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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.

ORNL’s Brenda Pracheil, left, and Kristine Moody collect water samples at Melton Hill Lake using a sophisticated instrument that collects DNA in the water to determine fish species and number of fish in the water, which could prove useful for monitoring hydropower impacts. Credit: Carlos Jones, ORNL/U.S Dept. of Energy

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.

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.

Planting native grasses such as the bioenergy crop switchgrass can restore habitat for birds like this Eastern kingbird. Credit: Chris Lituma/West Virginia University

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.

In a study, ORNL researchers concluded that the most direct path to plastic upcycling is through designing polymers specifically for reuse, which would allow the material to be converted into high-value products. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers determined that designing polymers specifically with upcycling in mind could reduce future plastic waste considerably and facilitate a circular economy where the material is used repeatedly.

The D2U model categorizes user data by capturing behavior in all open programs throughout a user’s day. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers have created a technology that more realistically emulates user activities to improve cyber testbeds and ultimately prevent cyberattacks.

The ectomycorrhizal fungus Laccaria bicolor, shown in green, envelops the roots of a transgenic switchgrass plant. Switchgrass is not known to interact with this type of fungi naturally; the added PtLecRLK1 gene tells the plant to engage the fungus. Credit: ORNL, U.S. Dept. of Energy

An ORNL team has successfully introduced a poplar gene into switchgrass, an important biofuel source, that allows switchgrass to interact with a beneficial fungus, ultimately boosting the grass’ growth and viability in changing environments.

Fine roots from a larch tree peek out from a pile of peat excavated from an experimental warming plot in the SPRUCE experiment in Northern Minnesota. Credit: Colleen Iversen/ORNL, U.S. Dept. of Energy

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.

Researchers at Colorado State University and ORNL evaluated 14 urban megaregions to simulate the effects of climate change on water resources. Credit: CSU/ORNL, U.S. Dept. of Energy

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 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.