Environmental Dose Research Articles

Survival of the brightest? pIRIR dating of volcanic sediments in Sulawesi, Indonesia, using micro-aliquots of K-rich feldspar

Volcanic sediments are challenging to date with luminescence-based methods. Both main minerals used for dating—quartz and K-rich feldspar—commonly have suboptimal luminescence properties when of volcanic origins, primarily a low signal intensity and, for K-rich feldspars, high rates of anomalous fading. The present work provides a case study of sediment samples from the Leang Bulu Bettue (LBB) archaeological site in Indonesia, a key site in our understanding of the early human occupation of the island of Sulawesi. We show that currently available state-of-the-art methods can provide robust optical ages for volcanic sediments. Through various reliability tests, we establish the suitability of a post-IR IR stimulated luminescence (pIRIR) standardised growth curve (SGC) procedure for De estimation of ‘micro-aliquots’ containing 5–10 grains of K-rich feldspar, and then combine this method with estimates of environmental dose rate to determine 10 new reliable and finite optical ages for the sedimentary deposits at LBB. Furthermore, by applying the LnTn method to circumvent truncation of the De distribution caused by the non-linearity of the dose response curve in the higher dose range, we could extend the site's luminescence-based chronology to span the interval ∼15–210 ka. The new chronology is in keeping with previous radiocarbon and U-series ages for the site's upper layers. We show that the low fading rate of micro-aliquots relative to using large aliquots composed of hundreds of grains lies in a brightness-based selection. By targeting bright grains with low fading rates, the need for fading corrections is greatly reduced and they can be made with a smaller uncertainty propagated through into the final age estimate, resulting in optical ages of improved accuracy and precision for volcanic sediments.

Chronostratigraphy of the Late Glacial Żabinko site (western Poland) and investigation of the dose rate variability

The Żabinko exposure (western Poland) reveals the classic fluvio-aeolian succession known from studies in the European Sand Belt. Previous chronostratigraphic studies were mainly based on uncalibrated radiocarbon dates from organic sediments and thermoluminescence dating. The picture visible from these studies indicated a number of discrepancies between these methods. The new research in this exposure was based on optically stimulated luminescence (OSL) dating and calibrated radiocarbon dates. The results obtained indicate a general discrepancy between the results achieved by these two methods. While the radiocarbon dates provide some meaningful picture and allow correlation with previous studies, the results of OSL dating do not allow for a chronological model of sedimentary processes. The OSL dates show large inversions of the results and are clearly younger than the other dating results. Detailed analysis of OSL measurements shows radioactive disequilibrium and variability linked to differential stratification of sediments, significantly impacting the assessment of environmental dose rates. We believe that this atypical variability is presumably the result of postdepositional processes, such as changes in groundwater levels, chemical weathering and radionuclide migration.

Assessment of environmental radioactivity concentration and effective dose rates from radon gas exposure from water samples in Gezira State, Sudan

A study was conducted in Gezira State, Sudan, to estimate the concentration of radon and the annual effective dose rate in water samples based on inhalation, ingestion, and age group. The study collected 26 samples from different locations. The results showed that the mean concentration of radon was 7.68 ± 1.07 Bq.l−1, and the mean effective dose rate of radon released from water to indoor air was 19.17 ± 2.68 μSv.y−1. The average effective dose rates calculated from ingestion, inhalation, and the total annual effective dose rate were 18.81 ± 2.63, 19.34 ± 2.71, and 38.15 ± 5.34 μSv.y−1, respectively. The annual effective dose rates for infants, children, and adults were calculated to have mean values of 80.60 ± 11.27, 53.73 ± 7.51, and 38.38 ± 5.37 μSv.y−1, respectively. The study found that 23.1% of the samples exceeded the maximum contamination level, while 76.9% were below the reference levels set by the USEPA, WHO, and EU. Despite the increase in radiation dose with age and consumption rates, the radiation dose from water was lower than the recommended limits set by UNSCEAR and WHO. Additionally, the bronchial epithelium received twice the radiation dose compared to the stomach walls.

