Track air quality index from APIs

To track the Air Quality Index (AQI) using APIs, you can use a variety of publicly available data sources. Here’s a quick guide on how to implement AQI tracking using popular APIs:

1. Choose a Suitable AQI API

Here are some commonly used APIs for AQI data:

a. OpenWeatherMap Air Pollution API

• Endpoint: http://api.openweathermap.org/data/2.5/air_pollution

• Features: Provides real-time, forecast, and historical air pollution data.

• Parameters: Requires latitude, longitude, and API key.

• Pollutants: PM2.5, PM10, NO2, CO, O3, SO2.

b. IQAir AirVisual API

• Website: https://www.iqair.com/world-air-quality-api

• Features: Real-time AQI and major pollutant data by city or coordinates.

• Free Tier: Limited access with a free key.

c. World Air Quality Index (WAQI)

• Endpoint: https://api.waqi.info/feed/{location}/?token={API_KEY}

• Data: Real-time AQI by city or geo-location.

• Open Source: Requires attribution.

2. Example Implementation with OpenWeatherMap (Python)

python
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import requests

def get_air_quality(lat, lon, api_key):
    url = "http://api.openweathermap.org/data/2.5/air_pollution"
    params = {
        "lat": lat,
        "lon": lon,
        "appid": api_key
    }
    response = requests.get(url, params=params)
    data = response.json()

    if response.status_code == 200 and "list" in data:
        aqi = data["list"][0]["main"]["aqi"]
        components = data["list"][0]["components"]
        return {
            "AQI": aqi,
            "Components": components
        }
    else:
        return {"error": "Unable to fetch AQI data"}

# Example usage
latitude = 40.7128
longitude = -74.0060
api_key = "YOUR_OPENWEATHERMAP_API_KEY"
print(get_air_quality(latitude, longitude, api_key))

AQI Scale (OpenWeatherMap):
1 = Good, 2 = Fair, 3 = Moderate, 4 = Poor, 5 = Very Poor

3. Scheduled Updates and Visualization

• Use cron jobs (Linux) or task scheduler (Windows) to run the script periodically.

• Store data in a database for historical tracking.

• Visualize with tools like Grafana, Plotly, or Matplotlib.

4. Additional Tips

• Use geo-location APIs to dynamically get coordinates for a user’s location.

• Always cache and handle API rate limits gracefully.

• Consider building alerts when AQI exceeds a set threshold.

Let me know if you’d like a full implementation or integration into a specific platform (like a website, mobile app, or IoT device).