 (1km, 2017-2022)

MH Subset Needed

Global High Air Pollutants dataset providing gapless daily PM2.5 concentrations at 1km resolution from 2017-2022 using machine learning and big data. Maharashtra subset enables day-level air quality tracking across every taluka.

Build a hyper-local air pollution exposure model for Maharashtra using 1km daily PM2.5 estimates.
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.
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Quick Start

import xarray as xr
# Download from https://zenodo.org/records/
print('GHAP PM2.5 Daily 1km: Check Zenodo for latest release')
print('High-resolution daily PM2.5 estimates globally')
Modality
raster-gridded
Size
~500 GB (global), ~5 GB (MH subset)
License
Format
GeoTIFF / NetCDF
Language
en
Update Frequency
static
Organization
Wuhan University / Multiple
Category
environment-climate-disaster

Schema

FieldTypeDescription
pm25floatDaily PM2.5 concentration in ug/m3
latitudefloatLatitude at 1km resolution
longitudefloatLongitude at 1km resolution
datedateDate of estimate

Build With This

Create a school-level air quality assessment for every school in Maharashtra using 1km PM2.5 data
Develop a long-term health impact model correlating 1km PM2.5 exposure with disease rates in Maharashtra
Build a real estate air quality score generator that rates Maharashtra neighborhoods by pollution exposure

AI Use Cases

Daily air quality forecastingPollution source attributionHealth exposure assessment by localityCrop damage from air pollutionPolicy impact evaluation (e.g., stubble burning bans)
Last verified: 2026-03-07