Guiding Wildfire Response and Recovery
CSS supports communities following catastrophic wildfires to ensure that items discarded during site cleanup are properly identified, sorted, and sent to an appropriate disposal facility.

Air Monitoring and Household Hazardous Waste Removal Help Devastated Communities During Recovery Efforts

Homes are filled with hundreds of items that are safe in normal conditions but pose significant environmental and health risks after being engulfed in fire. CSS supports communities following catastrophic wildfires to ensure that items discarded during site cleanup are properly identified, sorted, and sent to an appropriate disposal facility. In the aftermath of the recent North Bay/Sonoma, Camp, and Santa Cruz/Carmel wildfires in California, we led teams conducting household hazardous waste (HHW) collections, environmental and asbestos assessments, and multimedia sampling. We also performed on-site air monitoring to protect the health of workers and returning residents, checking for unsafe levels of asbestos, volatile organic compounds, and other airborne hazards that may have been released in the fire. Our staff oversaw safety compliance, prepared daily Incident Command System (ICS) reports, coordinated with senior EPA leaders, and handled requests for special services. We also performed quality assurance reviews of completed removals and assisted with data management.
Additional Projects

Hazard Analysis Support to the Transportation Security Administration
CSS has provided safety and health support, and a variety of other activities in support of Transportation Security Administration (TSA) Office of Occupational Safety, Health and Environment (OSHE) programs.

Analysis for Coastal Operational Resiliency
CSS assisted with planning and executing a demonstration of three decontamination technologies on a USCG vessel contaminated with a benign surrogate for anthrax.

Predictive Modeling/Spatial Planning, NY Bight
CSS designed and implemented this integrated data acquisition, data management, and statistical predictive modeling to select optimal wind farm locations while minimally impacting seabirds.

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