Environmental Gamma Research Articles

Estimating soil moisture from environmental gamma radiation monitoring data

AbstractSoil moisture (SM) information is invaluable for a wide range of applications, including weather forecasting, hydrological and land surface modeling, and agricultural production. However, there is still a lack of sensing information that adequately represents root‐zone SM for longer periods and larger spatial scales. One option for root‐zone SM observation is terrestrial gamma radiation (TGR), as it is inversely related to SM. Hence, the near real‐time data of more than 5000 environmental gamma radiation (EGR) monitoring stations archived by the EUropean Radiological Data Exchange Platform (EURDEP) is a potential source to develop a root‐zone SM product for Europe without extra investments in SM sensors. This study aims to investigate to what extent the EURDEP data can be used for SM estimation. For this, two EGR monitoring stations were equipped with in situ SM sensors to measure reference SM. The terrestrial component of EGR was extracted after eliminating the contributions of rain washout and secondary cosmic radiation, and used to obtain a functional relationship with SM. We predicted the weekly volumetric SM with a root mean square error of 7%–9% from TGR measurements. Nevertheless, we believe that this technique, due to its greater penetration depth and long data legacy, can provide useful data complementary to satellite‐based remote sensing techniques to estimate root‐zone SM at the continental scale.

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

Assessment of Environmental Background Gamma Radiation Variation in Minna Area of Nigeria

Radiation has been acknowledged to be responsible for deleterious conditions in living tissues. Hence, environmental background gamma radiation (BGR) measurement is crucial from an environmental and health perspective. In this study, due to the absence of comprehensive background gamma radiation data and the increasing numbers of anthropogenic activities that could increase the BGR level, such as where mining activities are active. The BGR in the Minna area of Niger State, Nigeria, was measured and analyzed in this study. In-situ measurement of the background gamma radiation level was carried out using a well-calibrated portable handheld GQ GMC-500 Plus nuclear radiation detector at an elevation of about 1.0 m above ground level. A global positioning system from Garmin (GPSmap 78s) was adopted for identifying geographical locations. A total of 1172 points were surveyed across the study area for background environmental radiation. The BGR values ranged from 0.102 to 0.147 μSv/h, with an overall mean value of 0.126 μSv/h. The average measured dose rate was more than twice the reported world average value of 0.059 μSv/h. The annual effective dose equivalent (AEDE) for the research area was calculated to be 0.221 mSv/y on average. The mean AEDE is lower than the ICRP recommended limit. This shows that the population of the Minna area is radiologically safe based on the estimated AEDE value. Similarly, the excess lifetime cancer risk (ELCR) value ranged from 0.626 × 10−3 to 0.901 × 10−3 mSv/y with a mean value of 0.774 ± 0.09 × 10−3 mSv/y. The mean value of AEDE is below the 0.24 mSv/y permissible limits as recommended by the International Commission on Radiological Protection (ICRP). The mean ELCR value exceeds the average world value of 0.29 × 10−3. Also, the mean organ dose values estimated for the whole body, liver, kidney, testes, bone marrow, ovaries, and lungs are 0.150 ± 0.02, 0.102 ± 0.01, 0.137 ± 0.02, 0.181 ± 0.02, 0.152 ± 0.02, 0.128 ± 0.02 and 0.141 ± 0.02 mSv/y respectively. The differences in the calculated mean of BGR were attributed to natural and human factors. Geological variation is a fundamental factor that influences the changes in BGR. Human activities, mining, building materials, and the use of phosphate fertilizers in agricultural practices are responsible for the differences in BGR. The ELCR implies that terrestrial gamma radiation does not pose any immediate radiological health effects on residents of the area, but there is a tendency for long-term health hazards in the future, such as cancer, due to the dose accumulated.

Unveiling Insights: Harnessing the Power of the Most-Frequent-Value Method for Sensor Data Analysis.

