Search Results (27)

The fall armyworm (Spodoptera frugiperda) is a highly invasive agricultural pest that has caused significant damage to maize and other crops since its initial detection in China in 2019. Understanding its invasion dynamics, migration patterns, genetic diversity, and overwintering capacity is crucial for developing effective pest management strategies. This study investigates these aspects in Shaanxi Province, a critical transitional zone between northern and southern climates in China, from 2019 to 2023. We conducted field surveys in six cities across Shaanxi to monitor the initial infestation of FAW. Migration trajectories were simulated using the HYSPLIT model, integrating pest occurrence data and meteorological information. Genetic analyses were performed on 113 FAW individuals from 12 geographical populations using mitochondrial COI and nuclear Tpi genes. Additionally, an overwintering experiment was conducted to assess the survival of FAW pupae under local winter conditions. The first detection dates of FAW in Shaanxi showed significant interannual variation, with a trend of delayed infestation each year. Three primary migration routes into Shaanxi were identified, originating from Sichuan, Hubei-Chongqing, and Henan. Genetic analysis revealed a predominance of the rice-strain FAW in Shaanxi, with some corn-strain variants in northern regions. The overwintering experiment indicated that FAW pupae could not survive the winter in Shaanxi, suggesting that the region does not support year-round breeding of this pest. This study provides comprehensive insights into the spatiotemporal dynamics and migration patterns of FAW in Shaanxi. The findings highlight the importance of integrated pest management approaches, including monitoring migration routes and genetic diversity, to develop targeted control measures. The inability of FAW to overwinter in Shaanxi suggests that regional climate conditions play a significant role in limiting its year-round presence, which is valuable information for designing early warning systems and sustainable pest management strategies. Full article

The weather research and forecasting (WRF) model is frequently used to investigate the meteorological field around nuclear installations. The configuration of physical process parameterization schemes in the WRF model has a significant impact on the accuracy of the simulation results. Consequently, carrying out a pre-experiment to quickly obtain the optimal combination of parameterization schemes is essential before conducting meteorological parameter research. To obtain the optimal combination of physical process parameterization schemes from the planetary boundary layer (PBL), land surface (LSF), microphysical (MP), long-wave (LW), and short-wave (SW) radiation processes of the WRF model for simulating the near-surface meteorological variables near a nuclear power plant in Sanshan Town, Fuqing City, Fujian Province, China on 4 June 2019 were observed. Orthogonal experimental design (OED), a comprehensive evaluation method based on the CRiteria Import Through Intercriteria Correlation (CRITIC) weight analysis, and comprehensive balance method were employed for the first time to conduct the research. The sensitivity of meteorological variables to physical processes was first discussed. The findings revealed that the PBL scheme configuration had a profound impact on simulating wind fields. Furthermore, the LSF scheme configuration had a significant influence on simulating near-surface temperature and relative humidity, which was much greater than that of other physical processes. In addition, the choice of the radiation scheme had a significant impact on how the temperature was distributed close to the ground and how the wind field was simulated. Furthermore, the configuration of the MP scheme was found to exert a certain influence on the simulation of relative humidity; however, it demonstrated a weak influence on other meteorological variables. Secondly, The MYNN3 scheme for PBL process, the NoahMP scheme for LSF process, the WSM5 scheme for MP process, the RRTMG scheme for LW process, and the Dudhia scheme for SW process are found to be the comprehensive optimal physical process parameterization scheme combination for simulating meteorological variables in the research area selected in this study. As evident from the findings, the use of the OED method to obtain the combinations of the optimal physical process parameterization scheme could successfully reproduce the wind field, temperature, and relative humidity in the current study. Thus, this method appears to be highly reliable and effective for use in the WRF models to explore the optimal combinations of the physical process parameterization scheme, which could provide theoretical support to quickly analyzing accurate meteorological field data for longer periods and contribute to deeply investigating the migration and diffusion behavior of airborne pollutants in the atmosphere. Full article

