Near-Real-Time Satellite Estimates of Surface PM_2.5 Concentrations in Africa

In collaboration with Google, Inc., Sonoma Technology scientists developed a new air quality data set for UNEP’s GEMS Air initiative. The new approach provides daily global estimates of ground-level fine particulate matter (PM_2.5) concentrations with very little delay by harnessing the massive computational power of the cloud-based Google Earth Engine. We combine satellite observations with an operational chemical transport model to estimate ground-level pollution in Africa. The data set shows promise to support air quality planning at regional and national scales, and can support current and historical air pollution event analysis.<br>
In many parts of the world, air quality planning and management capabilities are limited by a lack of timely air quality observations. This is often the case in locations where ambient air quality conditions are worst. Globally, poor air quality is estimated to lead to 4.5 million premature deaths annually due to ambient exposure to PM_2.5, and yet available data on air pollution remains scant or non-existent for many locations, including much of Africa. This approach provides timely data that is critically needed to fill that data gap, enhance air quality management, and improve health.