The paper explores the application of Steiner's most-frequent-value (MFV) statistical method in sensor data analysis. The MFV is introduced as a powerful tool to identify the most-common value in a dataset, even when data points are scattered, unlike traditional mode calculations. Furthermore, the paper underscores the MFV method's versatility in estimating environmental gamma background blue (the natural level of gamma radiation present in the environment, typically originating from natural sources such as rocks, soil, and cosmic rays), making it useful in scenarios where traditional statistical methods are challenging. It presents the MFV approach as a reliable technique for characterizing ambient radiation levels around large-scale experiments, such as the DEAP-3600 dark matter detector. Using the MFV alongside passive sensors such as thermoluminescent detectors and employing a bootstrapping approach, this study showcases its effectiveness in evaluating background radiation and its aptness for estimating confidence intervals. In summary, this paper underscores the importance of the MFV and bootstrapping as valuable statistical tools in various scientific fields that involve the analysis of sensor data. These tools help in estimating the most-common values and make data analysis easier, especially in complex situations, where we need to be reasonably confident about our estimated ranges. Our calculations based on MFV statistics and bootstrapping indicate that the ambient radiation level in Cube Hall at SNOLAB is 35.19 μGy for 1342 h of exposure, with an uncertainty range of +3.41 to -3.59μGy, corresponding to a 68.27% confidence level. In the vicinity of the DEAP-3600 water shielding, the ambient radiation level is approximately 34.80 μGy, with an uncertainty range of +3.58 to -3.48μGy, also at a 68.27% confidence level. These findings offer crucial guidance for experimental design at SNOLAB, especially in the context of dark matter research.

A silicon photomultiplier based compact gamma spectrometer for environmental gamma radiation monitoring networks.

In this paper, the details of the development and performance characterisation of a compact, low-power gamma spectrometer for environmental gamma radiation monitoring networks are presented. To reduce the power consumption and the size of the spectrometer, a gamma detector comprising a silicon photomultiplier coupled to a Gd3Ga3Al2O12:Ce,B (GGAG:Ce,B) scintillator has been used for gamma spectrometry. Initially, a Monte Carlo simulation study was carried out to verify the suitability of the 5mm×5mm×5mm GGAG:Ce,B crystal for spectrometry of gamma sources in the energy range 60-1332keV. For minimising the power consumption, the signal processing electronics has been custom designed. This electronics was realised using standard off-the-shelf components to reduce the cost. The developed spectrometer is of size 16cm×10cm×6cm, weighs 600g and consumes 600mW power. The spectrometer is developed such that it could be directly interfaced with GSM/Xbee for wireless communication with the radiation monitoring networks. The lower-level discriminator threshold of the system is 40keV and the total electronic noise is <20keV. The experimentally measured sensitivity of the spectrometer for 137Cs (662keV) is 2.4 cps/μGy/h at 3.5V overvoltage. The spectrometer offers excellent linearity over the measured energy range of 60-1332keV and an energy resolution of ~10% for 662keV gamma-ray at room temperature.

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.

Full background decomposition of the CONUS experiment

The CONUS experiment is searching for coherent elastic neutrino nucleus scattering of reactor anti-neutrinos with four low-energy threshold point-contact high-purity germanium spectrometers. Excellent background suppression within the region of interest below 1 keV (ionization energy) is absolutely necessary to enable signal detection. The collected data also make it possible to set limits on various models regarding beyond the standard model physics. These analyses benefit as well from the low background level of sim 10 d^{-1} kg^{-1} below 1 keV and at higher energies. The low background level is achieved by employing a compact shell-like shield that was adapted to the most relevant background sources at the shallow depth location of the experiment: environmental gamma radiation and muon-induced secondaries. Overall, the compact CONUS shield including the active anticoincidence muon-veto reduces the background by more than four orders of magnitude. The remaining background is described with validated Monte Carlo simulations which include the detector response. It is the first time that a full background decomposition in germanium operated at a reactor site has been achieved. Next to the remaining muon-induced background, ^{210}Pb within the shield and cryostat end caps, cosmogenic activation and airborne radon are the most relevant background sources. The reactor-correlated background is negligible within the shield. The validated background model, together with the parameterization of the noise, is used as input to the likelihood analyses of the various physics cases.

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.

Real-time Environmental Gamma Dose Monitoring around Dhaka University Campus and Estimation of Excess Lifetime Cancer Risk on Public Health

Real-time Environmental Gamma Dose Monitoring around Dhaka University Campus and Estimation of Excess Lifetime Cancer Risk on Public Health

Assessment of environmental gamma dose in air in Ho Chi Minh city, Vietnam

Assessment of environmental gamma dose in air in Ho Chi Minh city, Vietnam

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.

