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AirHistory
Measurement & Monitoring

Air Quality Forecast

Predictions of future AQI levels issued by state and local agencies, typically covering 1-2 days ahead.

Detailed Explanation

Air quality forecasts are predictions of pollutant concentrations and AQI values for the near future, typically covering the current day and the next one or two days. These forecasts are produced by state and local air quality agencies using a combination of meteorological models, historical patterns, satellite data, and ground-level monitoring data. Forecast accuracy varies by pollutant and season — ozone forecasts tend to be more reliable because ozone formation follows predictable temperature and sunlight patterns, while PM2.5 forecasts are more challenging because wildfire smoke and other events can cause rapid, unpredictable spikes. The EPA's AirNow system (airnow.gov) aggregates forecasts from agencies across the country and provides real-time AQI maps and forecasts to the public. Many cities and states issue Air Quality Action Days when forecasts predict AQI will reach "Unhealthy for Sensitive Groups" or higher, triggering public advisories and sometimes voluntary or mandatory emission reduction measures. AirHistory complements daily forecasts by providing the long-term historical context — knowing your city's 10-year trend, typical seasonal patterns, and dominant pollutant helps you interpret daily forecasts and understand whether a given reading is unusual or part of a chronic pattern. While AirHistory does not provide real-time or forecast data, its historical analysis helps contextualize the daily readings available from AirNow and local agencies.

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Frequently Asked Questions

Predictions of future AQI levels issued by state and local agencies, typically covering 1-2 days ahead.

Air quality forecasts are predictions of pollutant concentrations and AQI values for the near future, typically covering the current day and the next one or two days. These forecasts are produced by state and local air quality agencies using a combination of meteorological models, historical patterns, satellite data, and ground-level monitoring data. Forecast accuracy varies by pollutant and season — ozone forecasts tend to be more reliable because ozone formation follows predictable temperature and sunlight patterns, while PM2.5 forecasts are more challenging because wildfire smoke and other events can cause rapid, unpredictable spikes.