Methodology — Quanteta Air Quality Database
This page describes how we collect, process, and score data. All scores are calculated metrics derived from public data sources — never editorial opinions.
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Scoring Methodology
Quanteta provides proprietary scores derived from combining multiple data points. These are calculated metrics, not editorial opinions.
Air Quality Score (0-100)
Composite score based on AQI level and individual pollutant concentrations. Higher = cleaner air.
Breathability Score (0-100)
Measures how comfortable outdoor air is for breathing. Factors in PM2.5, O3, and NO2 relative to WHO guidelines.
Future Scores
Season Stability, Trend Momentum, and Nomad Score require 30+ days of historical data and will be activated as data accumulates.
Data Sources
- Air Quality Data
- Open-Meteo API — Provides real-time pollutant concentrations (PM2.5, PM10, O3, NO2, SO2, CO) from global monitoring networks.
- AQI Calculation
- US AQI and EU AQI are calculated from pollutant concentrations using official EPA and EEA breakpoint tables.
- Update Frequency
- Hourly via automated collectors.
- Current Coverage
- cities across multiple continents.
Update Frequency
Hourly via automated collectors.. Pages are regenerated only when underlying data changes. The "Last Updated" timestamp always reflects actual data changes, never cosmetic edits.
Data Quality
- Validation: All incoming data is validated against expected ranges and types before storage.
- Cross-referencing: Where multiple sources are available, data points are cross-validated for consistency.
- Anomaly detection: Sudden large deviations from historical norms are flagged for review.
- Automated collection: Data is collected by automated scripts (cron jobs) to eliminate manual entry errors.
- Single source of truth: JSON-LD structured data and HTML content are generated from the same variables to prevent mismatches.
Limitations & Caveats
- All data depends on the accuracy and availability of upstream API sources.
- Scores are descriptive metrics based on available data, not predictions or recommendations.
- Coverage may vary — not all entities have complete data for all fields.
- Historical data depth increases over time; some time-series metrics require minimum data accumulation periods.
- API rate limits or outages may temporarily affect data freshness.