Rapid Surface Sampling and Archival Record (RSSAR) system. Final report, October 1995--May 1997
Publication year - 1998
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/567469
Subject(s) - modular design , sampling (signal processing) , instrumentation (computer programming) , characterization (materials science) , computer science , scientific instrument , process engineering , sample (material) , detector , environmental science , systems engineering , engineering , materials science , nanotechnology , telecommunications , physics , operating system , thermodynamics , quantum mechanics
This report describes the results of Phase 2 efforts to develop a Rapid Surface Sampling and Archival Record (RSSAR) System for the detection of semivolatile organic contaminants on concrete, transite, and metal surfaces. The characterization of equipment and building surfaces for the presence of contaminants as part of building decontamination and decommissioning activities is an immensely large task of concern to both government and industry. Because of the high cost of hazardous waste disposal, old, contaminated buildings cannot simply be demolished and scrapped. Contaminated and clean materials must be clearly identified and segregated so that the clean material can be recycled or reused, if possible, or disposed of more cheaply as nonhazardous waste. DOE has a number of sites requiring surface characterization. These sites are large, contain very heterogeneous patterns of contamination (requiring high sampling density), and will thus necessitate an enormous number of samples to be taken and analyzed. Characterization of building and equipment surfaces will be needed during initial investigations, during cleanup operations, and during the final confirmation process, increasing the total number of samples well beyond that needed for initial characterization. This multiplicity of information places a premium on the ability to handle and track data as efficiently as possible
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