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.

Read interviews with the new Laboratory fellows to learn about their contributions to their field, what drives them, and how their research is making the nation safer, greener, and more resilient.

Eight PNNL research papers were recognized by the 2022 Waste Management Symposia as “Papers of Note” and “Superior.” One paper received a Best Oral Paper/Presentation Award.

The size and concentration of ions influences the aggregation behavior of solutions of boehmite.

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

PNNL’s Rob Howard received the 2022 Fuel Cycle and Waste Management Award from the American Nuclear Society.

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.

The size of the alkali metal within the material influences the crystallization pathway.

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 collaboration will further accelerate the science behind radioactively contaminated land management and radioactive waste disposal.

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.

This PNNL-developed separation system quickly and successfully separates larger particles from smaller ones at various scales, in different solid-liquid mixtures and at different flow rates.

Performing a network analysis of forces between particles reveals new insight into shear induced thinning and thickening in non-Newtonian fluids.

IDREAM researchers show that high concentrations of sodium hydroxide significantly impact the molecular and macroscale properties of sodium nitrite solutions.