Assessment of the environmental radiation by in situ gamma ray spectrometry

Naturally occurring radioactive materials (NORM) under certain conditions can reach hazardous radiological levels contributing to an additional exposure dose to ionizing radiation. Most environmental concerns are associated with uranium mining and milling sites, but the same concerns should be addressed to natural near surface occurrences of uranium as well as man-made sources such as technologically enhanced naturally occurring radioactive materials (TENORM) resulting from phosphates industry, ceramic industry and energy production activities, in particular from coal-fired power plants which is one of the major sources of increased exposure to man from enhanced naturally occurring materials. This work describes the methodology developed to assess the environmental radiation by in situ gamma spectrometry in the vicinity of a Portuguese coal fired power plant. The current investigation is part of a research project that is undergoing in the vicinity of Sines Coal-Fired Power Plant (south of Portugal) until the end of 2013.

Seven years of gamma-ray spectrometry interlaboratory comparisons in Switzerland.

Since the 1990s, regular comparisons of gamma-ray spectrometry in Switzerland were organized to improve laboratory abilities to measure the radioactivity in the environment and food stuffs at typical routine levels. The activity concentration of the test samples and the evaluation of the associated uncertainties remained each year the main required test result. Over the years, the comparisons used certified reference solutions as well as environmental samples. The aim of this study is to research the effect of the comparisons on measurement quality. An analysis of the seven last interlaboratory comparisons revealed that the Swiss measurement capability is up to date. In addition, the results showed that the participants now have an improved evaluation of the uncertainties associated with their measurement.

Gamma-ray spectrometry signature of main volcanic rocks of Serra Geral formation: preliminary results

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Porosity measurement of solid pharmaceutical dosage forms by gamma-ray transmission

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Spatial model of site index based on Y-ray spectrometry and a digital elevation model for two Pinus species in Tuan Toolara State Forest, Queensland, Australia

Site index prediction models are an important aid for forest management and planning activities. This paper introduces a multiple regression model for spatially mapping and comparing site indices for two Pinus species (Pinus elliottii Engelm. and Queensland hybrid, a P. elliottii x Pinus caribaea Morelet hybrid) based on independent variables derived from two major sources: g-ray spectrometry (potassium (K), thorium (Th), and uranium (U)) and a digital elevation model (elevation, slope, curvature, hillshade, flow accumulation, and distance to streams). In addition, interpolated rainfall was tested. Species were coded as a dichotomous dummy variable; interaction effects between species and the g-ray spectrometric and geomorphologic variables were considered. The model explained up to 60% of the variance of site index and the standard error of estimate was 1.9 m. Uranium, elevation, distance to streams, thorium, and flow accumulation significantly correlate to the spatial variation of the site index of both species, and hillshade, curvature, elevation and slope accounted for the extra variability of one species over the other. The predicted site indices varied between 20.0 and 27.3 m for P. elliottii, and between 23.1 and 33.1 m for Queensland hybrid; the advantage of Queensland hybrid over P. elliottii ranged from 1.8 to 6.8 m, with the mean at 4.0 m. This compartment-based prediction and comparison study provides not only an overview of forest productivity of the whole plantation area studied but also a management tool at compartment scale.

Spatial statistics to estimate peat thickness using airborne radiometric data

Soil carbon stores are a major component of the annual returns required by EU governments to the Intergovernmental Panel on Climate Change. Peat has a high proportion of soil carbon due to the relatively high carbon density of peat and organic-rich soils. For this reason it has become increasingly important to measure and model soil carbon stores and changes in peat stocks to facilitate the management of carbon changes over time. The approach investigated in this research evaluates the use of airborne geophysical (radiometric) data to estimate peat thickness using the attenuation of bedrock geology radioactivity by superficial peat cover. Remotely sensed radiometric data are validated with ground peat depth measurements combined with non-invasive geophysical surveys. Two field-based case studies exemplify and validate the results. Variography and kriging are used to predict peat thickness from point measurements of peat depth and airborne radiometric data and provide an estimate of uncertainty in the predictions. Cokriging, by assessing the degree of spatial correlation between recent remote sensed geophysical monitoring and previous peat depth models, is used to examine changes in peat stocks over time. The significance of the coregionalisation is that the spatial cross correlation between the remote and ground based data can be used to update the model of peat depth. The result is that by integrating remotely sensed data with ground geophysics, the need is reduced for extensive ground-based monitoring and invasive peat depth measurements. The overall goal is to provide robust estimates of peat thickness to improve estimates of carbon stocks. The implications from the research have a broader significance that promotes a reduction in the need for damaging onsite peat thickness measurement and an increase in the use of remote sensed data for carbon stock estimations.

