The development of nuclear power plants is progressing rapidly worldwide. However, there is currently a lack of dynamic monitoring of the thermal discharge temperature rise from these plants, making it unclear to governments where their nuclear power thermal discharges stand globally. We hypothesize that between 2013 and 2022, there are significant temporal and spatial differences in the thermal discharge temperature rise from nuclear power plants globally. Temporal differences are expected to reflect a country\'s nuclear power installed capacity and thermal discharge treatment capabilities, while spatial differences are related to the type of water bodies where nuclear power plants are located. To test these hypotheses, we utilized Landsat data to get the distribution range of thermal discharge and temperature rise levels ranging from 1 °C to 4 °C, and compared the temporal and spatial characteristics of temperature rise in different countries. The results indicate that: (1) Currently, China, the United States, and Canada rank among the top three globally in terms of the area experiencing temperature rise due to thermal discharge, which correlates with the total installed capacity of nuclear power in these countries. (2) Countries such as Russia, Finland, and Mexico exhibit larger areas with a 4 °C temperature rise level per unit installed capacity, with their thermal rise area per unit installed capacity (TRAUIC) exceeding the global average by more than 1.5 times. (3) The spatial dispersion trends of thermal discharges from nuclear power plants vary across different types of water bodies. For nuclear power plants located in bays, thermal discharges primarily disperse along the coast, while in open sea and lakes, thermal discharges tend to spread in a fan-shaped pattern. The findings of this study are crucial for understanding the efficiency of thermal discharge from nuclear power plants across different countries globally, assessing potential environmental risks during the operation of these plants, and promoting the safe and orderly development of nuclear power plants worldwide.

The mission of Atomic Energy Regulatory Board (AERB) of India is to ensure that the use of ionising radiation and nuclear energy in India does not cause unacceptable impact on the workers, members of the public and to the environment. AERB has the mandate to carry out detailed safety review for the siting, construction, commissioning, operation and decommissioning of nuclear and radiation facilities established within the country. To deliver and maintain a strong, credible and technically sound regulation, AERB has established the Safety Research Institute (SRI) at Kalpakkam with a robust technical infrastructure and wide knowledge base. This paper highlights the independent safety research activities carried out at SRI and its role to support and facilitate the decision-making process by AERB at various stages of regulatory review for ensuring safety of the nuclear facilities in India.

Global nuclear power is surging ahead in its quest for global carbon neutrality, eyeing an anticipated installed capacity of 436 GW for coastal nuclear power plants by 2040. As these plants operate, they emit substantial amounts of warm water into the ocean, known as thermal discharge, to regulate the temperature of their nuclear reactors. This discharge has the potential to elevate the temperature of the surrounding seawater, potentially influencing the marine ecosystem in the discharge vicinity. Therefore, our study area is on the Qinshan and Jinqimen Nuclear Power Plants in China, employing a blend of Landsat 8/9, and unmanned aerial vehicle (UAV) imagery to gather sea surface temperature (SST) data. In situ measurements validate the temperature data procured through remote sensing. Leveraging these SST observations alongside hydrodynamic and meteorological data from field measurements, we input them into the MIKE 3 model to prognosticate the three-dimensional (3D) spatial distribution and temperature elevation resulting from thermal discharge. The findings reveal that (1) satellite remote sensing can instantly acquire the horizontal distribution of thermal discharge, but with a spatial resolution much lower than that of UAV. The spatial resolution of UAV is higher, but the imaging efficiency of UAV is only 1/40,000 of that of satellite remote sensing. (2) Numerical simulation models can predict the 3D spatial distribution of thermal discharge. Although UAV and satellite remote sensing cannot directly obtain the 3D spatial distribution of thermal discharge, using remotely sensed SST as the temperature field input for the MIKE 3 model can reduce the quantity of measured temperature data and lower the cost of numerical simulation. (3) In the process of monitoring and predicting the thermal discharge of nuclear power plants, achieving an effective balance between monitoring accuracy and cost can be realized by comprehensively considering the advantages and costs of satellite, UAV, and numerical simulation technologies.

