Building new climate outcome scenarios by stitching together pieces of existing ones.

Researchers found that specific landscape metrics consistently outperform traditional population downscaling methods.

A systematic, multiple scenario approach was used to analyze the compounding impacts of demands for land for biofuels with increased land scarcity under a diverse set of uncertainties.

PNNL is the newest member of the CONsortium on Nuclear sECurity Technologies (CONNECT).

rmap enables users with limited to no geographic information system knowledge use R to visualize simple tabular data.

The methods researchers use to estimate crop yield gaps determines the location of projected future agricultural “breadbasket” regions.

Advancing the science of radiation, especially among students at minority-serving institutions, is the goal of one of the Department of Energy’s newest consortia.

PNNL research, featured on the cover of two science journals, describes advancements in using Raman spectrometry for Hanford Site nuclear waste remediation.

Better representing electric capacity markets, economic retirements, and power-plant age structure provides a more robust understanding of the future evolution of the electric sector.

PNNL experts in nuclear forensics helped lead laboratories around the world through a rigorous test involving nuclear materials.

MSD-LIVE, a cloud-based data and code management system, will be released in summer 2022 for hundreds of scientists.

An improved model captures the interactions between the U.S. economy, energy, water, and land systems with increased spatial and temporal detail.

A climate change study co-authored by PNNL scientist Hailong Wang inspired an artist to create an exhibit based on the research.

PNNL contributes to 30 years of data on clouds, radiation, and other climate-making factors as part of field campaigns and analysis conducted by DOE's Atmospheric Radiation Measurement user facility.

New work developed a methodology to generate building temperature setpoint schedules for use by modelers in large-scale building energy simulations.

Storage Targets and Release Function Inference Tool uses data to infer the operating policies of large reservoirs on a national scale.

A multisectoral analysis that combines land use data with hydrological simulations reveals wide disparities in potential source water contamination.

COVID-19 had multiple impacts on the electric sector and the nature of those impacts varied on the scale analyzed.

Using a novel settlement-related dataset produced more accurate population downscaling than using other, more traditional datasets.

Despite an increase in future electricity demands, virtual water trading in the U.S. electricity sector is expected to decline as renewable energy expands.