A method for estimating the minimum detectable concentration of a contaminant radionuclide in soil when scanning with gamma radiation detectors (known as the "scan MDC") is described in the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM). This paper presents an alternate method for estimating scan MDCs for GPS-based gamma surveys based on detector efficiencies modeled with the probabilistic Monte Carlo N-Particle Extended (MCNPX) Transport simulation code. Results are compared to those provided in MARSSIM. An extensive database of MCNPX-based detection efficiencies has been developed to represent a variety of gamma survey applications and potential scanning configurations (detector size, scan height, size of contaminated soil volume, etc.), and an associated web-based user interface has been developed to provide survey designers and regulators with access to a reasonably wide range of calculated scan MDC values for survey planning purposes.
Radiological surveys of a uranium mill site in Colorado and several proposed uranium recovery sites in Wyoming were conducted in 2006 and 2007. Advancements in Global Positioning System (GPS)-based gamma scanning systems combined with gamma/Ra correlations and Geographic Information Systems (GIS)-based spatial analysis techniques produced comprehensive and detailed characterizations of the spatial distributions of gamma exposure rates and Ra concentrations in surface soils across extensive study areas. Aside from limitations on gamma-based estimates of soil Ra related to soil heterogeneity or gamma shine effects, soil sampling results to date show good general agreement between estimated and measured values. Spatial characterization aspects of the survey approach are clearly more effective than conventional grid sampling methods, particularly for such large sites. Example project applications, data collection and analysis methods, challenges encountered, and resulting mapped estimates of various aspects of these radiological parameters are presented.
A mobile, on-site laboratory was used to estimate soil radionuclide concentrations in support of cleanup activities at a former uranium mill site. Respective instrumentation and analytical techniques demonstrated a successful balance between system cost, accuracy, versatility, throughput capacity, and practical simplicity. The methodology involved NaI scintillation gamma spectroscopy measurements calibrated against high-purity germanium analyses by a commercial lab. Statistical comparisons indicated levels of accuracy and precision attained by the on-site lab were similar to that of the commercial lab.
A probabilistic method for a priori calculation of the expected minimum detectable concentration of a contaminant radionuclide in soil while scanning (“scan MDC”) with a GPS-based gamma radiation survey system has previously been described. This paper presents supporting evidence for the validity of respective use of a statistical minimum detectable count rate (MDCR) as described in the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) and builds on related concepts to develop a technical basis for a posteriori estimation of MDCR and scan MDC sensitivity metrics for geospatially rendered datasets. Nearest-neighbor averaging of multiple data points from a geospatial population of gamma survey data permits retrospective quantification of MDCR values based on statistical reductions in the variance in both background and source data distributions. A retrospective MDCR can be used to calculate a posteriori scan MDCs based on detection efficiencies modeled with the probabilistic method for various radionuclides, source dimensions, detector heights, and scan speeds.
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