
Field Raman Spectrograph for Environmental Analysis
Author(s) -
John W. Haas,
Robert W. Forney,
Michael M. Carrabba,
R. D. Rauh
Publication year - 1998
Language(s) - English
Resource type - Reports
DOI - 10.2172/3969
Subject(s) - spectrograph , instrumentation (computer programming) , computer science , identification (biology) , software , sample (material) , scope (computer science) , environmental science , systems engineering , process (computing) , engineering , physics , botany , thermodynamics , astronomy , spectral line , biology , programming language , operating system
The widespread contamination found across the US Department of Energy (DOE) complex has received considerable attention from the government and public alike. A massive site characterization and cleanup effort has been underway for several years and is expected to continue for several decades more. The scope of the cleanup effort ranges from soil excavation and treatment to complete dismantling and decontamination of whole buildings. To its credit, DOE has supported research and development of new technologies to speed up and reduce the cost of this effort. One area in particular has been the development of portable instrumentation that can be used to perform analytical measurements in the field. This approach provides timely data to decision makers and eliminates the expense, delays, and uncertainties of sample preservation, transport, storage, and laboratory analysis. In this program, we have developed and demonstrated in the field a transportable, high performance Raman spectrograph that can be used to detect and identify contaminants in a variety of scenarios. With no moving parts, the spectrograph is rugged and can perform many Raman measurements in situ with flexible fiber optic sampling probes. The instrument operates under computer control and a software package has been developed to collect and process spectral data. A collection of Raman spectra for 200 contaminants of DOE importance has been compiled in a searchable format to assist in the identification of unknown contaminants in the field