Repeated aircraft measurements over central Oklahoma allow researchers to better understand the spatial variability of aerosol properties that affect cloud evolution.

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

Interns dive into important research that addresses national needs.

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.

TransMED analyzes patient data from similar diseases across multiple sources to understand COVID-19 patient outcome risk factors.

The Washington State Academy of Sciences added six people from PNNL to its 2022 class of inductees.

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

The virus that causes COVID-19 takes over the body’s fat-processing system and boosts cellular triglycerides as it causes disease.

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

The Department of Homeland Security Science and Technology Virtual First Responder Capitol Hill Showcase highlighted PNNL work in fentanyl detection standards and database libraries.

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.

PNNL scientists have developed a new mass spectrometry method for in-depth analysis of proteins in individual cells.

The paper was recognized by the Society of Toxicology’s Medical Device and Combination Product Specialty Section.