PNNL partners with SRNL, FIU, and industry to test fixative technologies that could be used to immobilize radioactive contaminants on the surface of building materials during the deactivation and decommissioning of DOE legacy facilities.

A theoretical index linking precipitation and atmospheric evaporative demand explains historical land humidity changes across observations, reanalyses, and climate models.

Observations, reanalysis, and E3SMv3 experiments linked inter-annual variability of Congo Basin surface temperature to the zonal position of precipitation over the Indo-Pacific maritime continent region.

Watershed-based representation discretized into topographic subgrid units better captured small-scale land cover, precipitation, temperature, and snow variability across multiple spatial scales.

Physics-informed and data-driven neural network models enhance Earth system models in simulating compound flooding at river-ocean interfaces.

The Iowa Nuclear Energy Task Force, chaired by PNNL’s Mark Nutt, evaluated the state’s potential nuclear future including emerging technologies, workforce needs, waste management, and economic growth opportunities.

Researchers support NRC in accelerating the environmental review process for restarting reactors to meet increased electricity demands—starting with the Palisades Nuclear Plant.

A team from PNNL joined the Department of Homeland Security Science and Technology Directorate and first responders from across the country to evaluate commercially available unmanned ground vehicles for emergency response.

Longtime PNNL researcher resumes leadership role, continuing AGI’s partnership between PNNL and WSU.

Award-winning research advances AI applications for environmental cleanup.

PNNL’s nondestructive evaluation capabilities support advancements in nuclear energy, including research for the U.S. Nuclear Regulatory Commission to preserve the nation’s existing nuclear fleet.

Custom AI research assistant allows users to ask questions and get answers from hundreds of wildfire mitigation plans.

From exploring the development of transformative materials to strengthening biotechnology, six up-and-coming PNNL scientists were recognized for their scientific vision and prowess.

From developing new energy storage materials to revealing patterns of Earth’s complex systems, studies led by PNNL researchers are recognized for their innovation and influence.

As Laboratory Director Steve Ashby pens his last monthly column, he highlights PNNL’s accomplishments with pride and gratitude.

The ability of a storm-resolving weather model to predict the growth of storms over central Argentina was evaluated with data from the Clouds, Aerosols, and Complex Terrain Interactions (CACTI) field campaign in central Argentina.

Researchers have developed the first coastal transport model for microplastics to understand how particles move in waterways and coastal currents.

Researchers from PNNL and Parallel Works, Inc., applied machine learning methods to predict how much oxygen and nutrients are used by microorganisms in river sediments.

Lakes are important sentinels of climate change and contribute significantly to the emissions of the second most important greenhouse gas—methane.

The rate of conversion of cloud droplets to precipitation, known as the autoconversion rate, remains a major source of uncertainty in characterizing aerosol’s cloud lifetime effects and precipitation in global and regional models.