Air quality data

Air quality data measures the concentration of pollutants such as fine particulate matter (PM2.5 and PM10), nitrogen dioxide, ozone, sulphur dioxide and carbon monoxide, and summarises them into indices. Buyers include health and insurance analysts studying population exposure, property and travel platforms, smart city and mobility teams, researchers and companies monitoring the impact of their own sites.

Typical fields

• Station ID or grid cell, with coordinates
• Timestamp and averaging period (hourly or daily)
• Pollutant concentrations in µg/m³ or ppb
• Air quality index value and category
• Source flag: regulatory monitor, low-cost sensor, satellite or model
• Forecast lead time where forecasts are included

Sources and methods

Regulatory monitoring networks run by national and city agencies provide the most reliable measurements, but stations are sparse. Low-cost sensor networks add density but need calibration and are sensitive to humidity. Satellites observe column concentrations of gases such as nitrogen dioxide, and atmospheric chemistry models, including the Copernicus Atmosphere Monitoring Service, fill gaps and produce forecasts. Commercial datasets usually blend these sources into a continuous grid.

Delivery and pricing

Current conditions and forecasts are sold through APIs priced by calls or locations. Historical archives are sold per city, country or grid extent, usually as CSV or Parquet. Price depends on spatial resolution, depth of history and whether forecasts are included.

Before you buy

• Ask which index definition is used, because national indices differ.
• Check how low-cost sensor readings are calibrated and flagged.
• Confirm units and averaging periods for each pollutant.
• Review coverage outside major cities.
• Check validation against regulatory monitors.