The Nereus Project aims to collect and analyze comprehensive environmental monitoring data around operational marine energy sites and devices in the United States.
Pacific Northwest National Laboratory supports innovations in data analytics, instrumentation, and experimental techniques for the Northwest (NW) Biopreparedness Research Virtual Environment (BRaVE) Initiative.
PNNL's Ocean Dynamics Modeling group studies coastal processes such as marine-hydrokinetic energy, coastal circulations, storm surge and extreme waves, tsunamis, sediment transport and nutrient-macroalgal dynamics.
The Pacific Northwest Advanced Compound Identification Center (PNACIC) brings together innovations in integrated chemistry and advanced instrumentation to create a platform for comprehensive, unambiguous identification of metabolites.
Physics-informed machine learning (PIML) is a modeling approach that harnesses the power of machine learning and big data to improve the understanding of coupled, dynamic systems.
PNNL has developed performance assessment guidance for remediation of volatile contaminants in the vadose zone, inorganic contaminant remediation in the vadose zone, and pump-and-treat of groundwater contaminant plumes.
PNNL's River Corridor Hydrobiogeochemistry Scientific Focus Area works to transform understanding of spatial and temporal dynamics in river corridor hydrobiogeochemical functions from molecular reaction to watershed and basin scales.
The Salish Sea Model (SSM) is a predictive coastal ocean model for estuarine research, restoration planning, water-quality management, and climate change response assessment.
The Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites online tools provide rapid data analytics and visualization of environmental data supporting remedy decisions, optimization, and exit strategies.
