3 Questions: What the laws of physics tell us about CO2 removal
In a report on the feasibility of removing carbon dioxide from the atmosphere, physicists say these technologies are “not a magic bullet, but also not a no-go.”
In a report on the feasibility of removing carbon dioxide from the atmosphere, physicists say these technologies are “not a magic bullet, but also not a no-go.”
MIT oceanographer and biogeochemist Andrew Babbin has voyaged around the globe to investigate marine microbes and their influence on ocean health.
Specialist in paleoclimate and geochronology is known for contributions to education and community.
The course challenges students to commercialize technologies and ideas in one whirlwind semester. Alumni of the class have founded more than 150 companies.
Rapid development and deployment of powerful generative AI models comes with environmental consequences, including increased electricity demand and water consumption.
MAD Design Fellow Zane Schemmer writes algorithms that optimize overall function, minimize carbon footprint, and produce a manufacturable design.
New findings illuminate how Prochlorococcus’ nightly “cross-feeding” plays a role in regulating the ocean’s capacity to cycle and store carbon.
The startup Alsym Energy, co-founded by Professor Kripa Varanasi, is hoping its batteries can link renewables with the industrial sector and beyond.
A new electrode design boosts the efficiency of electrochemical reactions that turn carbon dioxide into ethylene and other products.
Using the concept of “outdoor days,” a study shows how global warming will affect people’s ability to work or enjoy recreation outdoors.
MIT researchers identify facility-level factors that could worsen heat impacts for incarcerated people.
Professor Ronald Prinn reflects on how far sustainability has come as a discipline, and where it all began at MIT.
The presence of organic matter is inconclusive, but the rocks could be scientists’ best chance at finding remnants of ancient Martian life.
Knowing where to look for this signal will help researchers identify specific sources of the potent greenhouse gas.
A new downscaling method leverages machine learning to speed up climate model simulations at finer resolutions, making them usable on local levels.