A complicated future for a methane-cleansing molecule
A new model shows how levels of the “atmosphere’s detergent” may rise and fall in response to climate change.
A new model shows how levels of the “atmosphere’s detergent” may rise and fall in response to climate change.
MIT researchers uncovered the roles of bacterial species from the environment as they consume biodegradable plastic.
New research by MIT geophysicists could assist efforts to remove carbon from the atmosphere and store it underground.
While some N2O is produced naturally at the plant root, agricultural practices can increase its levels, to the detriment of some microbes that support plant growth.
Through research with MIT D-Lab, MIT engineering student Kiyoko “Kik” Hayano worked with Keo Fish Farms to build a model for regenerative water systems.
Cross-border collaborations are seen as a key to success for the MIT Leventhal Center’s Mexico City Initiative.
MIT Energy Initiative researchers calculated the economic and environmental impact of future ammonia energy production and trade pathways.
While the growing energy demands of AI are worrying, some techniques can also help make power grids cleaner and more efficient.
Cutting air travel and purchasing renewable energy can lead to different effects on overall air quality, even while achieving the same CO2 reduction, new research shows.
A new study by MIT researchers analyzes different nuclear waste management strategies, with a focus on the radionuclide iodine-129.
MIT PhD student and CSAIL researcher Justin Kay describes his work combining AI and computer vision systems to monitor the ecosystems that support our planet.
In “Carbon Removal,” Howard Herzog and Niall MacDowell assess proposed methods of removing carbon already in the atmosphere as a means of mitigating climate change.
Proposed system would combine two kinds of plants, creating greater efficiency and lowering costs while curbing climate-changing emissions.
Analysis from MIT’s Center for Transportation and Logistics finds companies are still acting to reduce emissions, but often lag in measurement techniques.
New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.