- Success Stories
- Safety, Health, & Environmental Compliance
Training the Next Generation of Researchers
CSS staff support the National Institutes of Health (NIH) Division of Occupational Safety and Health by providing Safe Techniques Advance Research Science (STARS) training to summer interns. Following a pause during the pandemic, staff resumed training May 15, 2024. During the in-person STARS training, CSS staff cover key concepts from the pre-requisite NIH Lab Safety online training by working through two case studies: one biological hazard (salmonella typhi handling procedures), and one chemical hazard (acrylamide for gels). CSS trainers provide a show and tell while demonstrating the safety equipment in the mock lab.
We anticipate training hundreds of interns this summer.
We are proud to be training the next generation of researchers!


See More CSS Insights
Assessing Contamination in Abandoned Mines
CSS supports the Environmental Protection Agency with assessing contamination within abandoned mines. There are thousands of abandoned mines throughout the western United States. Many of these mines are leaching heavy metals into nearby streams or have contaminated soils causing vegetation die off. CSS employee owners conduct field work to assess the extent of this contamination.…
Developing a Decontamination Line Guide for EPA Responders
CSS employee owners supporting the Environmental Protection Agency’s (EPA) Scientific and Technical Assistance for Consequence Management (STACM) contract have been working with the National Chemical Preparedness Workgroup and Sub Workgroups to create a decontamination (decon) line guide and detailed drawing for EPA on-scene coordinators and EPA’s special teams to use for emergency responses and incidents. The…
Evaluating the Use of Earth Observations Digital Twin Technologies
Earth Observations Digital Twin technologies are data analytics, artificial intelligence, and advanced modeling technologies that provide an estimate of the true state of the Earth. An Earth Systems Digital Twin is observations-based and grid-flexible with multiple components and high-resolution data over space and time to capture all available observations and feed a variety of direct…
