Air Quality Index Forecast

Get accurate 4-day AQI forecasts for any location worldwide. Check air quality predictions to plan your outdoor activities safely.

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AQI Forecast Examples

See sample air quality forecasts for major cities worldwide

New York City

Today
72
Moderate
Tomorrow
68
Moderate
Day 3
45
Good
Day 4
55
Moderate

New York typically experiences moderate air quality due to traffic emissions and regional transport. Summer months may see higher ozone levels, while winter inversions can trap pollutants.

London

Today
42
Good
Tomorrow
58
Moderate
Day 3
63
Moderate
Day 4
48
Good

London's air quality varies with weather patterns and traffic. The ULEZ (Ultra Low Emission Zone) has improved air quality, but PM2.5 and NO2 from vehicles remain concerns during peak hours.

How to Get AQI Forecast

What is AQI Forecast?

Air Quality Index (AQI) forecast predicts future air pollution levels based on meteorological data, emission patterns, and atmospheric models. Our forecasts analyze multiple factors:

  • Weather patterns (wind, temperature, humidity)
  • Traffic and industrial emission cycles
  • Seasonal variations and pollen counts
  • Transboundary pollution transport

Understanding Forecast Accuracy

AQI forecasts are most accurate for the next 24-48 hours, with decreasing precision for days 3-4. Factors affecting accuracy include:

  • Day 1-2: 80-90% accuracy using real-time data
  • Day 3-4: 60-70% accuracy based on weather models
  • Sudden changes: Wildfires, storms can alter predictions
  • Local events: Traffic, construction impact local AQI

Using AQI Forecast for Planning

Check AQI forecasts to plan outdoor activities, especially for sensitive groups:

  • Good (0-50): Perfect for all outdoor activities
  • Moderate (51-100): Generally safe, sensitive individuals be cautious
  • Unhealthy for Sensitive (101-150): Limit prolonged outdoor exertion
  • Unhealthy (151+): Avoid outdoor activities when possible

Data Sources

Our AQI forecasts combine multiple reliable data sources:

  • Government monitoring stations worldwide
  • Satellite air quality observations
  • Weather forecast models (ECMWF, GFS)
  • Machine learning predictions based on historical patterns