Combining local monitoring data with satellite modeling to develop city-scale operational air quality forecasts
Cities around the world struggle to find the financial and human capital resources to understand the levels, sources and impacts of air pollution. Many of the places with the highest levels of pollution have the least information on their air quality, preventing them from managing it accordingly. However, there are a growing number of globally available, publicly funded, open resources for tracking, forecasting and attributing pollution. This information can be used to improve local ambient air monitoring, allowing for changes in air pollution that improve lives and protect the environment.
CityAQ is a partnership with WRI, NASA Global Modeling and Assimilation Office (NASA-GMAO) and eight cities to develop a global air quality monitoring system that provides cost-effective, reliable and timely data to air quality and health professionals.
The eight pilot cities are: Addis Ababa, Ethiopia; Bogota, Colombia; Jakarta, Indonesia; Kigali, Rwanda; Leon-Salamanca-Celaya Metro, Mexico; Monterrey Metro, Mexico; Guadalajara Metro, Mexico; and Sao Paulo, Brazil.
*In Quito, Ecuador, CityAQ provided technical support for sharing real-time data.
CityAQ is creating a scalable model for combining locally available air quality monitoring information with the outputs of NASA’s global GEOS Composition Forecast model (GEOS-CF) to develop optimized air quality forecasts for subnational air quality managers. The CityAQ pilot aims to:
- Provide participating cities with useful air quality forecasts. City officials and air quality managers can use this forecast to anticipate air quality events, communicate with stakeholders and more effectively manage local interventions.
- Refine a methodology for combining locally-held information with globally-consistent analysis to offer new tools for city and regional decision-makers. WRI supports cities in preparing and sharing relevant data with NASA and OpenAQ. NASA applies a machine-learning algorithm to local monitoring data and GEOS-CF model outputs to generate more accurate local air quality forecasts.
- Develop the data infrastructure to make localized forecasts available and usable by all world cities. The programming workflow was designed to ingest local monitoring data, combine it with the GEOS-CF model outputs and return the combined forecasts to an Application Programming Interface (API) developed by Development Seed. Where possible, we draw data into platforms such as OpenAQ so that it can be used by others. The API ensures that the forecasts are accessible to all users, including city participants and platforms such as Resource Watch.
- Design a scalable approach for engaging with users to co-create air quality tools that leverage and extend the existing scientific analysis. WRI engages with participating cities to conduct a qualitative assessment of user needs and use cases for locally-corrected forecasts.
CityAQ is also currently developing an operational plan for extending the CityAQ forecast methodology to more cities and creating additional analytical layers such as health warnings, source insights or others as identified by participating cities.