Machine learning algorithm uses high-resolution micro-satellite imagery and weather data to detect levels of harmful air pollution with as much accuracy and more resolution than any current method.
articles
Reef Sand Dissolving Quicker Than Previously Thought, Study Warns
A new international study led by Monash University climate scientists has found reef sand is dissolving much quicker than previously thought due to the impact of microbes.
South Asia Faces Increased Threat Of Extreme Heat, Extreme Pollution, Study Shows
A report authored by a Texas A&M professor details how often people in the region will be threatened by the hazards of pollution and heat.
Segregation and Local Funding Gaps Drive Disparities in Drinking Water
As droughts become more frequent and intense, the fragmentation of water service in the U.S. leaves many households vulnerable to water contamination or loss of service.
New Dual-Action Coating Keeps Bacteria From Cross-Contaminating Fresh Produce
Texas A&M researchers have created a coating that can be applied to surfaces like conveyor belts and collection buckets.
Airborne Particle Levels Plummet in Northern India
Satellite data show that aerosol levels have dropped significantly since the COVID-19 lockdown began.


