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
ITC Tank Farm Fire Emergency Response
In response to a dangerous fire EPA ordered CSS’ senior field operations specialists to a facility near Houston where massive tanks stored highly flammable liquids to help manage emergency response activities.
Analytical Support for the Drinking Water Emergency in Hawaii
In response to the Red Hill Drinking Water Emergency, CSS staff mobilized on Christmas Day to set up mobile laboratory assets to analyze drinking water samples and confirm that the drinking water in residential homes was safe for human consumption.
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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