Georgia Tech researchers introduced a groundbreaking machine learning technique to improve the assessment and analysis of declining oxygen levels in the ocean.

Zhigang Peng and graduate students Phuc Mach and Chang Ding are using small seismic sensors to better understand just how, why, and when certain earthquakes are occurring.

Led by School of Earth and Atmospheric Sciences Professor Greg Huey, the NSF RAPID grant is for analyzing air chemistry data collected during a three-week span when a chemical plume impacted the Atlanta area.

In fact, every decade since 1984, when satellite recordkeeping of ocean temperatures started, has been warmer than the previous one.

A Georgia Tech-led review paper recently published in Nature Reviews Physics is exploring the ways machine learning is revolutionizing the field of climate physics — and the role human scientists might play.

The fires enabled the first real-time data on airborne lead, thanks to a pioneering air quality measurement network.