Reverse osmosis (RO) membrane fouling and biological contamination problems faced by seawater desalination systems are microbiologically related. We used full-length 16S rRNA gene sequencing to assess the bacterial community structure and chlorine-resistant bacteria (CRB) associated with biofilm growth in different treatment processes under the winter mode of a chlorinated seawater desalination system in China. At the outset of the winter mode, certain CRB, such as Acinetobacter, Pseudomonas, and Bacillus held sway over the bacterial community structure, playing a pivotal role in biofouling. At the mode\'s end, Deinococcus and Paracoccus predominated, with Pseudomonas and Roseovarius following suit, while certain CRB genera still maintained their dominance. RO and chlorination are pivotal factors in shaping the bacterial community structure and diversity, and increases in total heterotrophic bacterial counts and community diversity in safety filters may adversely affect the effectiveness of subsequent RO systems. Besides, the bacterial diversity and culturable biomass in the water produced by the RO system remain high, and some conditionally pathogenic CRBs pose a certain microbial risk as a source of drinking water. Targeted removal of these CRBs will be an important area of research for advancing control over membrane clogging and ensuring water quality safety in the future.

This paper introduces the novel design and implementation of a low-power wireless monitoring system designed for nuclear power plants, aiming to enhance safety and operational efficiency. By utilizing advanced signal-processing techniques and energy-efficient technologies, the system supports real-time, continuous monitoring without the need for frequent battery replacements. This addresses the high costs and risks associated with traditional wired monitoring methods. The system focuses on acoustic and ultrasonic analysis, capturing sound using microphones and processing these signals through heterodyne frequency conversion for effective signal management, accommodating low-power consumption through down-conversion. Integrated with edge computing, the system processes data locally at the sensor level, optimizing response times to anomalies and reducing network load. Practical implementation shows significant reductions in maintenance overheads and environmental impact, thereby enhancing the reliability and safety of nuclear power plant operations. The study also sets the groundwork for future integration of sophisticated machine learning algorithms to advance predictive maintenance capabilities in nuclear energy management.

The accident at Fukushima Daiichi Nuclear Power Plant (FDNPP) in 2011 resulted in the dispersion of radioactive materials throughout the surrounding area and an increase in the air dose rate was even confirmed in Fukushima City, which is located approximately 60 km northeast of FDNPP. A Tokyo Electric Power Company (TEPCO) Holdings employee, who has lived and worked in Fukushima City since the FDNPP accident, measured individual external doses, GPS data, and his activities in Fukushima Prefecture over a 9 year period beginning in 2014. This data provides valuable information about the area. The data show the following results. (i) Comparison of the air dose rate at the home location to the individual external dose per hour at the home shows that the average conversion factor has increased over the 9 years and exceeded 0.3 since 2019, indicating an overall relatively good correlation. (ii) Individual external doses measured in the office on the fourth floor of a concrete structure in Fukushima City have not changed significantly from 2014 to 2022, when air dose rates showed a decrease. (iii) Outdoor individual external doses, such as those measured when commuting on foot, have a relatively strong correlation with air dose rates from airborne monitoring with the conversion factor of about 0.6. The conversion factor do not differ significantly from 2014 to 2022.In this study, the individual external dose data is applicable to the TEPCO measurer and is not necessarily representative of all residents of Fukushima City. However individual external dose data for 9 consecutive years will be useful for estimating individual external doses from air dose rates, and estimating annual additional exposure doses, if even some of them are applicable to similar life patterns and lifestyles.

