Ambee Global Air Quality Data - Historical | Present | Forecast

**Overview**
Ambee's Air Quality dataset provides calibrated, globally consistent air quality and pollutant data built for health, environmental, and industry. Inputs are sourced from regulatory ground stations across more than 60 countries, fused with satellite observations, and processed through a multi-stage pipeline to deliver harmonized outputs to any global location, including a precise lat/lon or any geographically bounded area such as ZIP or Postal Code, DMA, or MSA.

**Use cases**

- Public health monitoring and respiratory disease risk assessment
- HVAC automation and personalization
- Programmatic advertising
- Healthcare strategy and digital wellness platform development
- Logistics planning and route optimization
- Connected device integration for real-time health alerts

**Product details**

- AQI: Air Quality Index providing standardized pollution level assessment
- PM25: Fine particulate matter concentration < 2.5 micrometers
- PM10: Coarse particulate matter concentration < 10 micrometers
- NO2: Nitrogen dioxide concentration in parts per billion
- SO2: Sulfur dioxide concentration in parts per billion
- CO: Carbon monoxide concentration in parts per million
- OZONE: Ground-level ozone concentration in parts per billion
- city: City name of specified location
- countryCode: 2-letter ISO country code
- placeName: Specific location identifier

**Tables included:**

- AQ_1hr_current_data
- AQ_historical_data
- AQ_historical_data_daily
- AQ_forecast_96hr_data
- AQ_forecast_daily_4_days

**Benefits to Databricks Marketplace users**

- Instantly available: Delivered directly for immediate integration into any analytics, machine learning, or Databricks workflow.
- Comprehensive global network: Data is sourced from regulatory stations across 60+ countries, including Ambee’s own global sensor network, and various satellites, including the ESA Copernicus, NASA Earth Data, and others such as Sentinel-5P, MODIS, and VIIRS.
- Complete pollutant portfolio: All 7 critical air quality metrics (AQI, PM2.5, PM10, NO₂, SO₂, CO, O₃.
- Scientific precision: Region-specific calibration models with anomaly detection and temporal and spatial consistency
- Sequential time series for environmental trend modeling: Harmonized historical-to-present-to-forecast datasets enable consistent training, backtesting, and future projection models.
- Hyperlocal resolution: Data is provided on a scientifically consistent grid that can be mapped to any user-defined location or geography.
- Continuous updates: Real-time ingestion of best-in-class observational data feeds, ensuring the dataset reflects the most current available measurements.