Object identification based on 3D spatial models of construction sites

On obstacle-cluttered construction sites, understanding the motion characteristics of objects is important for anticipating collisions and preventing accidents. This study investigates algorithms for object identification applications that can be used by heavy equipment operators to effectively monitor congested local environment. The proposed framework contains algorithms for three-dimensional spatial modeling and image matching that are based on 3D images scanned by a high-frame rate range sensor. The preliminary results show that an occupancy grid spatial modeling algorithm can successfully build the most pertinent spatial information, and that an image matching algorithm is best able to identify which objects are in the scanned scene.

Gamma-ray luminosity function of gamma-ray bright AGNs

Detection of gamma-ray emissions from a class of active galactic nuclei (viz blazars), has been one of the important findings from the Compton Gamma-Ray Observatory (CGRO). However, their gamma-ray luminosity function has not-been well determined. Few attempts have been made in earlier works, where BL Lacs and Flat Spectrum Radio Quasars (FSRQs) have been considered as a single source class. In this paper, we investigated the evolution and gamma-ray luminosity function of FSRQs and BL Lacs separately. Our investigation indicates no evolution for BL Lacs, however FSRQs show significant evolution. Pure luminosity evolution is assumed for FSRQs and exponential and power law evolution models are examined. Due to the small number of sources, the low luminosity end index of the luminosity function for FSRQs is constrained with an upper limit. BL Lac luminosity function shows no signature of break. As a consistency check, the model source distributions derived from these luminosity functions show no significant departure from the observed source distributions.

A theoretical color-velocity correlation for supernovae associated with gamma-ray bursts

We carry out the first multi-dimensional radiative transfer calculations to simultaneously compute synthetic spectra and light curves for models of supernovae driven by fast bipolar outflows. These allow us to make self-consistent predictions for the orientation dependence of both color evolution and spectral features. We compare models with different degrees of asphericity and metallicity and find significant observable consequences of both. In aspherical models, we find spectral and light curve features that vary systematically with observer orientation. In particular, we find that the early-phase light curves are brighter and bluer when viewed close to the polar axis but that the peak flux is highest for equatorial (off-axis) inclinations. Spectral line features also depend systematically on observer orientation, including the velocity of the Si II 6355 Å line. Consequently, our models predict a correlation between line velocity and color that could assist the identification of supernovae associated with off-axis jet-driven explosions. The amplitude and range of this correlation depends on the degree of asphericity, the metallicity, and the epoch of observation but we find that it is always present and acts in the same direction. © 2012. The American Astronomical Society. All rights reserved..

Gamma-ray diagnostics of Type Ia supernovae. Predictions of observables from three-dimensional modeling

Context. Although the question of progenitor systems and detailed explosion mechanisms still remains a matter of discussion, it is commonly believed that Type Ia supernovae (SNe Ia) are production sites of large amounts of radioactive nuclei. Even though the gamma-ray emission due to radioactive decays is responsible for powering the light curves of SNe Ia, gamma rays themselves are of particular interest as a diagnostic tool because they directly lead to deeper insight into the nucleosynthesis and the kinematics of these explosion events. Aims: We study the evolution of gamma-ray line and continuum emission of SNe Ia with the objective of analyzing the relevance of observations in this energy range. We seek to investigate the chances for the success of future MeV missions regarding their capabilities for constraining the intrinsic properties and the physical processes of SNe Ia. Methods: Focusing on two of the most broadly discussed SN Ia progenitor scenarios - a delayed detonation in a Chandrasekhar-mass white dwarf (WD) and a violent merger of two WDs - we used three-dimensional explosion models and performed radiative transfer simulations to obtain synthetic gamma-ray spectra. Both chosen models produce the same mass of 56Ni and have similar optical properties that are in reasonable agreement with the recently observed supernova SN 2011fe. We examine the gamma-ray spectra with respect to their distinct features and draw connections to certain characteristics of the explosion models. Applying diagnostics, such as line and hardness ratios, the detection prospects for future gamma-ray missions with higher sensitivities in the MeV energy range are discussed. Results: In contrast to the optical regime, the gamma-ray emission of our two chosen models proves to be quite different. The almost direct connection of the emission of gamma rays to fundamental physical processes occurring in SNe Ia permits additional constraints concerning several explosion model properties that are not easily accessible within other wavelength ranges. Proposed future MeV missions such as GRIPS will resolve all spectral details only for nearby SNe Ia, but hardness ratio and light curve measurements still allow for a distinction of the two different models at 10 Mpc and 16 Mpc for an exposure time of 106 s. The possibility of detecting the strongest line features up to the Virgo distance will offer the opportunity to build up a first sample of SN Ia detections in the gamma-ray energy range and underlines the importance of future space observatories for MeV gamma rays.