Satellites, mobile-monitoring, and fixed-site measurements to understand local variations in air pollution, globally: the view from Google

Abstract

BACKGROUND AND AIM: Hyperlocal air pollution maps are helpful for cities around the globe to take action on climate and health in the ground in their cities. METHODS: By combining big data -- from ground measurement, both stationary and fixed, to satellites and other data -- hyperlocal air pollution maps and insights can be produced that help cities identify neighborhood hotspots, plan and design their cities to be more healthy, and monitor progress towards environmental goals. RESULTS:We'll look at the latest in cloud geospatial computing for air quality mapping, and how cities are already taking action with the data. CONCLUSIONS:Finally, we'll discuss how this computing can assist global mapping of local air pollution in cities around the world. KEYWORDS: modeling, big data, cloud computing