Teams at PNNL welcomed their first two interns this summer from the competition-based program.

PNNL’s Reid Hart and Bing Liu have earned individual Champions of Energy Efficiency in Buildings awards from the American Council for an Energy-Efficient Economy.

PNNL worked with the Department of Energy on the Commercial Packaged Boiler rule, which will help reduce energy use, enhance the environment, and save dollars.

Aerosols from sea-spray that are transported by atmospheric rivers enhance snow precipitation in the Sierra Nevada Mountains.

The Earth system model aerosol-cloud diagnostics package version 1 uses aircraft, ship, and surface measurements to evaluate simulated aerosols in an Earth system model.

Bing Liu was named to the newly established committee to further ASHRAE's decarbonization strategy.

Yunyang Ye, a research engineer at PNNL, receives ASHRAE Homer Addams Award.

Journal article on novel approach to characterizing particles selected by Spectrochimica Acta Part B as the best paper published during 2021.

Michael Brambley, a mechanical engineer at PNNL, receives ASHRAE Exceptional Service Award.

Srinivas Katipamula, a staff scientist at PNNL, has been honored with an ASHRAE Exceptional Service Award.

In an invited review article, PNNL researchers examined the literature surrounding modeling and measuring the ice-nucleating particles that help form clouds.

A novel database of tracked deep convective storms reveals how environmental factors affect storm formation and growth in South America.

Investigating cloud condensation nuclei activities in various airmasses enabled linking activity variations with organic oxidation levels and volatility

New study investigates how to use a non-toxic condensation particle counter for airborne atmospheric research

A new capability facilitates source apportionment of organic aerosols in real time.

The COVID-19 pandemic massively disrupted human activities, which caused additional turmoil through regional record rainfall and floods.

Measuring the ice nucleation activity of particles in the ambient atmosphere can help develop better representations for use in climate models.

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.

Researchers use machine learning to speed up the analysis of aerosol datasets from mass spectrometry.

Srinivas Katipamula and Ron Underhill were invited to share their expertise in energy efficient building operations.