Dose calibration of Health Canada's Fixed Point Surveillance system for environmental radiation monitoring in terms of air kerma and H*(10)

The environmental radiation exposure in Canada has been monitored since 2002 by Health Canada's Fixed Point Surveillance network. The network consists of over eighty 7.6 cm × 7.6 cm sodium iodide spectrometers, and routinely reports to the public the environmental gamma radiation level throughout Canada. This paper describes the latest dose calibrations to air kerma and ambient dose equivalent for the future upgraded network. The calibration curves were developed using Monte Carlo techniques and further optimized via experiments in various reference fields. The dose calibration was validated over a wide range of gamma energy, dose measurement range, and angle of incidence under laboratory conditions. In environmental monitoring situations, the angular distribution of radiation exposure was analytically calculated by assuming a semi-infinite plume source, semi-infinite planar source, and infinite volume sources for the respective exposure scenarios of radioactive plume, ground contamination, and soil source. By coupling the resultant radiation angular distribution with detector's angular variation on dose response, the overall accuracy of dose measurement in each of these environmental scenarios was estimated. The accuracy is expected to be within ±3.7% for plume radiation, −5.6% for 137Cs ground contamination, and 0% to −17.1% for soil radioactive sources. The under-estimation for soil sources is mainly caused by absorption of radiation in the electronic system underneath the crystal.

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.

Investigation of a SiPM-GGAG:Ce,B scintillator detector for environmental gamma radiation monitoring

A study of a silicon photomultiplier (SiPM) coupled with a GGAG:Ce,B scintillator detector for environmental gamma radiation monitoring is presented in this paper. FLUKA based Monte Carlo simulations were carried out for the optimization of scintillator material and geometry for this application. Based on the simulation study, the dimensions of GGAG:Ce,B scintillator crystal were finalized and the scintillator was prepared. The detector was assembled by optically coupling to a commercially available SiPM. The analog output pulses of the SiPM were amplified by a voltage sensitive amplifier and subsequently counted using a microcontroller. The linearity of the detector response with gamma dose rate was verified using 137Cs standard gamma source. The radiation response of the detector for different gamma energies was investigated using standard 137Cs, 241Am and 60Co sources. The variation of detector sensitivity with SiPM overvoltage was measured for choosing an optimal overvoltage for the SiPM operation. The experimentally observed response of the SiPM-GGAG:Ce,B detector was very linear in the measurement range of 3.5–300 μGy/h with a sensitivity of 2.44 cps/μGy/h. The gamma response study of the detector confirm the suitability of the developed detector for making a compact and low power gamma monitor for environmental gamma radiation monitoring network.

Evaluating environmental radiations of the tomotherapy facility by optimizing full factorial design of the TLD technique

BACKGROUND: In the last 40 years, the number of deaths due to cancer has been the highest in TaiwanOBJECTIVE: To optimize the readout system of the thermoluminescent dosimeter (TLD)-100H, the radiation rates among the Tomotherapy (TOMO) facility of the Department of Radiology Oncology of Chung Shan Medical University Hospital (CSMUH) were calculated with a 3 full factorial design (FFD). METHODS: A ten-month survey of the facility was employed using the sensitive and accurate TLD method. The TLD system was optimized for maximum temperature, heat rate, and preheat temperature of Harshaw 3500 reader. Eight analyzed groups with different factors were tested.RESULTS: The TOMO facility had significantly different radiation rates. The farther away from the gantry head, environmental radiation rates. The half value layer (HVL) was also determined. These results were compared with published. No significant contributions of environmental gamma radiations were detected except in the treatment room.CONCLUSIONS: Those were far below the occupational doses recommended by ICRP 60.