New chronology of K-feldspar isochron optical dating (iIRSL) in the late Pleistocene coastal aeolian deposits of Southeast China

Old red sand (ORS), which developed during the late Pleistocene, is widely distributed along the coasts of the western Pacific and Indian Ocean.The Optically Stimulated Luminescence (OSL) dating technology have primarily determined its sedimentary age. However, in tropical and subtropical regions, chemical weathering can impact the calculation of environmental dose rates, potentially leading to age biases whose magnitude remains uncertain.Recently, advance in the OSL dating technique, the new K-feldspar isochron dating method (iIRSL), have determined its depositional age. This approach effectively enhances the accuracy of age data by accounting for variations in past dose rates caused by chemical weathering and changes in water content during sample burial. This study used the iIRSL method to conduct infrared stimulated luminescence signal tests on ORS samples from the Haitan Island, south China. Five grain sizes of K-feldspar grains were extracted from each sample during experimentation. The single aliquot regenerative dose method (SAR) was utilized to determine the equivalent dose for each grain size and calculate age using the isochron method (iIRSL). Furthermore, it compared the iIRSL ages with quartz age (SAR). The results indicate that: (1) This study obtained four iIRSL ages, which are consistent with the ages obtained from quartz (SAR) within a reasonable range, ranging from 62.13 ± 4.85 to 39.44 ± 4.85 ka BP. (2) Comparison of the simulation results of different weathering degrees using the iIRSL method and K-feldspar two-step IRIR methods indicates that the iIRSL method can effectively mitigate the impact of chemical weathering on age determination, giving more reliable iIRSL ages. (3) The ORS along the southern coast of China mainly deposited during Marine Isotope Stages 5, 4, and 3, exhibiting relatively higher deposition rates during MIS 5 and MIS 3 at approximately 30 cm/ka and 15 cm/ka respectively. This suggests that the ORS was predominantly deposited during periods of elevated sea levels. However, it is important to note that the data from MIS 5 may have been influenced by the absence of samples from this particular stage and limitations in dating methods, resulting in a lower frequency-density of deposition ages during MIS 5 and creating an “illusion” of sediment interruption.

μDOSE+: Environmental radioactivity and dose rate measurement system with active shielding boosted by machine learning

The μDOSE+ is a novel measurement system designed for environmental radioactivity measurements and trapped charge dating applications. This study describes improvements integrated into the μDOSE+ system. These enhancements include a redesigned counting chamber equipped with an active radon removal system, passive shielding and an active shielding module that is further refined by machine learning algorithms for precise pulse classification. These advancements collectively lead to a significant reduction in background in the β counting window, improved α and β counting efficiency and easier sample handling. This is demonstrated through a comparative analysis with its predecessor, the classical μDOSE system.

Measurement of Environmental Gamma Radiation Dose Rates and Estimation of Radiation Risk near the Construction Site of the Nuclear Power Plant, Indoor and Outdoor Locations of the Research Reactor, and Coal-Fired Thermal Power Plant Area

Measurement of Environmental Gamma Radiation Dose Rates and Estimation of Radiation Risk near the Construction Site of the Nuclear Power Plant, Indoor and Outdoor Locations of the Research Reactor, and Coal-Fired Thermal Power Plant Area

