Use Cases

Access to key open data sets (emission sources, air pollution levels, meteorological/atmospheric conditions, etc.) are fundamental to air pollution research. OpenAQ serves as one of these important data sets, used by many scientific researchers to, for example, evaluate and verify air pollution read more...

AQAI is using the OpenAQ platform to develop a machine learning predictive model for air quality showing child population density against regions with pollutant concentrations above WHO-recommended limits. AQAI is one of nine startups (out of 450 applicants) awarded investment funding from the read more...

The Bloomberg Green scoreboard shows which cities have the unhealthiest air, using data from the OpenAQ platform. A screenshot of the live air pollution scoreboard on the Bloomberg Green website Data are needed to slow and stop climate change. Measuring how far we have to go to arrest greenhouse read more...

OpenAQ provides air quality data, specifically PM2.5 measurements, to C40 Cities. This helps them assess the impact of implemented actions, track progress in reducing air pollution, and verify the number of air quality monitors reported by cities. The Problem Almost all urban residents in the read more...

Through OpenAQ’s data platform, Clean Air One Atmosphere is able to provide data access to community members in Ghana and Malawi, helping them learn what they are breathing first-hand and become more environmentally aware. The Problem Air pollution in Africa is a major yet often overlooked public read more...

OpenAQ is proud to be a source of data for the Global Burden of Disease (GBD) report, providing reliable historical and real-time global air quality data to support air pollution interventions. Read more on our blog. Health practitioners and policymakers need accurate information on health trends read more...

Harmonized air quality measurements from the OpenAQ platform aided researchers who were awarded the 2021 Paul Crutzen Publication Award by the journal Atmospheric Chemistry and Physics. The awardees include Christoph A. Keller, Mathew J. Evans, K. Emma Knowland, Christa A. Hasenkopf, Sruti read more...

Data from the OpenAQ platform informed the development of (and continue to feed) a highly accurate air pollution prediction model for Los Angeles County and beyond. The Predicting What We Breathe (PWWB) model provides hourly air quality predictions for six pollutants–PM2.5, ozone, CO, CO2, NO, and read more...

The Sh\\t I Smoke! mobile app uses data from the OpenAQ platform to demonstrate the severity of air pollution by comparing it to cigarette smoking. Sh\\t I Smoke! was developed by Amaury Martiny and Marcelo Coelho. The Problem Air pollution is largely invisible. Most people don’t realize that read more...

For many university students, accessing and working with data from OpenAQ serves as a real-world, hands-on learning experience that increases their data fluency and deepens their understanding of the air pollution crisis. The Problem Students studying environmental health, urban planning, and read more...

Satellites orbiting Earth are able to fill air quality data gaps in regions with little or no ground-level monitoring by applying mathematical models to the atmospheric data that they collect. However, satellite-based observations have limitations and challenges. Ground measurements are needed to read more...