Air pollution is the world's largest environmental health risk. An estimated 7 million premature deaths annually. The monitoring infrastructure exists: government stations, low-cost sensor networks like PurpleAir, satellite atmospheric measurements, and industrial emission tracking systems. But these networks don't talk to each other. A PurpleAir sensor three blocks from an EPA monitoring station operates in a completely separate data universe.

The result is a patchwork. Dense coverage in wealthy urban areas, almost nothing in the developing regions where pollution kills the most people. When coverage does exist, correlating air quality readings with industrial activity, traffic patterns, and weather data to identify pollution sources requires crossing three or four separate databases that use different formats, update at different intervals, and were never designed to work together.

AETHER aggregates these fragmented networks into a single coherent view. It identifies pollution sources by correlating sensor data with industrial and traffic patterns. It generates real-time health advisories for communities. It maps coverage gaps to show where new sensors would have the most impact. And it produces policy-ready reports that connect air quality data to health outcomes in a format decision-makers can actually use.