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Thermal power plants serve as significant CO2 sources, and accurate monitoring of their emissions is crucial for improving the precision of global carbon emission estimates. In this study, a measurement method based on measuring point source plumes was employed in ground-based remote sensing experiments at the thermal power plant. By simulating CO2 plumes, we analyzed the impact of surrounding urban structures, the geometric relationship between measurement points and plumes, and the influence on measurement points selection. We also assessed the capability and uncertainties in quantifying CO2 emissions. For the Hefei power plant, CO2 emission estimates were on average 7.98 ± 10.01 kg/s higher with surface buildings compared to scenarios without buildings (approximately 4.09% error). By selectively filtering discrete data, the emission estimation errors were significantly reduced by 7.31 ± 7.13 kg/s compared to pre-filtered data. Regarding the relationship between observation paths and plume geometry, simulation studies indicated that the ability to estimate CO2 emissions varied for near and middle segment observations. The lowest emission rate error was found in the mid-segment near 1.5-2.0 km, reaching 7.13 ± 5.39 kg/s. CO2 distribution at the mid-segment position becomes more uniform relative to the near segment, making it more suitable for meeting emission estimation requirements. Optimizing measurement schemes by considering environmental factors and precisely selecting measurement points significantly enhances emission estimation accuracy, providing crucial technical support for top-down estimates of anthropogenic CO2 emissions.

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In this research, aligned with global policies aimed at reducing CO2 emissions from traditional power plants, we developed a holistic energy system utilizing solar, wind, and ocean thermal energy sources, tailored to regions optimal for ocean thermal energy conversion (OTEC). The selected site, characterized by favorable wind and solar conditions close to areas with high OTEC potential, is designed to meet the electricity needs of a coastal community. The system's core components include an Organic Rankine Cycle, turbines, thermoelectric elements, pumps, a heat exchanger, a wind turbine, and a solar collector. A detailed system analysis and thermodynamic evaluation based on thermodynamic principles were carried out using the Engineering Equation Solver (EES) software. Key factors such as wind speed, solar radiation, and collector area were critical in determining system performance. To enhance the system's effectiveness, we conducted a comprehensive comparison of optimization algorithms, incorporating the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and utilizing a Pareto front for value optimization. This approach significantly outperformed other algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Simulated Annealing (SA) in terms of system efficiency and cost-effectiveness. The developed system achieved an exergy efficiency of 14.46 % and a cost rate of $74.98 per hour, demonstrating its suitability for its intended functions. Moreover, exergoenvironmental evaluation was conducted for the proposed plant. The findings revealed that key component HEX has a high exergoenvironmental factor due to their use of hot water, which has zero unit exergoenvironmental impact. Additionally, pumps demonstrated a zero exergoenvironmental impact factor, indicating negligible component-related environmental impacts. Sensitivity analysis further evaluated critical performance parameters, revealing that increases in solar irradiation lead to decreased total system cost rates, while higher turbine temperatures resulted in a remarkable 14.08 % reduction in the system's cost rate. These results underscore the economic viability of operating the system at higher temperatures and strengthen the argument for its adoption from a financial perspective.

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After the 2011 Fukushima nuclear power plant accident, the prevalence of metabolic syndrome sharply increased in municipalities near the nuclear power plant, where a massive evacuation of community residents occurred (the evacuation area). However, after the initial increase, the rate of increase in metabolic syndrome in the evacuation area was slower than that in the surrounding area (non-evacuation area). In this study, we compared the incidence of and recovery from metabolic syndrome as well as its prevalence between evacuation and non-evacuation areas during the 10 years after the accident to explore whether the slower increase in metabolic syndrome after the initial increase in the evacuation area stemmed from suppressed incidence or from fast recovery. We analyzed specific health check-up data of community residents aged 40-74 in Fukushima Prefecture from fiscal year (FY) 2012 to FY 2021 (N = 710,201). To explore the prevalence of metabolic syndrome, we examined the associations of time, residential area, and their interaction with metabolic syndrome using mixed-model repeated measures. We used data from those without metabolic syndrome in FY 2012 to investigate the incidence. We similarly examined the associations of time, residential area, and their interaction with metabolic syndrome using FY 2013 to FY 2021 data. To explore recovery, we used the data of those with metabolic syndrome in FY 2012 and repeated the same procedure. The rate of increase in the prevalence and incidence of metabolic syndrome was slower in the evacuation area than in the non-evacuation area. On the other hand, as for the recovery, the time trend of metabolic syndrome did not differ between the two areas. The slower increase in metabolic syndrome in the evacuation area was partly explained by the slower incidence in the evacuation area but not by recovery.

