Retrospective Detection Sensitivity for GPS-based Gamma Radiation Surveys.

ABSTRACT: 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.

Spatial Variability and Behavior of Background Radon Concentrations in Ambient Air in the San Mateo Basin of the Grants Mineral Belt.

ABSTRACT: A modeling study and analysis of measurement data was conducted in the San Mateo basin near the former Homestake Mining Company of California's mill site located north of Milan, NM, to understand the spatial variability of background radon and identify a suitable background station. Recent guidance from the US Nuclear Regulatory commission clarifies the requirement that dose assessments of existing facilities be based on environmental measurements at the facility's unrestricted boundary instead of predictive modeling. Background is important because it is subtracted from radon measured at the boundary for dose calculations. The current background station lies on the slopes above the wash floor. The mill site contains two tailing piles with a total area of 1.03 km2 that in 2019 emitted 1,750 mBq m-2 s-1 from the larger of the piles and 320 mBq m-2 s-1 from the smaller pile. Atmospheric transport modeling was conducted to facilitate understanding of the movement of radon in the San Mateo wash bottom and surrounding hillsides. The model was validated using emission and measurement data from the nearby Ambrosia Lake mining region. The modeling, in combination with current measurements and previous studies, indicated the wash floor has characteristically higher radon concentrations than the slopes above the wash. This phenomenon was attributed to (1) higher radon soil flux in the alluvial sediments that make up the wash floor, (2) nocturnal drainage flow that results in a pooling of radon on the wash floor, and (3) inversion conditions that trap radon in a shallow air mass on the wash floor during late evening and early morning hours. Using a regression of predicted and observed radon concentrations, a background concentration of 25.7 Bq m-3 was derived that was close to that measured at background stations about 4 km north of the tailings pile and on the San Mateo wash floor.

Scan MDCs for GPS-Based Gamma Radiation Surveys.

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.

Normalization of energy-dependent gamma survey data.

Instruments and methods for normalization of energy-dependent gamma radiation survey data to a less energy-dependent basis of measurement are evaluated based on relevant field data collected at 15 different sites across the western United States along with a site in Mongolia. Normalization performance is assessed relative to measurements with a high-pressure ionization chamber (HPIC) due to its "flat" energy response and accurate measurement of the true exposure rate from both cosmic and terrestrial radiation. While analytically ideal for normalization applications, cost and practicality disadvantages have increased demand for alternatives to the HPIC. Regression analysis on paired measurements between energy-dependent sodium iodide (NaI) scintillation detectors (5-cm by 5-cm crystal dimensions) and the HPIC revealed highly consistent relationships among sites not previously impacted by radiological contamination (natural sites). A resulting generalized data normalization factor based on the average sensitivity of NaI detectors to naturally occurring terrestrial radiation (0.56 nGy hHPIC per nGy hNaI), combined with the calculated site-specific estimate of cosmic radiation, produced reasonably accurate predictions of HPIC readings at natural sites. Normalization against two to potential alternative instruments (a tissue-equivalent plastic scintillator and energy-compensated NaI detector) did not perform better than the sensitivity adjustment approach at natural sites. Each approach produced unreliable estimates of HPIC readings at radiologically impacted sites, though normalization against the plastic scintillator or energy-compensated NaI detector can address incompatibilities between different energy-dependent instruments with respect to estimation of soil radionuclide levels. The appropriate data normalization method depends on the nature of the site, expected duration of the project, survey objectives, and considerations of cost and practicality.

Radiological site characterizations: gamma surveys, gamma/226Ra correlations, and related spatial analysis techniques.

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.

Mobile soils lab: on-site radiological analysis supporting remedial activities.

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.