Many regulatory requirements add significant delay in the licensing of new nuclear power stations. One area of particular interest is the environmental impact of potential atmospheric release. The purpose of this research is to demonstrate effectiveness of meteorological data mining and synthesis from offsite locations to reduce need for onsite data, hence allowing rapid licensing. The automated procedures tested for data mining and extraction of meteorological data from multiple offsite sources and the data analytic tool developed for data fusion are presented here. Three important meteorological parameters from regulatory compliance are considered for this analysis: wind velocity, wind direction, and atmospheric stability. Callaway Nuclear Power Plant (CNPP) is used as our reference site. CNPP uses the ${\displaystyle \frac{\mathsf{\Delta }T}{\mathsf{\Delta }z}}$ approach while we use the Vogt method to estimated stability for the offsite locations. Stability classification correlation coefficients between the reference plant and Columbia Regional Airport range from −0.087 to 0.826 for raw with an average of 0.317 ± 0.313. With travel time, correction changed slightly, i.e., a 10 m observation 0.064 ± 0.249 and 0.028 ± 0.123 and a 60 m observation 0.103 ± 0.265 and 0.063 ± 0.155 for the wind from the reference plant to the airport and vice versa, respectively. For Jefferson City Memorial Airport, raw data correlation was from −0.083 to 0.771, with an average of 0.358 ± 0.321. With travel time, correction changed slightly, i.e., 10 m observation 0.075 ± 0.208 and −0.073 ± 0.255 and 60 m observation 0.018 ± 0.223 and −0.032 ± 0.248 for wind from the reference plant to the airport and vice versa, respectively. Stability classification correlation coefficients between the reference plant and St. Louis Lambert International Airport ranged from −0.083 to 0.763 for raw with an average of 0.314 ± 0.295. With travel time, correction changed slightly, i.e., 10 m observation −0.003 ± 0.307 and −0.030 ± 0.277 and 60 m observation −0.030 ± 0.193 and −0.005 ± 0.215 for wind from the reference plant to the airport and vice versa, respectively. It is important to observe that mathematically. stability class correlation coefficients were not great, but in most cases the predicted and observed values were only off by one stability class. Similar correlations were calculated for wind direction and velocities. Our result, when applied to a proposed nuclear power station, can significantly reduce time and effort to prepare a robust environmental protection plan required for license application. Full article

Based on the Weather Research and Forecasting Model Coupled with Chemistry (WRF-Chem) atmospheric chemistry model, a parameterization scheme for the radioactive isotope caesium (¹³⁷Cs), considering processes such as advection, turbulent diffusion, dry deposition, and wet deposition, was constructed, enabling the spatial distribution simulation of the concentration and deposition of ¹³⁷Cs. The experimental simulation studies were carried out during the high emission period of the Fukushima nuclear accident (from 11 to 17 March 2011). Two sets of comparison experiments, with or without deposition, were designed, the effects of wind field and precipitation on the spatial transport and ground deposition of ¹³⁷Cs were analyzed, and the influence of wind field and precipitation on ¹³⁷Cs vertical transport was analyzed in detail. The results indicate that the model can accurately simulate the meteorological and ¹³⁷Cs variables. On 15 March, ¹³⁷Cs dispersed towards the Kanto Plain in Japan under the influence of northeastern winds. In comparison to the experiment without deposition, the concentration of ¹³⁷Cs in the Fukushima area decreased by approximately 286 Bq·m⁻³ in the deposition experiment. Under the influence of updrafts in the non-deposition experiment, a ¹³⁷Cs cloud spread upward to a maximum height of 6 km, whereas in the deposition experiment, the highest dispersion of the ¹³⁷Cs cloud only reach a height of 4 km. Affected by the wind field, dry deposition is mainly distributed in Fukushima, the Kanto Plain, and their eastern ocean areas, with a maximum dry deposition of 5004.5 kBq·m⁻². Wet deposition is mainly influenced by the wind field and precipitation, distributed in the surrounding areas of Fukushima, with a maximum wet deposition of 725.3 kBq·m⁻². The single-station test results from the deposition experiment were better than those for the non-deposition experiment: the percentage deviations of the Tokyo, Chiba, Maebashi, and Naraha stations decreased by 61%, 69%, 46%, and 51%, respectively, and the percentage root mean square error decreased by 46%, 25%, 38%, and 48%, respectively. Full article