The invasion of Ukraine and military operations around Ukrainian nuclear power plants and other nuclear facilities have prompted us to search for radiocaesium in mosses from the Kopački Rit Nature Park in Croatia, since mosses are known bioindicators of airborne radioactive pollution, and Kopački Rit is a known low radiocaesium background area. Sampling was finished in August 2023, and our analysis found no elevated radiocaesium levels. Kopački Rit therefore remains a suitable place for future detection of anthropogenic radioactive pollutants.
Invazija na Ukrajinu i vojne operacije oko ukrajinskih nuklearnih elektrana i drugih nuklearnih postrojenja potaknule su nas da potražimo radiocezij u mahovinama u Parku prirode Kopački rit, jer su mahovine poznati bioindikatori radioaktivnog onečišćenja zraka, a Kopački je rit poznat po niskoj razini onečišćenja radiocezijem. Uzorkovanje je završeno u kolovozu 2023. Naša analiza nije otkrila povišene razine radiocezija. Kopački rit stoga ostaje pogodno mjesto za buduću detekciju antropogenog radioaktivnog onečišćenja.

This paper presents research on the assessment of the radioecological state of plant cover surrounding two research reactor facilities located within the Semipalatinsk Test Site (STS) as examples of nuclear fuel cycle facilities (NFC). Source data on the concentrations of artificial radionuclides in the plant cover were obtained. Quantitative values for 137Cs, 241Am, and 239+240Pu activity concentrations were determined in plants across the perimeters of the facilities, indicating that these compounds may be present in the associated media from the perspective of accumulative bioindication. The values determined for artificial radionuclides in the \'soil‒plant\' system around the researched NFC facilities were attributed to radioactive contamination of the STS territory.

The reactor coolant pump is a key equipment in a nuclear power plant. If the leakage exceeds a certain threshold, it may cause reactor overheating and shutdown. The reactor coolant pump leakage fault usually has two problems: corrosion and scaling. Accurately and efficiently diagnosing the leakage fault mode as early as possible and predicting its remaining useful life (RUL) are important for taking timely maintenance measures. In this paper, an integrated method is proposed. First, the cross-sectional area of the first seal is extracted as a fault indicator. The motivation is that corrosion may enlarge the cross-sectional area, and scaling may reduce the cross-sectional area. Based on the fluid mechanics theory, an integrated model with several uncertain parameters is established among the cross-sectional area, temperature, and leakage at the inlet and outlet of the first seal. In the diagnosing process, a modified change-detection method is proposed to detect the starting point of degradation. Then, the unknown parameters in the previous relation are estimated, and the degrading data before the starting point of degradation are used to diagnose the leakage fault mode. Second, a time-series model of the autoregressive integrated moving average (ARIMA) is established to predict the remaining useful life based on the degrading data after the starting point of degradation. Finally, the leakage degrading data from six reactor coolant pumps of a nuclear power plant is used to perform the leakage fault mode diagnosis and life prediction with degradation point detection error rates not exceeding 4%, fault mode diagnosis correction rates 100% and practical RUL predicting results, which proves that the proposed integrated method is accurate and efficient. The proposed integrated method combines the advantages of both the physical model diagnosis and the data-driven model diagnosis and innovatively make use of the quantity of flow from the output side of the primary pump as the monitoring indicator and the cross-sectional area as the characteristic index together to diagnose the leakage fault mode happened to the seal and predict its RUL, which can meet the needs of actual operation and maintenance to ensure a healthy and stable operation of the pump and prevent unexpected shutdowns of nuclear power plants and serious accidents.

An accident at the Barakah Nuclear Power Plant (BNPP) would result in a significant radionuclide release into the semi-closed marine environment. In this research, the released radionuclide distribution pattern and dose rate in the Persian/Arabian (Gulf) were calculated using a combined hydrodynamic/radiobiological model. Simulations of the dispersion of artificial radionuclide concentrations were conducted using a HYSPLIT model. To assess prospective hazards in case of an incident, environmental risk from ionizing contaminants: assessment and management (ERICA) tools were used. Using the Fukushima nuclear power accident as a model, the scenario source term profile was developed. The volumetric concentrations levels of pollutants ranged between 1 × 104 mBq m-3 to 1 × 1010 mBq m-3 in the radius of 200 km after 48 h. Based on the dose rates of the various marine biotas, Polychaete worms, and Pelagic fish, they had the highest and lowest dose contribution.