Bridging the gap in environmental gamma ray spectrometry [ENVIRONMENT]

Lead Research Organisation: University of Stirling
Department Name: Biological and Environmental Sciences


In-situ and mobile gamma spectrometry systems are important tools for measuring environmental radioactivity, characterising contaminated land and detecting radioactive particles. Key limitations remain: for example in calibration and spectral interrogation. Application has been limited by poor spectral resolution of scintillation technology (NaI(Tl), BGO) and the high acquisition and running costs of bulky and fragile semi-conductor technology (HPGe). Moreover, the accuracy of measurement and detection capability are compromised by issues of source burial. Solutions to this problem have become the 'Holy Grail' of environmental gamma ray spectrometry (Tyler, 2007). The forward scattering of gamma photons about the full energy peak has been successfully implemented by the PI Tyler in a number of environments to quantify the depth distribution of 137Cs and 40K (Tyler et al., 1996; Tyler, 1999; Tyler et al., 2001; Tyler 2004). For radionuclides and decay series, which emit energetically different gamma photon peaks, the two line method has also proven successful, especially for U, Th and 226Ra contaminated land (Tyler, 2007). The recent emergence of large LaBr3(Ce) and LaCl3 crystals demonstrates the exciting potential of developing detectors with substantially higher spectral resolution (<3% at 662 keV) and greater detection efficiency per unit volume compared with NaI(Tl) technology, without the issues that compromise the utility of HPGe detectors. The higher detector density and photoelectric cross section significantly reduces the background Compton continuum thus permitting the detection of more complex spectra, which when coupled with a thin Be or C window, will facilitate superior detection capability for low energy gamma photon emissions (e.g. 241Am, 234Th). As a result, simpler spectral processing and improved detection limits enables shorter acquisition times and the opportunity to focus on more intelligent data processing for radionuclide and site (3 dimensional) characterisation. Techniques to reduce the noise introduced by shorter integration times are being developed (Tyler, 2007), similar to noise reduction techniques such as the minimum noise fraction transformations used in image analysis (Tyler et al., 2006: Rainey et al., 2003). These post-processing techniques can be very powerful in yielding subtle spectral changes that correlate with real physical/contaminant change. The implementation of computational intelligence type classification of gamma spectral information provides the opportunity for more powerful real time processing with shorter integration times by using primary and scattered secondary gamma photon information. Training these techniques from measurements with new detector technology at pre-characterised sites and using Monte Carlo simulations will yield more efficient and higher accuracy data extraction than is currently achievable. This forms the hypothesis of this PhD proposal. Following a literature review and training in gamma spectrometry, the student will derive the project design, including the choice of detector technology. The student will determine the detector's radiometric response characteristics and its stability across a range of climatic conditions within controlled climate chambers at Stirling. These data will be used in the detector setup, deployment and software development. Following training in MCNPX Monte Carlo Code (Los Alamos National Laboratory; London Oct. 2011), simulations of detector response will be developed and validated through laboratory work and more complex characterisation of the environment radiation field. A database of simulated and real spectra will be built to support the development of real time high accuracy radiological survey and 3D mapping of site contamination. The student will trial and validate the system alongside existing projects: particle contamination of beaches (Nuvia Limited); site contamination by Stirling with SEPA and the EA.


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