A new OSL dose model to account for post-depositional mixing of sediments

In applications of optically stimulated luminescence (OSL) dating to unconsolidated sediments, the burial age of a sample of grains is estimated using statistical models of the distribution of the experimentally determined equivalent doses of the grains, together with estimates of the environmental dose rate. For grains that have been vertically mixed after deposition (e.g., due to bioturbation), existing dose models may fail to appropriately account for the complexity of the mixing process, thus producing inaccurate age estimates of the original time of deposition of the ‘native’ grains in any particular sample (usually the quantity of most interest). Here we introduce a new dose model, the asymmetric Laplacian mixture model (ALMM), developed for vertically mixed samples with single-grain dose distributions. The approach is based on a continuous statistical mixture that models the displacement of grains in both upward and downward directions. The central dose of the native grains in each sediment sample is estimated by the ALMM, as well as the parameters associated with overdispersion of single-grain dose distributions and the (modelled) mixing process. Using Bayesian methodology, we apply the model to two series of vertically contiguous samples collected at the site of Nawarla Gabarnmang in northern Australia. Independent age estimates obtained from radiocarbon dating of charcoal fragments support the OSL ages for the native grains estimated by the ALMM. Moreover, our study includes sensitivity analyses that show the model is robust to variation in the experimental error of the OSL data, as well as a simulation study that demonstrates the model’s good ability to recover the simulated central dose and its excellent coverage properties. The ALMM is introduced in the context of compound Gaussian distributions, a broadly encompassing statistical framework that includes many of the most commonly used dose models. This unifying and accessible perspective on the statistical modelling of dose distributions will support practitioners in selecting an appropriate model for samples affected by post-depositional mixing, and hopefully stimulate further theoretical developments. A new R package rstanosl is provided that fits the ALMM and other commonly used dose models using Hamiltonian Monte Carlo methods via the Stan programming language.

Influence of decontamination process parameters on ultrasonic decontamination efficiency of pipeline

Many radioactive pollutants will be deposited inside the nuclear power plant pipelines after long-term service, which will form radioactive hot spots and increase the radiation dose rate level of operators. The ultrasonic decontamination efficiency was studied through the establishment of ultrasonic decontamination dynamic test bench, under different decontamination process parameters. It has also been applied in the engineering filed. The results show that: Ultrasonic decontamination efficiency increases with the increase of decontamination power, and the maximum decontamination efficiency of pollutants is up to 62.69%. The main reason is that the mechanical effect and cavitation effect of ultrasonic are significant with the increase of power, which is conducive to the removal of pollutants in the pipeline. When the decontamination time is 60min, the ultrasonic decontamination efficiency is more than 90%. Meanwhile, after ultrasonic decontamination of the pipeline hot spots, the contact dose rate at the pipeline hot spots is reduced by 75.20% at the highest, and the environmental dose rate is reduced by more than 90%, which reduces the collective dose level of operators working near the pipeline hot spot greatly, and ensures the health of the operators and environmental safety.

Optically stimulated luminescence cross-dating from quartz of different grain size

Optically stimulated luminescence (OSL) signals from quartz can be used to determine when a sample was last exposed to sunlight. The total specific energy (dose) absorbed since the last resetting is measured using OSL, and divided by the rate of storage (dose rate) to give the time elapsed from the last heating or daylight exposure. The general equation used to determine the age in luminescence dating is given by the ratio between the Equivalent Dose (ED) and the Annual Dose rate (AD). The ED, measured using luminescence signals, is the total absorbed dose starting from the last "zero event" while the AD, evaluated by in situ and extra situ radioactivity measurements, represents the rate at which energy is absorbed from natural radioactivity present in the sample and in the environment. Evaluation of the environmental dose rate component becomes a crucial point in dating since particular conditions of the site (heterogeneity, lack of structure...) could make age measurement inaccurate. In this work, the conditions for applicability of subtraction dating are tested on a sediment of known age; it allows an age determination that is independent of knowledge of the environmental dose-rate.

Post-violet infrared stimulated luminescence (pVIRSL) dating protocol for potassium feldspar

Devi et al. (2022) suggested that post-violet infrared stimulated luminescence (pVIRSL; IRSL at 100 °C after a violet bleach at 50 °C) of K-feldspars, generally has a near zero athermal fading rate. This study explores the mechanism and suitability of the pVIRSL signal for dating applications. The results suggest that pVIRSL is a recuperated signal, arising from the eviction of charges in deep traps by violet stimulation followed by their recapture to the IR traps. A post-violet IR single aliquot regenerative dose (pVIR-SAR) protocol worked well for seven K-feldspar samples from varied depositional environments with ages ranging from 6 to 286 ka. The pVIRSL paleodoses of most samples, accorded with paleodoses computed using the published ages and their environmental dose rates.

