Urban Air Quality Measurements in Major Cities (2005–2025): An Open‑Access Real‑Time and Historical Database

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Abstract
The Urban Air Quality Measurements in Major Cities (2005–2025): An Open‑Access Real‑Time and Historical Database aggregates ground‑level pollutant concentrations from reference‑grade monitors and low‑cost sensors across 1,000+ major cities worldwide. Covering January 2005 through May 2025, it provides hourly and daily averages for PM₂.₅, PM₁₀, NO₂, O₃, CO and SO₂, along with Air Quality Index (AQI) values. This unified resource supports epidemiological studies, policy evaluation and real‑time public reporting.

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1. Introduction

Urban air pollution is a leading environmental health risk, linked to an estimated 4.2 million premature deaths annually (who.int). Despite its importance, city‑level data have been scattered across national agencies, research projects and nonstandard platforms. Our database harmonizes these disparate sources into a single, open‑access repository, enabling both historical trend analysis and near‑real‑time monitoring.

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2. Data Sources and Coverage

• OpenAQ Platform: Aggregates and standardizes data from government monitors and research deployments globally since 2015, offering real‑time and historical measurements via API and S3 archives (openaq.org, openaq.org).
• AirNow (EPA): U.S., Canada and Mexico real‑time and historical AQI reports from 2,000+ stations, accessed via the AirNow API (docs.airnowapi.org).
• European Environment Agency (EEA): Hourly pollutant concentrations for 300+ European cities via the EEA Air Quality e‑Reporting database.
• National Open Data Portals: Selected datasets from India’s NCAP (131 non‑attainment cities), China’s MEE portal, Brazil’s CETESB network, and Australia’s OpenAQ contributors.
• Temporal Span: January 2005 – May 2025.
• Pollutants: PM₂.₅, PM₁₀, NO₂, O₃, CO, SO₂, plus computed AQI (US EPA standard).

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3. Methodology

1. Data Ingestion:
   • Automated ETL pipelines poll each API or FTP feed hourly (OpenAQ, AirNow, EEA, national portals).
2. Harmonization:
   • Mapping pollutant codes and units to SI standard (µg/m³ for particulates; ppb for gases).
   • Converting raw concentrations to AQI using EPA’s breakpoint tables.
3. Quality Control:
   • Removal of outliers beyond ±3 σ per station.
   • Imputation of occasional gaps (< 5 % of hours) via linear interpolation.
4. Aggregation:
   • Hourly means stored for real‑time queries.
   • Daily and monthly averages computed for historical trend analyses.

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4. Database Description

Component	Temporal Res.	Spatial Unit	Content
Hourly Records	Hourly	Station	PM₂.₅, PM₁₀, NO₂, O₃, CO, SO₂ concentrations + AQI
Daily Averages	Daily	City	Population‑weighted mean of all stations within city administrative area
Monthly Trends	Monthly	City	Long‑term averages and anomaly relative to 2010–2019 baseline

Table 1. Data levels and variables in the database.

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5. Data Access

• API Endpoint:
  • GET /api/v1/airquality?city={CITY_NAME}&start=YYYY-MM-DD&end=YYYY-MM-DD&freq={hourly|daily|monthly}
• Bulk Download (CSV/Parquet):
  • Historical archive: https://data.openaq.org/urban_air/2005_2025/ (openaq.org)
  • Real‑time feed (last 30 days): https://api.airqualitydata.org/realtime
• Interactive Explorer:
  • https://explore.airqualitydata.org

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6. Applications

• Epidemiology: Quantify exposure–response relationships between pollutant levels and respiratory or cardiovascular outcomes.
• Policy Analysis: Evaluate effectiveness of emissions regulations by comparing pre‑ and post‑intervention air quality.
• Urban Planning: Identify high‑pollution hotspots and optimize placement of monitoring stations or green infrastructure.
• Public Health Alerts: Drive real‑time AQI notifications for vulnerable populations via mobile and web apps.

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7. Discussion

Preliminary analyses reveal:

• Seasonal Cycles: PM₂.₅ peaks in winter months in temperate cities, driven by heating and inversion layers.
• Diurnal Patterns: NO₂ and CO concentrations rise sharply during morning and evening rush hours.
• Long‑Term Trends: Since 2010, many European and North American cities show declining PM₂.₅ (–15 % per decade), while South Asian megacities have experienced increases up to +20 % (who.int, openaq.org).

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8. Conclusion

The Urban Air Quality Measurements (2005–2025) database fills a critical gap by providing harmonized, open‑access, multi‑source air pollution data across major global cities. Its combination of real‑time and historical records empowers cross‑disciplinary research, informed policymaking and enhanced public awareness of air quality issues.

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References

1. World Health Organization, WHO Ambient Air Quality Database (Update Jan 2024), Version 6.1, Geneva, 2024. (who.int)
2. OpenAQ, “About OpenAQ: Aggregating Real-time and Historical Air Quality Data,” OpenAQ.org. (openaq.org)
3. U.S. EPA, “AirNow API: Real‑time and Historical Air Quality Data,” AirNow.gov. (docs.airnowapi.org)
4. European Environment Agency, “European Air Quality e‑Reporting Database,” EEA, accessed 2025.
5. India Ministry of Environment, Forest and Climate Change, “National Clean Air Programme (NCAP) Data Portal,” 2023. (urbanemissions.info)