Safety in nuclear energy utilization is crucial. In the event of a radioactive release incident, coupled with meteorological uncertainties, a radioactive plume can impact personnel evacuation. This paper presents an integrated solution for radionuclide release accident assessment and emergency evacuation decision making. The solution consists of three processes: atmospheric dispersion calculation, dose calculation, and path planning. The individual processes are connected through data exchange, thus allowing users to choose specific models based on experience. The proposed scheme combination is the Gaussian plume model, the dose conversion factor method, and an improved Dijkstra’s path planning algorithm. This algorithm, combined with dispersion and dose results, weighs nodes using the moving expected dose, facilitating the path with minimum dose risk. A program for Atmospheric Diffusion and Dose Calculation (ADDC) is developed based on the recommended scheme. Advantages include ease of use, minimal data requirements, data accessibility, and efficient evacuation. Dose estimates and optimal evacuation routes can be obtained quickly and at very low cost in response to rapidly changing environmental conditions. In a case study at a Chinese planned nuclear plant, we consider a spent fuel pool water loss scenario, assessing dose risks from 2020 to 2022 meteorological statistics. In dose calculation, results reveal that during an SFP drying accident, the radiation dose in the core area (100 m away) can reach 30–150 mSv within 2 h, and at 500 m away, it can reach 5–15 mSv. The dose in all downwind directions can drop below 250 mSv within 60 m. In path planning, results reveal the program is capable of accurately and efficiently calculating the minimum dose evacuation route. The program’s path reduces the effective dose by up to 67.3% compared to the shortest route, enhancino safety, and guiding post-accident decision making and planning. Full article

Atmospheric radon measurements assist in many aspects of climate and meteorological research, notably as an airmass tracer and for modelling boundary layer development, mixing heights and stability. Daughter products from radon decay are sometimes incorporated into the particle pollution measurements of commercially available beta-attenuation monitors (BAM). BAMs incorporating radon measurements are used in air quality monitoring networks and can supplement traditional radon measurements. Here we compare in-situ radon measurements from Thermo Fisher Scientific (Franklin, MA, USA) BAM instruments (Thermo Scientific 5014i, Thermo Scientific 5030 SHARP, Thermo Anderson FH62C14) at two air quality monitoring stations in New South Wales, Australia. Between systems we find strong correlations for hourly measurements (r = 0.97–0.99); daily means (r = 0.97–0.99); hour of the day (r = 0.84–0.98); and month (r = 0.82–0.98). The regression analysis for radon measurements between systems showed strong linear responses, although there are some variations in the slopes of the regressions. This implies that with correction BAM measurements can be comparable to standard measurement techniques, for example, from the Australian Nuclear Science and Technology Organisation (ANSTO) dual flow loop monitors. Our findings imply that BAM derived radon measurements are precise, although their accuracy varies. BAM radon measurements can support studies on boundary layer development or where radon is used as an atmospheric transport tracer. Full article

The safe evacuation of residents near a nuclear power plant during a nuclear accident is vital for emergency response planning. To tackle this challenge, considering the dynamic dispersion of radioactive materials in the atmosphere and its impact on evacuation routes under different meteorological conditions is crucial. This paper develops a dynamic dose-based emergency evacuation model (DDEEM), which is an efficient and optimized nuclear accident evacuation model based on dynamic radiological dose calculation, utilizing an improved A* algorithm to determine optimal evacuation routes. The DDEEM takes into account the influence of radiological plume dispersion and path selection on evacuation effectiveness. This study employs the DDEEM to assess radiological consequences and evacuation strategies for students residing 5 $\mathrm{k}\mathrm{m}$ from a Chinese nuclear power plant. Under various meteorological conditions, including the three typical meteorological conditions, random ordered and random unordered meteorological sequences, optimal routes obtained through the DDEEM effectively reduce radiological dose exposure and mitigate radiation hazards. The results indicate that all evacuation paths generated by the DDEEM have a maximum dose of less than $1 \mathrm{m}\mathrm{S}\mathrm{v}$. Through simulations, the model’s effectiveness and reliability in dynamic radiological environments in terms of radiological consequences and evacuation analysis is verified. The research provides valuable insights and a practical tool for nuclear power plant emergency decision-making, enhancing emergency management capabilities during nuclear accidents. The DDEEM offers crucial technical support and a solid foundation for developing effective emergency response strategies. Full article

