CSS scientists supporting the Environmental Protection Agency’s Office of Pesticide Programs are reviewing modeling data that evaluates the potential for transfer of chemical residues from pregnant and nursing animals to fetuses and infants. The vast majority of data come from pharmaceuticals, but staff are reviewing some data from pesticides and other environmental contaminants as well. Staff are reviewing the data for measured concentrations in maternal blood and milk as well as fetal tissues in laboratory animals and humans. The objective of this work is to better understand the various models being developed and use this modeling data to help refine risk assessment for pesticides.
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Supporting National Ocean Service Financial Management Centers
CSS employee-owners bring exceptional dedication and expertise to the National Ocean Service (NOS) Agreements, Grants, and Acquisitions Division, supporting several Financial Management Centers (FMCs) through complex, high‑priority initiatives. CSS has played a key role in helping FMCs navigate the U.S. Department of Treasury’s G‑Invoicing system during a period of transition and heavy workload. CSS staff recognized the challenges many teams were facing and broke down the system’s complex requirements…
Contributing to Wind Energy Area Designations
The Bureau of Ocean Energy Management (BOEM) recently announced two Wind Energy Areas (WEAs) in the Gulf of Mexico. The WEAs are located off the coasts of Galveston, Texas, and Lake Charles, Louisiana and have the potential to power nearly three million homes. BOEM collaborated with the National Oceanic and Atmospheric Administration (NOAA) to identify…
Advancing Severe Weather Predictions with Artificial Intelligence
As artificial intelligence (AI) and machine learning (ML) technologies evolve in Earth sciences, CSS employee owners (formerly Riverside staff) are growing our expertise in this field. CSS employee owners are advancing technologies for our client, NOAA’s Center for Satellite Applications and Research (STAR). Our staff have developed a framework, exploiting modern AI/ML techniques, to rapidly…