PNNL researchers are helping to better define the need for grid energy storage in future clean energy scenarios, as well as working to improve technologies for storing renewable energy so it's available when and where it's needed.

Using a combination of satellite data and modeling to study the temperatures and humidity people might feel in urban areas, researchers have pinpointed who in the U.S. is most vulnerable to heat stress.

PNNL receives a 2023 Federal Laboratory Consortium Far West Regional Award for a technological innovation that could help make the U.S. a producer of critical minerals used in electronics and energy production.

Quantifying the long-term destination of anthropogenic emissions and robustness of global carbon sinks.

New study identifies crucial factors for more accurate hydrological predictions in the Community Land Model version 5.

Groundwater modeling of irrigation return flow dynamics is important for improving estimates of water availability.

PNNL scientists investigate the promising properties of a common, Earth-abundant salt.

The Great Plains and Great Lakes regions are the major sources of moisture for the precipitation that falls in the Great Lakes region.

A team of researchers at PNNL designed and constructed an atmospheric chamber to simulate the fate of volatile and semivolatile radioisotopes.

A computationally efficient calibration procedure helps constrain simulated runoff in an Earth system model.

The complex interactions between the land and atmosphere can affect cloud growth.

Existing clouds affect the growth of neighboring clouds.

Oluwayemi Garuba brings Arctic expertise to panel on climate modeling.

Daniel Deng, mechanical engineer and Laboratory Fellow at PNNL, has been named 2022 PNNL Inventor of the Year.

By mimicking nature, scientists make a breakthrough in breaking down wood.

Findings in a new PNNL report show long-duration energy storage will be a necessity in decarbonizing the grid and recommends the planning and procurement process to identify those needs start immediately.

Yun Qian has been selected as an editor of the Journal of Geophysical Research: Atmospheres, a prominent atmospheric science journal.

PNNL researchers explore the feasibility of using low-flying drones to survey sites for low levels of radiation.

Methods review suggests ways to use artificial intelligence and machine learning to handle missing data when integrating two or more omics approaches.

Assessing observed weather conditions that support or suppress the growth of clouds into deep precipitating storms during the Cloud, Aerosol, and Complex Terrain Interactions experiment.