By adding rain, snow, and rain-on-snow precipitation data to a background model, a new scheme pinpoints local flood risks in order to improve the design of small-scale hydrological infrastructure.
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.
Infusing data science and artificial intelligence into electron microscopy could advance energy storage, quantum information science, and materials design.
PNNL has three small-scale spectroscopy devices that are speeding up the testing and analysis of candidate novel materials used in energy storage research and environmental remediation.
Pacific Northwest National Laboratory (PNNL) is part of a continuing National Science Foundation (NSF) team investigating the environmental impact of nanoparticles at the molecular level.
Oliver Gutiérrez leads an electrocatalytic hydrogenation research team at PNNL that focuses on next-generation catalysts at the molecular level and in an aqueous state.
To help close the gap between observed and modeled ice-nucleating particles (INPs), researchers simulated concentrations of dust, sea spray, and other types of atmospheric particles within a global atmospheric model.
At PNNL, subsurface science inhabits two separate but interlocking worlds. One looks at basic science, the other at applied science and engineering. Both are funded by the U.S. Department of Energy (DOE).
Jason McDermott is a PNNL computational biologist whose research interests include machine learning, data integration, and network inference. He unravels complex data related to cancer, infectious disease, and soil microbiomes.
A study co-led by PNNL and reviewed in Science investigates how nanomaterials—both ancient and modern—cycle through the Earth’s air, water, and land, and calls for a better understanding of how they affect the environment and human health.