An in situ method for the high resolution mapping of 137Cs and estimation of vertical depth penetration in a highly contaminated environment

Abstract

The Chernobyl nuclear power plant meltdown has to date been the single largest release of radioactivity into the environment. As a result, radioactive contamination that poses a significant threat to human health still persists across much of Europe with the highest concentrations associated with Belarus, Ukraine, and western Russia. Of the radionuclides still prevalent with these territories Cs presents one of the most problematic remediation challenges. Principally, this is due to the localised spatial and vertical heterogeneity of contamination within the soil (~10's of meters), thus making it difficult to accurately characterise through conventional measurement techniques such as static in situ gamma-ray spectrometry or soil cores. Here, a practical solution has been explored, which utilises a large number of short-count time spectral measurements made using relatively inexpensive, lightweight, scintillators (sodium iodide and lanthanum bromide). This approach offers the added advantage of being able to estimate activity and burial depth ofCs contamination in much higher spatial resolution compared to traditional approaches. During the course of this work, detectors were calibrated using the Monte Carlo Simulations and depth distribution was estimated using the peak-to-valley ratio. Activity and depth estimates were then compared to five reference sites characterised using soil cores. Estimates were in good agreement with the reference sites, differences of ~25% and ~50% in total inventory were found for the three higher and two lower activity sites, respectively. It was concluded that slightly longer count times would be required for the lower activity (<1MBqm) sites. Modelling and reference site results suggest little advantage would be gained through the use of the substantially more expensive lanthanum bromide detector over the sodium iodide detector. Finally, the potential of the approach was demonstrated by mapping one of the sites and its surrounding area in high spatial resolution.

Reconstructing the deposition environment and long-term fate of Chernobyl 137Cs at the floodplain scale through mobile gamma spectrometry

“…In this study, the software package Monte Carlo N-Particle 5 code (MCNP5) was used to obtain spectral responses in order to derive PVR values for appropriate depth distribution (Briesmeister, 1993). To ensure that each depth distribution could be adequately modelled, disk-shaped source descriptions measuring 10 mm thick were simulated down to a depth of 70 g cm -3 (Varley et al, 2017). In this manner the PVR could be defined with higher depth resolution and facilitated improved counting statistics as the maximum particle number in MCNP5 (2×10 -9 ) could be run for each simulation, thereby effectively increasing the source density without repeated random number sampling (Hendriks et al, 2002).…”

“…Recently, Varley et al, (2017) demonstrated that through the use of the peak-to-valley ratio (PVR) improved inventory estimates could be made for aged Chernobyl deposits in Belarus.…”

“…Following the calibration and validation work of assessing the PVR method for mobile handheld gamma spectrometry (Varley et al, 2017) it was apparent that one calibration site exhibited a systematic change in the deposited 137 Cs activity and depth distribution towards a tributary of the Pripyat River. The primary aim was to follow up on this observation and to complete a high resolution (<1 m) mobile gamma spectrometry survey across the flood plain to characterise and explain the systematic distribution in a landscape that had been highly impacted by the 1986 Chernobyl accident and that had hitherto been considered to be highly heterogenous with regards to the 137 Cs distribution.…”

Nonintrusive Depth Estimation of Buried Radioactive Wastes Using Ground Penetrating Radar and a Gamma Ray Detector

“…This can have significant impact on the decommissioning cost because these materials are usually present in large volumes in contaminated sites [2]. Sources of contamination of this porous materials especially soil include fall out from nuclear weapons testing; nuclear accidents e.g., the Chernobyl and Fukushima accidents; and poor disposal of nuclear wastes [3][4][5]. In addition, the presence of these contaminants in the soil constitute a major public hazard due to their long half-life and chemical behaviour.…”

“…However, traditional methods of depth estimation such as core sampling and logging are slow and have limited spatial sampling extent because of their intrusive nature. Furthermore, the nonintrusive methods reported in [5,[7][8][9][10][11][12][13][14] are either based on regressional models whose parameters typically have no physical significance or are limited to specific radioactive sources. Also, other nonintrusive methods reported in [15,16] use specialised shielding and collimator arrangements while those that employ machine learning [17][18][19] require significant amount of data to train the algorithms.…”