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This paper discusses the simultaneous management of active and reactive power of a flexible renewable energy-based virtual power plant placed in a smart distribution system, based on the economic, operational, and voltage security objectives of the distribution system operator. The formulated problem aims to specify the minimum weighted sum of energy cost, energy loss, and voltage security index, considering the optimal power flow model, voltage security formulation, and the operating model of the virtual power plant. The virtual unit includes renewable sources, like wind systems, photovoltaic, and bio-waste units. Flexibility resources include electric vehicle parking lot and price-based demand response. In the mentioned scheme, parameters of load, renewable sources, electric vehicles, and energy prices are uncertain. This paper utilizes the Unscented Transformation method for modeling uncertainties. Fuzzy decision-making is utilized to extract a compromised solution. The suggested approach innovatively considers the simultaneous management of active and reactive power of a virtual unit with electric vehicles and price-based demand response. This is performed to promote economic, operational, and network security objectives. According to numerical results, the approach with optimal power management of renewable virtual units is capable of boosting the economic, operation, and voltage security status of the network by approximately 43%, 47-62%, and 26.9%, respectively, to power flow studies. Only price-based demand response can improve the voltage security, operation, and economic states of the network by about 19.5%, 35-47%, and 44%, respectively, compared to the power flow model.

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The Fukushima Daiichi Nuclear Power Plant accident released considerable radionuclides into the environment. Radioactive particles, composed mainly of SiO2, emerged as distinctive features, revealing insights into the accident's dynamics. While studies extensively focused on high-volatile radionuclides like Cs, investigations into low-volatile nuclides such as 90Sr and Pu remain limited. Understanding their abundance in radioactive particles is crucial for deciphering the accident's details, including reactor temperatures and injection processes. Here, we aimed to determine 90Sr and Pu amounts in radioactive particles and provide essential data for understanding the formation processes and conditions within the reactor during the accident. We employed radiochemical analysis on nine radioactive particles and determined the amounts of 90Sr and Pu in these particles. 90Sr and Pu quantification in radioactive particles showed that the 90Sr/137Cs radioactivity ratio (corrected to March 11, 2011) aligned with core temperature expectations. However, the 239+240Pu/137Cs activity ratio indicated nonvolatile Pu introduction, possibly through fuel fragments. Analyzing 90Sr and Pu enhances our understanding of the Fukushima Daiichi accident. Deviations in 239+240Pu/137Cs activity ratios underscore nonvolatile processes, emphasizing the accident's complexity. Future research should expand this data set for a more comprehensive understanding of the accident's nuances.

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Waste-to-energy (WtE) power plants, supplied mainly with municipal solid waste (MSW) and refuse-derived fuel (RDF), which convert waste into electricity, have emerged as a solution to Thailand's waste management problems. This study focused on identifying and studying the critical success factors (CSFs) that influence the success of MSW and RDF power plants in Thailand. This study employed interpretive structural Modelling and cross-impact matrix multiplication applied to a classification analysis to evaluate the impact of these CSFs on the development of WtE projects. The results showed that, for MSW, most CSFs were related to energy and waste management policies, followed by waste quality for electricity generation. In addition, strong financial resources and appropriate power plant locations are important for MSW management success. Conversely, for RDF, most CSFs were sufficient waste quality for electricity generation and performed well according to licensing conditions. In this study, high-level CSFs indicated that these factors were crucial for MSW and RDF development. CSFs differ based on specific technologies and regulations. However, sufficient waste quality (heating value and moisture content) is a common CSF in the MSW and RDF technologies. This study provides valuable insights into the CSFs that affect the development of WtE. Understanding and addressing these CSFs is essential for the development and operation of WtE power plants in Thailand and other countries with similar conditions. Thus, policy-makers and other stakeholders can make informed decisions to ensure the success of WtE projects.

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The study aims to analyze and decompose the qualitative parameters of wood chips in Poland. The European Green Deal brings the new framework to support sustainability and elimination of emissions. The Wavelet coherence and Wavelet Discrete Decomposition are used for determination of relations among significant qualitative parameters. Thus, the possible uses are discussed. For the obvious relationship between moisture and calorific value there is evidence of strong correlation. The behaviour of these interrelations are different at frequencies in the long and short time. The wood chip price is inter-transmitter from moisture parameter to calorific value in a positive (in-phase) relationship. At both low and high frequencies there is evidence that the variables of moisture and calorific value are highly correlated. The transient effect of linkage is presented at values between 0.1 and 0.3 in coherence map. The empirical findings provide implication for local producers and policymakers.

