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: ORNL climate modeling expertise contributed to an AI-backed model that assesses global emissions of ammonia from croplands now and in a warmer future, while identifying mitigation strategies. This map highlights croplands around the world. Credit: U.S. Geological Survey

ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.

Using a better modeling framework, with data collected from Mississippi Delta marshes, scientists are able to improve the predictions of methane and other greenhouse gas emissions. Credit: Matthew Berens/ORNL, U.S Dept. of Energy

Scientists at the Department of Energy’s Oak Ridge National Laboratory are using a new modeling framework in conjunction with data collected from marshes in the Mississippi Delta to improve predictions of climate-warming methane and nitrous oxide

Researchers used the open-source Community Earth System Model to simulate the effects that extreme climatic conditions have on processes like land carbon storage. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Researchers from Oak Ridge National Laboratory and Northeastern University modeled how extreme conditions in a changing climate affect the land’s ability to absorb atmospheric carbon — a key process for mitigating human-caused emissions. They found that 88% of Earth’s regions could become carbon emitters by the end of the 21st century. 

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Global carbon emissions from inland waters such as lakes, rivers, streams and ponds are being undercounted by about 13% and will likely continue to rise given climate events and land use changes, ORNL scientists found.

Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions. Credit: Getty Images

Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.

Physicist Charles Havener uses the NASA end station at ORNL’s Multicharged Ion Research Facility to simulate the origin of X-ray emissions from space. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Scientists are using Oak Ridge National Laboratory’s Multicharged Ion Research Facility to simulate the cosmic origin of X-ray emissions resulting when highly charged ions collide with neutral atoms and molecules, such as helium and gaseous hydrogen.

Oak Ridge National Laboratory researchers built an Earth-to-space communications system to work with private and government partners with the goal of directly connecting data downlinks to high performance computing. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory is debuting a small satellite ground station that uses high-performance computing to support automated detection of changes to Earth’s landscape.

Samples of four unique materials hitched a ride to space as part of an effort by ORNL scientists to evaluate how each fares under space conditions. Credit: Zac Ward/ORNL, U.S. Dept. of Energy

To study how space radiation affects materials for spacecraft and satellites, Oak Ridge National Laboratory scientists sent samples to the International Space Station. The results will inform design of radiation-resistant magnetic and electronic systems.

Results show change in annual aridity for the years 2071-2100 compared to 1985-2014. Brown shadings (negative numbers) indicate drier conditions. Black dots indicate statistical significance at the 90% confidence level. Credit: Jiafu Mao/ORNL, U.S. Dept. of Energy

A new analysis from Oak Ridge National Laboratory shows that intensified aridity, or drier atmospheric conditions, is caused by human-driven increases in greenhouse gas emissions. The findings point to an opportunity to address and potentially reverse the trend by reducing emissions.

An ORNL research team has incorporated important effects from microbially-active hot spots near streams into models that track the movement of nutrients and contaminants in river networks. The integrated model better tracks water quality indicators and facilitates new science. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

A new modeling capability developed at Oak Ridge National Laboratory incorporates important biogeochemical processes happening in river corridors for a clearer understanding of how water quality will be impacted by climate change, land use and