Cities around the world struggle to find the financial and human capital resources to understandto know more about the levels, sources, and impacts of air pollution. Many of the places with the highest levels of pollution have the least information to work with to know their air quality and manage it accordingly. However, there is a growing number of globally available, publicly funded, open resources for tracking, forecasting, and attributing pollution that can be used to improve local ambient air monitoring.

CityAQ is a partnership with WRI, NASA Global Modeling and Assimilation Office (NASA-GMAO), and 10 cities to develop a global air quality monitoring system that provides cost-effective, reliable and timely data to air quality and health professionals.  

The 10 pilot cities are: Addis Ababa, Ethiopia; Bogota, Colombia; Guadalajara Metro, Mexico; Jakarta, Indonesia; Kigali, Rwanda; Leon-Salamanca-Celaya Metro, Mexico; Monterrey Metro, Mexico; Quito, Ecuador; Rio de Janeiro, Brazil; and Sao Paulo, Brazil.

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 that subnational air quality managers can use.  The CityAQ pilot addresses the following objectives:

  1. 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. 
  2. 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 develop the corrections factors used to generate more accurate local air quality forecasts. 
  3. Develop the data infrastructure to make the localized forecasts available and useable by all world cities. The programming workflow has been 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 as well as platforms such as Resource Watch.
  4. 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. 

Under development is an operational plan for extending the CityAQ forecast methodology to more cities and for creating additional analytical layers such as health warnings, source insights, or others as identified by participating cities