Many well-established models exist for predicting the dispersion of radioactive particles that will be generated in the surrounding environment after a nuclear weapon explosion. However, without exception, almost all models rely on accurate source term parameters, such as DELFIC, DNAF-1, and so on. Unlike nuclear experiments, accurate source term parameters are often not available once a nuclear weapon is used in a real nuclear strike. To address the problems of unclear source term parameters and meteorological conditions during nuclear weapon explosions and the complexity of the identification process, this article proposes a nuclear weapon source term parameter identification method based on a genetic algorithm (GA) and a particle swarm optimization algorithm (PSO) by combining real-time monitoring data. The results show that both the PSO and the GA are able to identify the source term parameters satisfactorily after optimization, and the prediction accuracy of their main source term parameters is above 98%. When the maximum number of iterations and population size of the PSO and GA were the same, the running time and optimization accuracy of the PSO were better than those of the GA. This study enriches the theory and method of radioactive particle dispersion prediction after a nuclear weapon explosion and is of great significance to the study of environmental radioactive particles. Full article

Energy policies of the European Union, the United States, China, and many other countries are focused on the growth in the number of and output from renewable energy sources (RES). That is because RES has become increasingly more competitive when compared to conventional sources, such as coal, nuclear energy, oil, or gas. In addition, there is still a lot of untapped wind energy potential in Europe and worldwide. That is bound to result in continuous growth in the share of sources that demonstrate significant production variability in the overall energy mix, as they depend on the weather. To ensure efficient energy management, both its production and grid flow, it is necessary to employ forecasting models for renewable energy source-based power plants. That will allow us to estimate the production volume well in advance and take the necessary remedial actions. The article discusses in detail the development of forecasting models for RES, dedicated, among others, to wind power plants. Describes also the forecasting accuracy improvement process through the selection of the network structure and input data set, as well as presents the impact of weather factors and how much they affect the energy generated by the wind power plant. As a result of the research, the best structures of neural networks and data for individual objects were selected. Their diversity is due to the differences between the power plants in terms of location, installed capacity, energy conversion technology, land orography, the distance between turbines, and the available data set. The method proposed in the article, using data from several points and from different meteorological forecast providers, allowed us to reduce the forecast error of the NMAPE generation to 3.3%. Full article

Long-term consequences of radionuclide contamination of the Arabian Gulf as a result of hypothetical accidents at the Bushehr and Barakah nuclear power plants (NPPs) were studied using a chain of models including the atmospheric dispersion model RIMPUFF, the marine compartment model POSEIDON-R, and the dose model. The compartment model POSEIDON-R is complemented by a dynamic model of the biota food chain that includes both pelagic and benthic organisms. The source terms for the hypothetical releases of the selected radionuclides (¹³⁴Cs, ¹³⁷Cs, ¹⁰⁶Ru, and ⁹⁰Sr) in the atmosphere were defined as a fraction of respective reactor inventories available in the literature. Conservative meteorological scenarios for the calculation of the initial depositions of radionuclides were selected. Because the Gulf is shallow, a significant portion of the reactive radionuclides (¹³⁴Cs, ¹³⁷Cs, ¹⁰⁶Ru) remain in the bottom sediments and continue to contaminate water and benthic organisms for a long period of time. The annual dose due to the consumption of marine products can exceed 1 mSv, whereas the annual dose due to drinking the water from desalination plants is expected to be an order less. The contribution of elements to the dose depends on the type of reactor. This is manifested in differences between the contributions of different marine organisms to the dose. Full article

Studying the migration and diffusion of radionuclides plays an important role in emergency decision making and accident mitigation of floating nuclear power plants. Based on the CALPUFF model, this paper simulates the spatial distribution and concentration distribution of airborne radionuclides ¹³¹I diffusion under the conditions of sailing and power supply under LOCA (Loss-of-Coolant Accident) of the floating nuclear power plant, and the influence of four meteorological parameters, namely wind speed, cloudiness, temperature and air pressure, on the migration was analyzed using sensitivity analysis. The results show that the wind direction affects the diffusion direction of ¹³¹I, and the concentration of ¹³¹I decreases with the increase in the diffusion distance; under the same conditions, the radionuclides diffuses farther and the affected area is larger under the sailing condition. Wind speed is the dominant factor affecting the diffusion of radionuclides, followed by the cloud amount parameter, temperature parameter, and air pressure parameter. The research results can provide theoretical support for emergency responses to nuclear accidents in offshore floating nuclear power plants. Full article