The Influence of Environmental Stress Cracking (ESC) and Gamma Irradiation on the Mechanical Properties of Polycarbonate: Study of Synergistic Effects

Polycarbonate is an engineering polymer due its outstanding properties and is widely used in several different applications. In some of these applications it can be exposed to certain liquids/solvents. In many cases, this liquid exposure may cause an effect known as Environmental Stress Cracking (ESC), which may lead to crack formation on the polymer surface and consequent reduction of its mechanical resistance, with loss of lifetime. On the other hand, polycarbonate medical supplies are often exposed to gamma rays in the radio-sterilization process, at doses up to 25 kGy. This exposure causes main chain scissions. In this present work, the viscosity average molecular weight decreased about 10% at 25 kGy. Elongation at break was drastically affected by ESC phenomenon. When simultaneously exposed to the ESC agents (methanol or isopropanol) and gamma radiation, combined effects of both takes place. Moreover, the stress relaxation rate of ~1000 Pa/s (air or methanol) and ~2200 Pa/s (isopropanol) at the dose of 100 kGy, suggests strong influence of isopropanol as surfactant on PC. Results of elongation at break and stress relaxation rate were reliable data to evaluate ESC and radiolytic effects on PC.

Countrywide Monitoring of Environmental Gamma Radiation in India

Countrywide Monitoring of Environmental Gamma Radiation in India

Outdoor Environmental Radiation Monitoring and Estimation of Radiation Risk on Public in New Market Thana, Dhaka, Bangladesh

The Real-time outdoor environmental gamma radiation (RTOEGR) dose rates were monitored at New Market Thana in Dhaka city to generate a baseline database that would help to know any deviation after operation of Rooppur NPP. The RTOEGR monitoring was carried out using a digital portable radiation monitoring device (DPRMD). The RTOEGR dose rates at the area of New Market Thana were ranged from 0.103 ± 0.004 µSv/h to 0.168 ± 0.007 µSv/h with an average of 0.135 ± 0.004 µSv/h. The public's annual effective doses were calculated based on RTOEGR dose rates, and those were varied from 0.181 ± 0.007 mSv to 0.295 ± 0.007 mSv with an average of 0.238 ± 0.007 mSv. Excess Lifetime Cancer Risk (ELCR) on public health was estimated based on the annual effective dose. The Public's ELCR were from 0.720×10-3 to 1.174×10-3 with an average of 0.892×10-3, which is higher than the worldwide standard value of 0.29×10-3. The mean RTOEGR dose rate of the New Market Thana in Dhaka city is comparable to that of Sabzevar city (Iran), Kathmandu city of Tribhuvan University (Nepal), Baghdad city (Iraq), Kirikkale city (Turkey).

Monte Carlo Simulations of scintillation detectors for the use as dosemeters

The energy dependent conversion factors from measured photon pulse height spectra to ambient dose equivalent (H*(10)) of three different detectors based on the scintillation materials CeBr_3, LaBr3 and SrI2 were simulated with the three Monte Carlo Codes, GEANT4, MCNP and PENELOPE, respectively. The performance of the detection systems, using the calculated conversion factors (fitted to response functions), is demonstrated for different scenarios ranging from laboratory conditions (i.e. a precisely defined radiation field in a calibration facility) to a free-field irradiation scenario produced by the natural radioactivity at a large lawn. With very simple geometric models of the detector systems, the response function of scintillation based dosemeters can be derived from the aforementioned Monte Carlo simulations with an accuracy of the measured doses in H*(10) of ±10% in an photon energy range from 100 keV to 3000 keV, as being typical for natural environmental gamma radiation.

Calculating radiation dose rate from online real-time environmental γ-spectrum using NaI(Tl) detector

Calculating gamma radiation dose rate from online real-time environmental gamma spectrum using NaI(Tl) detector has been developed into a software named RADAPROC V.1 in the Center for Operating the National Network of Environmental Radiation Monitoring And Warning (CONNERMAW). Currently, hundreds of online gamma spectra per day from online monitoring stations are processed to calculate the total ambient dose equivalent rate and the ambient dose equivalent rate of typical natural radioactive isotopes such as K-40, Bi-214, Tl-208 according to the method of using the function G(E) and the photo-peak area method. The calculated results have been compared with the results of calculating the dose rate from the specific activity of radioactive isotopes in soil samples collected at the same monitoring location and analyzed in the laboratory. The difference between the methods is less than 25%. The ambient dose equivalent rates of typical natural radioactive isotopes are a bit higher than those calculated with SARA-NMC software. The software will be improved shortly for better results.