Researchers from PNNL and Parallel Works, Inc., applied machine learning methods to predict how much oxygen and nutrients are used by microorganisms in river sediments.

Lakes are important sentinels of climate change and contribute significantly to the emissions of the second most important greenhouse gas—methane.

The rate of conversion of cloud droplets to precipitation, known as the autoconversion rate, remains a major source of uncertainty in characterizing aerosol’s cloud lifetime effects and precipitation in global and regional models.

The Coastal Observations, Mechanisms, and Predictions Across Systems and Scales: Field, Measurements, and Experiments project established a network of observational field sites across Chesapeake Bay and western Lake Erie.

Due to their inherent variability and complexity over space and time, scientists are challenged to understand the complex interactions among soil, vegetation, and water along coastal terrestrial-aquatic interfaces.

This study characterized above- and below-ground properties to explore the spatial heterogeneity of the terrestrial aquatic interface ecosystem within the Chesapeake Bay area and evaluate the major drivers of soil respiration.

To assess the impact of observation period and gauge location, model parameters were learned on scenarios using different chunks of streamflow observations.

PNNL's E-COMP initiative is helping unleash American energy innovation with advanced theories, models, and software tools to better operate power systems that rely heavily on high-speed power electronic control.

This study presents an automated method to detect and classify open- and closed-cell mesoscale cellular convection (MCC) using long-term ground-based radar observations.

PNNL's ASSORT model will help airports balance passenger screening and security risks with throughput. It also quantifies risks for different traveler types and optimizes checkpoint operations, improving efficiency while enhancing safety.

A team from PNNL contributed several articles to the Domestic Preparedness Journal showcasing recent efforts to explore the emergency management and artificial intelligence research and development landscape.

A series of conference panels recently explored how new and evolving technologies can support emergency managers’ responsibilities.

A new report details the potential for floating offshore wind to lower energy costs and enhance the resilience of the nation’s western grid.

RemPlex and IAEA convene international leaders to tackle recruitment and retention in complex environmental cleanup efforts.

PNNL’s year in review includes highlights ranging from advancing soil science to understanding Earth systems, expanding electricity transmission, detecting fentanyl, and applying artificial intelligence to aid scientific discovery.

PNNL Earth scientist Alison Delgado will serve as an author for the “Science of Response Management” chapter of the Sixth National Climate Assessment (NCA6.)

This study evaluated the sensitivity of multiple geophysical methods to measure and evaluate the spatiotemporal variability of select soil properties across terrestrial–aquatic interfaces.

Researchers integrated field measurements, lab experiments, and model simulations to study oxygen consumption dynamics in soils along a coastal gradient.

This research explores how changes in groundwater levels affect the chemistry of underground water, especially in areas where land meets water, like wetlands.