Comprehensive Investigation of Neolithic Ceramic Samples: Firing Technology and Age Insights

Thermogravimetric (TG/DTG), thermoluminescence (TL), and X-ray powder diffraction (XRD) techniques were applied to characterize samples collected from the archaeological site of Polutepe in Azerbaijan, dating to the Neolithic period, and gave new information on the firing technology. The thermogravimetric analysis of ceramic shards from Polutepe revealed that the firing temperature of the samples was in the range of 700°C, based on the presence of calcite in the sample. XRD analysis confirmed the presence of quartz, feldspar, and clay minerals in the ceramic samples. According to XTD analysis the mineral composition of the ceramic sample from Polutepe site was as follows: Quartz-33.8 mass%, Feldspar (albite)-21.7 mass%, Muscovite- 33.6 mass%, and Calcite- 10.9 mass%.
 TL glow-curve intensity at 325°C was measured to estimate the historical dose of the sample, which was found to be 22.19±1.36 Gy. The concentration of U, Th, and K were 2.24±0.20 ppm , 8.31±0.80 ppm, 2.39±0.23% respectively. Dose rate and age calculation were conducted using the DRAC, version 1.2 and output results are as follows: Environmental dose rate: 3.46±0.19 mGy/a; Age of the sample: 4.400±530 BC years which are in line with the stratigraphically estimated age of this area and with the radiocarbon age (4270±160 BC) reported in our previous work. The results obtained from this multidisciplinary approach provide insights into the firing technology and age of the ceramic samples.

Characterising and correcting for a previously unconsidered source of scatter in measurements of equivalent dose

Single aliquot methods make it feasible to routinely determine multiple estimates of equivalent dose (De) for a sample. The scatter in De values observed within a sample has been used previously to make inferences about the resetting of the luminescence signal being measured prior to the event dated, about post-depositional processes that may have affected the sample, and about spatial variations in environmental dose rate on a small (millimetre) scale. However, in addition to processes associated with deposition and burial, scatter in the De values generated may also arise if the dose rate from the beta source used as part of the De determination method varies between grains or aliquots. Spatial variation in the beta dose arising from 90Sr plaque beta sources has been known for more than 20 years. What has not previously been described is variation in beta dose rate between different sample positions on the Risø TL/OSL instruments, one of the most widely used commercial systems used for luminescence dating. The variation arises from misalignment of the carousel used to hold samples with respect to the lid upon which the beta source is mounted. For one instrument in this study, this misalignment led to variations in apparent dose between different carousel positions of 14%. For most instruments the variability was lower (0.15–∼2%), but still detectable. A method for assessing the severity of this problem for individual instruments is described, along with a procedure for correcting for the effect and thus reducing the impact of this hitherto undescribed source of scatter in De.

Machine learning to predict environmental dose rates from a radionuclide therapy service — a proof of concept study

The Ionising Radiation Regulations 2017 requires prior risk assessment calculations and regular environmental monitoring of radiation doses. However, the accuracy of prior risk assessments is limited by assumptions and monitoring only provides retrospective evaluation. This is particularly challenging in nuclear medicine for areas surrounding radionuclide therapy patient bathroom wastewater pipework. Machine learning (ML) is a technique that could be applied to patient booking records to predict environmental radiation dose rates in these areas to aid prospective risk assessment calculations, which this proof-of-concept work investigates. 540 days of a dosimeters historical daily average dose rate measurements and the corresponding period of department therapy booking records were used to train six different ML models. Predicted versus measured daily average dose rates for the following 60 days were analysed to assess and compare model performance. A wide range in prediction errors was observed across models. The gradient boosting regressor produced the best accuracy (root mean squared error = 1.10 µSv.hr−1, mean absolute error = 0.87 µSv.hr−1, mean absolute percentage error = 35% and maximum error = 3.26 µSv.hr−1) and goodness of fit (R 2 = 0.411). Methods to improve model performance and other scenarios where this approach could prove more accurate were identified. This work demonstrates that ML can predict temporal fluctuations in environmental radiation dose rates in the areas surrounding radionuclide therapy wastewater pipework and indicates that it has the potential to play a role in improving legislative compliance, the accuracy of radiation safety and use of staff time and resources.

