Monitor air quality index via API

To monitor the Air Quality Index (AQI) via API, you can use several reliable services that provide real-time air pollution data globally or locally. Below is a brief overview of how to do this using a popular free and paid API source, followed by a sample implementation.

Recommended API for Monitoring AQI

1. OpenWeatherMap – Air Pollution API

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

• Data Provided: Real-time AQI, CO, NO, NO₂, O₃, SO₂, PM₂.₅, PM₁₀

• Requirements: Free tier available, requires API key

• Documentation: https://openweathermap.org/api/air-pollution

2. IQAir AirVisual API

• Endpoint: https://api.airvisual.com/v2/city

• Data Provided: AQI (US & CN standards), pollutant concentration, health recommendations

• Requirements: Free tier with limited calls, API key required

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

3. BreezoMeter API

• Endpoint: https://api.breezometer.com/air-quality/v2/current-conditions

• Data Provided: AQI, pollutants, health insights, pollen, and fire alerts

• Requirements: Offers free trial; paid plans available

• Documentation: https://docs.breezometer.com/

Example: Fetch AQI with OpenWeatherMap API using Python

python
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import requests

# Replace with your OpenWeatherMap API Key
API_KEY = 'your_openweathermap_api_key'
LAT = '37.7749'  # Example: San Francisco latitude
LON = '-122.4194'  # Example: San Francisco longitude

url = f"http://api.openweathermap.org/data/2.5/air_pollution?lat={LAT}&lon={LON}&appid={API_KEY}"

response = requests.get(url)
data = response.json()

if response.status_code == 200:
    aqi = data['list'][0]['main']['aqi']
    components = data['list'][0]['components']
    print(f"AQI Level: {aqi}")
    print("Pollutants:")
    for key, value in components.items():
        print(f"  {key}: {value} µg/m³")
else:
    print("Error fetching data:", data)

AQI Levels Reference (OpenWeatherMap)

Notes for Implementation

• Always handle API rate limits and errors gracefully.

• Store and visualize data over time to identify trends.

• Use scheduled scripts or cron jobs to automate periodic checks.

• Optionally integrate with a dashboard (e.g., Grafana) or a mobile app.

Let me know if you want this implemented in JavaScript, Node.js, or integrated with a front-end dashboard.