Researchers use models to represent relationships between climate and socio-economic processes, helping inform decisions for slowing climate change and enhancing resilience.
From air-sealing windows and checking for leaky ducts to insulating the attic, PNNL researchers offer tips on how to keep a home warm in winter weather.
The use of disciplines in pure mathematics can increase the reliability and explainability of machine learning models that “transcend human intuition,” according to PNNL scientists.
The roles of the various environmental variables in the transition from suppressed to active tropical precipitation regimes are characterized using statistical analysis and machine learning.
This study revealed that fresh organic vapors are soluble in particulate organics that are actively growing in size. However, if the particulate matter ages, fresh organic vapors can no longer mix with the organic matter.
A larger HVAC workforce with training on modern heat pump technology will be pivotal to achieving the mass-scale electrification of household HVAC systems needed to meet building decarbonization goals.
Leaders from the DOE Office of Energy Efficiency and Renewable Energy visited PNNL October 19–20 for a firsthand look at capabilities and research progress.
Pacific Northwest National Laboratory and Launch Point CDC, Inc. are developing a framework to empower disadvantaged communities with clean energy technology—along with a set of resources to give other community organizations a head start.
Metabolism metrics provide information about biological activity and carbon cycling in rivers. Conditions in large rivers differ from smaller rivers and require adjustments to existing methods.