The Community Emissions Data System (CEDS) provides historical emissions data are used both for general analysis and assessment and also for model validation through comparisons with observations.
PNNL’s integrated software systems (FRAMES, MEPAS, MetView, APGEMS, CAPP) allow users to assess the environmental fate and transport of contaminants—and the potential impacts on humans and the environment—in a systematic, holistic approach.
The Joint Global Change Research Institute conducts research to advance fundamental understanding of human and Earth systems and provide decision-relevant information for management of emerging global risks and opportunities.
PNNL is heavily engaged in the development and use of mass spectrometry technology across its science, energy, and security missions, from fundamental research through mature operational capabilities.
Advancing the understanding and monitoring of nuclear material processing to accelerate development and qualification of new material systems for national security and nuclear energy.
The Molecular Observation Network is a national open science network designed to produce a comprehensive database of molecular and microstructural information on soil, water, microbial communities, and biogenic emissions.
PNNL data scientists and engineers will be presenting at NeurIPS, the Thirty Fourth Conference on Neural Information Processing Systems, and the co-located Women in Machine Learning workshop, WiML.
A software suite for working with neutron activation rates measured in a nuclear fission reactor, an accelerator-based neutron source, or any neutron field to determine the neutron flux spectrum using a generalized least-squares approach.
UTEP and PNNL are advancing the collective scientific impact of both institutions through collaborations between PNNL researchers and UTEP faculty, as well as by building on the complementary strengths to grow a diverse STEM workforce.
The Water Cycle and Climate Extremes Modeling (WACCEM) Scientific Focus Area advances predictive understanding of water cycle variability and change through foundational research using models, observations, and novel numerical experiments.
