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Year

2024

Our Role

Implementing advanced data management and analytics solutions

Air Force PFAS AFFF Project

The U.S. Air Force launched a project in 2024 to address PFAS contamination at military bases, with Trinnex supporting CDM Smith by providing advanced data management and analytics solutions. Through the use of dataCAST™, a cloud-based platform, Trinnex enables effective PFAS remediation by integrating complex environmental data for informed decision-making.

U.S. Air Force Takes Action on PFAS Contamination at Military Bases

The U.S. Air Force is tackling the environmental and health impacts of per- and polyfluoroalkyl substances (PFAS) contamination caused by aqueous film-forming foam (AFFF) at military bases.

Trinnex and CDM Smith Revolutionize PFAS Remediation with dataCAST™ Platform

Trinnex, supporting CDM Smith, developed the software technology part of this initiative. Our team is leveraging cutting-edge digital tools and frameworks to compile, organize, and integrate vast amounts of data, supporting effective remediation decision-making. At the heart of the Trinnex contribution is dataCAST™, a cloud-based platform designed to manage large and complex datasets. dataCAST integrates data from various sources, including soil, groundwater, and surface water samples, to provide a comprehensive view of PFAS contamination. It provides advanced data integration, compiling data from multiple sources to deliver a complete understanding of PFAS distribution, fate, and transport. The platform also includes 3D modeling with Leapfrog technology, visualizing PFAS contamination to aid risk assessment and guide remedial decisions. With a Custom Leaching Model, dataCAST tracks PFAS movement from the vadose zone to groundwater using a streamlined mass balance framework. Finally, Digital Dashboards deliver clear, visual data for quick, effective decision-making.

dataCAST Empowers AFCEC to Drive Effective PFAS Remediation at Military Bases

By leveraging dataCAST, the U.S. Air Force Civil Engineer Center (AFCEC) can efficiently manage and interpret large datasets, ultimately supporting the development of effective remediation programs to address PFAS contamination at military installations.

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