Secondary organic aerosol formation from monoterpenes is more strongly influenced by oxidant and monoterpene structure than by nitric oxides and hydroperoxy radical concentrations.

The presence of mMarine microorganisms may enhance cloud droplet formation, leading to brighter clouds that reflect more sunlight.

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.

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.

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.

PNNL scientists developed new capabilities to study materials under extreme conditions.

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.

PNNL Materials Scientist Leo Fifield recognized for contributions to the field of nuclear instrumentation and control.

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 researchers have uncovered a plant-derived process that leads to the formation of aerosol particles over the Amazon rainforest and potentially other forested parts of the world. 

Combining aircraft measurements and regional modeling allowed researchers to identify the role of in-plant biochemistry in secondary organic aerosol formation.