New Nuclear Power Plant (NPP), which is under construction in El Dabaa, Egypt, is expected to start working within few years. Such project should be associated with several scientific research works. The suitability of the NPP location as well as the assessment of the impact of its routine work and accidental failure is among the points that should be addressed. In this work, the contamination risks due to uniform accidental leakage of the radioactive aerosol $C_{}^{137}s$ that continues for eight hours is studied. FLEXPART version 10.4 at high resolution (55 km) is applied using six-hour NCEP FNL (1° × 1°) gridded data to simulate the dispersion and deposition of $C_{}^{137}s$ for the subsequent five days. This process is repeated each day for the period of 2008 to 2018. It is shown that high concentration and total deposition are observed particularly during the summer season. In addition, the consideration of different emission scenarios indicates that Egypt is expected to be strongly affected. Moreover, dispersion and concentration of the radioactive materials is notably influenced by near-surface winds. In conclusion, FLEXPART is considered as a promising tool to explore the possible nuclear hazards under a variety of meteorological conditions. Further, a future study will consider the influence of the horizontal grid spacing and lateral boundary condition using the coupled Weather Research and Forecasting (WRF)-FLEXPART system. Full article

This study presents a model for the dispersion of radioactive smoke clouds from a nuclear weapon explosion. A model based on a modified Settlement model is chosen to simulate the dispersion of radioactive contaminants from a nuclear explosion in the atmosphere. The arrival time and dose rate of radioactive fallout at various distances in the downwind direction are given for different equivalents of the surface explosion and typical meteorological conditions. Thus, the prediction of the dispersion of radioactive contaminants from a nuclear explosion can be achieved under the conditions of known nuclear explosion equivalence and local meteorological parameters. This provides a theoretical basis for the estimation of the affected environment and the input of rescue forces after the explosion. Full article

Mediterranean hurricanes, or medicanes, are tropical-like cyclones forming once or twice per year over the waters of the Mediterranean Sea. These mesocyclones pose a serious threat to coastal infrastructure and lives because of their strong winds and intense rainfall. Infrasound technology has already been employed to investigate the acoustic signatures of severe weather events, and this study aims at characterizing, for the first time, the infrasound detections that can be related to medicanes. This work also contributes to infrasound source discrimination efforts in the context of the Comprehensive Nuclear-Test-Ban Treaty. We use data from the infrasound station IS48 of the International Monitoring System in Tunisia to investigate the infrasound signatures of mesocyclones using a multi-channel correlation algorithm. We discuss the detections using meteorological fields to assess the presence of stratospheric waveguides favoring propagation. We corroborate the detections by considering other datasets, such as satellite observations, a surface lightning detection network, and products mapping the simulated intensity of the swell. High- and low-frequency detections are evidenced for three medicanes at distances ranging between 250 and 1100 km from the station. Several cases of non-detection are also discussed. While deep convective systems, and mostly lightning within them, seem to be the main source of detections above 1 Hz, hotspots of swell (microbarom) related to the medicanes are evidenced between 0.1 and 0.5 Hz. In the latter case, simulations of microbarom detections are consistent with the observations. Multi-source situations are highlighted, stressing the need for more resilient detection-estimation algorithms. Cloud-to-ground lightning seems not to explain all high-frequency detections, suggesting that additional sources of electrical or dynamical origin may be at play that are related to deep convective systems. Full article

Accurate simulation of boundary layer surface meteorological parameters is essential to achieve good forecasting of weather and atmospheric dispersion. This paper is devoted to a model sensitivity study over a coastal hyper-arid region in the western desert of the United Arab Emirates. This region hosts the Barakah Nuclear Power Plant (BNPP), making it vital to correctly simulate local weather conditions for emergency response in case of an accidental release. We conducted a series of high-resolution WRF model simulations using different combinations of physical schemes for the months January 2019 and June 2019. The simulated results were verified against in-situ meteorological surface measurements available offshore, nearshore, and inland at 12 stations. Several statistical metrics were calculated to rank the performance of the different simulations and a near-to-optimal set of physics options that enhance the performance of a WRF model over different locations in this region has been selected. Additionally, we found that the WRF model performed better in inland locations compared to offshore or nearshore locations, suggesting the important role of dynamical SSTs in mesoscale models. Moreover, morning periods were better simulated than evening ones. The impact of nudging towards station observations resulted in an overall reduction in model errors by 5–15%, which was more marked at offshore and nearshore locations. The sensitivity to grid cell resolution indicated that a spatial resolution of 1 km led to better performance compared to coarser spatial resolutions, highlighting the advantage of high-resolution simulations in which the mesoscale coastal circulation is better resolved. Full article