Process identification and discrimination in the environmental dose rate time series of a radiopharmaceutical facility using machine learning techniques

Multi-facility nuclear sites with research reactors have several environmental area gamma monitors in a network as a part of their surveillance capability. However, the routine release of low levels of 41Ar gas from the reactor is prone to interfere with the recorded gamma dose rate and mask the genuine processes being monitored at the network's central control room. As a potential solution, machine learning techniques have been used in this study to autonomously identify and discriminate the genuine processes, viz., the radioactive consignment loading and its movement, at an interim radiopharmaceutical facility located close to a research reactor. To increase the richness of the recorded univariate dose rate time series, several additional features were created. A labelled dataset of process and non-process dose rate sub-sequences or segments was generated by subject matter experts, based on practical knowledge of the facility, and aided by k-means clustering algorithm. The labelled dataset was used to train several supervised classification models and the random forest class of models gave superior performance. The optimised random forest model was able to identify process sub-sequences with a precision of 82.35% and a specificity of 97.11%. The overall balanced accuracy of the model was 91% with a f1 score of 82%. This machine learning approach proved useful to autonomously identify genuine process driven sub-sequences in the univariate dose rate time series. It has an application in reducing the false alarms at exit portal monitors, especially at those sites where there is a potential for external interference in the monitored dose rate.

Identification and quantification of anomalies in environmental gamma dose rate time series using artificial intelligence

Gamma dose rate (GDR) monitors are the most widely used tool for continuous monitoring of environmental radioactivity. They are inexpensive to procure and operate, and generally require little maintenance. However, since no spectral information is available, the detection limit for irregularities is correspondingly high; A value around 20 nSv/h is often called out.By adding weather data to the GDR measurement and a sequence of machine learning algorithms, the anomaly detection sensitivity can be significantly increased while simultaneously decreasing the number of false positives. The algorithms were designed such that an integrated safety net prevents false negatives. First, the precipitation-induced GDR peaks from washed-out Radon progeny are removed by means of regression, provided that a check of the regression parameters shows sufficient agreement with past data at the measurement site. A neural network then calculates the expected value of the remaining GDR baseline for the prevailing conditions. Finally, an anomaly detection is carried out on the remainder between the expected and actual GDR baseline value. Extreme value theory is used to detect point anomalies, and hierarchical clustering of subsequences for slower processes. By combining the two detection methods, the full spectrum of irregularities is covered.The algorithms were implemented in Python and trained with real measurement data from the German GDR monitoring network. For verification, the data were enriched with results from JRODOS simulations of a nuclear power plant accident. Altogether, the presented methodology can lower the detection limit of irregularities to about 4 nSv/h, i. e. about a factor of 5 below the previous consensus value. The algorithm detects as well as quantifies the anomaly in the GDR, allowing for additional conclusions like potentially involved isotopes. Most important, it allows to refrain from the current practice of defining fixed alarming thresholds between the two contradicting goals of high sensitivity and low false alarm rate. Instead, it allows to transition to the more natural alarming on deviations from the expectation.

Potential increased radiological risk in cargo scanning activity

The image-based cargo inspection systems are generally intended to identify illegal practices. However, imaging processes from the scanning of motorized containers have been used for increasing industrial safety. This is made possible by the application of high-energy particle linear accelerators (linac). Measurements of both the environmental equivalent dose rate (δH*(10), and the integrated environmental equivalent dose (H*(10) were performed. The estimation of δH*(10) and H*(10) in the scanning channel, including the driver’s cab of the truck transporting the container, is critical. The aim of this study is to check the radiological safety for occasional users (drivers) by comparing the levels of δH*(10) and H*(10) with those adopted for public exposure. The study was experimentally conducted in a cargo and container inspection facility that uses a linac operating at the maximum energy of 4.5 MeV. During the in situ measurements, a SpiR-ID identifier detector Model F 8929 MGP manufactured by Mirion Technologies was used. The measurements in the driver’s cab suggest that the procedure can be considered safe. However, a fast transient of δH*(10) was identified recording raised values (peaks) around 210× the threshold for public exposures in the first 9 s of each scanning procedure.

