PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.
Now, anyone can easily explore and access data from a nationwide map of data centers, the infrastructure that powers them, and projections of future data center locations.
New datasets delineating global urban land support scientific research, application, and policy, but they can produce different results when applied to the same problem making it difficult for researchers to decide which to use.
The demand for energy is growing—and so is the technology supporting it. However, future development of power generation technologies could be affected by a key factor: material supply.
With the launch of a large research barge, PNNL and collaborators took another significant step to improve offshore wind forecasting that will lower risk and cost associated with offshore wind energy development.
Researchers found that in a future where the Great Plains are 4 to 6 degrees Celsius (°C) warmer as projected in a high-emission scenario, these storms could bring three times more intense rainfall.
The nation is closer to its offshore wind energy goals than ever before, but better wind forecasting is still needed. To address this challenge, PNNL and collaborators are charting a new course with help from novel technology.
PNNL’s Center for the Remediation of Complex Sites convened attendees from around the world to discuss challenges associated with environmental contamination.
A team of scientists at PNNL developed new computational models to predict the behavior of these impurities and reduce the expense and risk related to actinide metal production.
Variations in the level of market globalization can greatly affect the amount of water required to meet future global demand for agricultural commodities.