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.
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.
Researchers at Oak Ridge National Laboratory are using a novel approach in determining environmental impacts to aquatic species near hydropower facilities, potentially leading to smarter facility designs that can support electrical grid reliability.
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 analysis by Oak Ridge National Laboratory shows that using less-profitable farmland to grow bioenergy crops such as switchgrass could fuel not only clean energy, but also gains in biodiversity.
New data hosted by Oak Ridge National Laboratory is helping scientists around the world understand the secret lives of plant roots as well as their impact on the global carbon cycle and climate change.
Oak Ridge National Laboratory worked with Colorado State University to simulate how a warming climate may affect U.S. urban hydrological systems.
Scientists at Oak Ridge National Laboratory added new plant data to a computer model that simulates Arctic ecosystems, enabling it to better predict how vegetation in rapidly warming northern environments may respond to climate change.
Scientists studying a unique whole-ecosystem warming experiment in the Minnesota peatlands found that microorganisms are increasing methane production faster than carbon dioxide production.
To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human cell receptor.