Environmental Gamma Radiation Measurement, Dose Rate and Lifetime Cancer Risk Assessment in Malatya Province and its Districts

Bu çalışmada, Malatya ilinde, 15 farklı noktada, gama doz hızı ölçümleri yapılmıştır. Ölçümler, her noktada hem yerde hem de yerden 1 m yükseklikte alınmıştır. Gama doz hızı ölçümleri NaI (Tl) kristaline sahip taşınabilir bir sintilasyon sayacı kullanılarak yapılmıştır. Gama doz hızlarına (DR) ek olarak, yıllık etkin doz oranları (YEDO) ve ömür boyu kanser riski (ÖBKR) değerleri de hesaplanmıştır. Yerden 1 m yükseklikte DR, YEDO ve ÖBKR için elde edilen ortalama değerler, sırasıyla, 48,47 nGy/h, 58,18 µSv/y ve 0,2110-3 olarak hesaplanmıştır. Bu çalışmada sunulan sonuçlar, Türkiye’nin farklı bölgelerinde yapılan benzer çalışmaların sonuçları ve UNSCEAR tarafından verilen dünya ortalama değerleri ile karşılaştırılmıştır.

CRYSTAL CONFIGURATION DEPENDENCE OF CSI(TL) SCINTILLATION DETECTORS ON ENVIRONMENTAL DOSE RATE MEASUREMENT.

The crystal configuration dependence of thallium-doped caesium iodide (CsI(Tl)) scintillation detectors was analysed on an ambient dose equivalent (H*(10)). H*(10) were systematically calculated in various crystal conditions for aspect ratios and sizes in a virtual environment contaminated by radionuclides to investigate directional characteristics by comparing the H*(10)s with the typical irradiation geometries in anterior-posterior (AP), lateral (LAT), rotational (ROT) and isotropic (ISO). The simulation revealed that H*(10) obviously changes according to the crystal configuration and cuboidal CsI(Tl) scintillation detectors with specific aspect ratios could be applied to environmental dose rate measurement without further changes in the calibration procedure.

Environmental Gamma Dose Rate Monitoring and Radon Correlations: Evidence and Potential Applications

Gamma emitting radionuclides naturally present in the Earth’s crust and the radon exhaled by soil in the atmosphere with its short-lived progeny are two of the main contributors to the environmental gamma dose rate that typically characterizes an outdoor measurement site. The present work aims to investigate variations in the environmental dose-rate time series originated by different natural phenomena, such as weather and seismic events, which can modify the radon concentration in the air. The data analyzed here were acquired over a five-year period using a Reuter–Stokes high-pressure ionization chamber placed in the ENEA Casaccia Research Center (Rome, Italy), from November 2013 to December 2018. The detector was set to take a single measurement of the equivalent ambient dose H*(10) every 15 min, thereby collecting more than 184,000 values over the five-year period under consideration. The detector’s sensitivity to the short-lived radon progeny was verified in a preparatory study performed by means of simultaneous radon flux measurement on field. Variations induced by meteorological events as well as variations potentially induced by seismic events were investigated by implementing different data analysis techniques. In the latter case, a retrospective preliminary study was conducted, applying the ARFIMA class of models in order to test the method’s potential. The analysis techniques, results and potential applications are presented and discussed in this article.

Reduced Environmental Dose Rates Are Responsible for the Increased Susceptibility to Radiation-Induced DNA Damage in Larval Neuroblasts of Drosophila Grown inside the LNGS Underground Laboratory.

A large amount of evidence from radiobiology studies carried out in Deep Underground Laboratories support the view that environmental radiation may trigger biological mechanisms that enable both simple and complex organisms to cope with genotoxic stress. In line with this, here we show that the reduced radiation background of the LNGS underground laboratory renders Drosophila neuroblasts more sensitive to ionizing radiation-induced (but not to spontaneous) DNA breaks compared to fruit flies kept at the external reference laboratory. Interestingly, we demonstrate that the ionizing radiation sensitivity of flies kept at the LNGS underground laboratory is rescued by increasing the underground gamma dose rate to levels comparable to the low-LET reference one. This finding provides the first direct evidence that the modulation of the DNA damage response in a complex multicellular organism is indeed dependent on the environmental dose rate.