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BACKGROUND: Cancer is a leading cause of death worldwide, posing a significant threat to human health and life expectancy. Numerous existing studies explored the correlation between coal-fired power plants and cancer development. Currently, Chungcheongnam-do Province hosts 29 coal-fired power plants, constituting half of the total 58 plants across South Korea. METHODS: This study assessed the cancer incidence by proximity to coal-fired power plants in Chungcheongnam-do Province, Korea. In this study, the exposed group comprised individuals residing within a 2-km radius of the coal-fired power plants, whereas the control group comprised individuals who had no prior residency within the 2-km radius of such plants or elsewhere in the province. Standardized incidence ratios were calculated using the cancer incidence cases retrieved from the National Health Insurance System data from 2007 to 2017. RESULTS: The study found that exposed men had a 1.11 (95% confidence interval [CI], 1.09-1.21) times higher risk of developing all cancer types and a 1.15 (95% CI, 1.09-1.22) times higher risk of developing cancers excluding thyroid cancer compared with control men. Exposed women had a 1.05 (95% CI, 1.00-1.14) times higher risk of developing all cancer types and a 1.06 (95% CI, 0.98-1.13) times higher risk of developing cancers excluding thyroid cancer than did control women. The colorectal, liver, prostate, and bladder cancer incidence rates were significantly higher in exposed men than that in all control groups. The incidence of esophageal, stomach, liver, and lung cancers were significantly higher in exposed women compared with all control groups. CONCLUSION: The residents near coal-fired power plants had a higher risk of developing cancer than did those living in other areas. In the future, long-term follow-up investigations in residents living in the vicinity of power plants are warranted.

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In contemporary scenario, electric power companies have observed upsurge in penetration level of tidal power plants (TPPs) in the traditional electric power system framework. However, the tidal turbines offer less frequency assistance due to their lesser rotor mass. Hence, TPPs may be collaborated with conventional units like diesel engine generator (DEG) to confirm system frequency stability in multi-area micro-grid system. The DEG comprises of primary and proportional integral derivative (PID) secondary frequency controls. However, in TPPs, to advance the system frequency regulation, deloading control approach is suggested and a cascade fuzzy fractional order PID-ID with derivative filter (CFFOPID-IDF) droop controller is suggested in place of the conventional non-cascade controller droop in the deloaded region. The suggested controller gains are fetched exploiting Salps swarm algorithm. For further enhancement of the dynamic responses, a precise high voltage direct current (AHVDC) link with the inertia emulation-based control (INEC) scheme is adopted, which allows the utilization of the gathered energy from the capacitance of the HVDC interface for frequency regulation. It provides better results compared to conventional AC tie line interface having less undershoot (34 %/20.63 %/43.75 %) and settling time (20.45 %/59.09 %/16.83 %) for variation in area-1 frequency/area-2 frequency/tie line power, respectively. The recommended control scheme is evidenced superior over numerous existing control techniques and provides least cost function in contrast to other control techniques. Additionally, it offers a highly stable performance under variable load conditions.

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The utilization of coal in Power Plants (PLTUs) can lead to the generation of fly ash waste, which may contain natural radionuclides that can potentially contaminate the surrounding environment. Despite Labuan PLTU's land-coastal location, marine environment monitoring remains minimal. A recent study conducted sediment and seawater sampling, revealing varying levels of natural radionuclides 226Ra, 232Th, and 40K ranging from 3.4 to 27.5 Bq kg-1, 3.9 to 34.9 Bq kg-1, and 64.0 to 275.0 Bq kg-1 in sediments, respectively. Meanwhile, the activity concentration of natural radionuclides 226Ra and 232Th in seawater ranges from 0.5 to 1.1 Bq L-1 to 0.7-1.5 Bq L-1, respectively. These findings provide baseline data for marine radiation levels around PLTU Labuan. Additionally, risk assessments were conducted, indicating Raeq, Hin, and Hex ranges of 13.80-91.00 Bq kg-1, 0.04-0.25, and 0.05-0.31, respectively. The study concludes that Labuan's radiation levels are within safe limits for exposure.

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INTRODUCTION: Power plants are associated with numerous occupational health and safety risk factors, with psychosocial risks being particularly significant. This study examines work-life conflict and burnout among power plant employees and discusses the factors associated with these issues. MATERIALS AND METHODS: This cross-sectional study focused on employees at three hydroelectric power plants in Turkey. The inclusion criteria included employees with at least one year of tenure. Using cluster sampling, three plants were selected in Adana, Ankara, and Samsun. The sample size was determined to be 262, and 201 employees participated, yielding a 76.7% response rate. Data were collected via face-to-face interviews using a structured questionnaire, which encompasses the sub-dimensions of a valid and reliable scale: The Work-Life Conflict and Burnout sub-dimensions of the Copenhagen Psychosocial Questionnaire-III (COPSOQ-III) were used to measure the dependent variables. The independent variables included age, education level, total and weekly working hours, perceived health status, and department. The dependent variables were work-life conflict and burnout. Ethical approval was obtained from the Gazi University Ethics Committee. Statistical analysis compared the Pearson chi-square test, Fisher's exact test, and Yates correction with a significance threshold of p < 0.05. RESULTS: The mean age was 40.83 years, with an average tenure of 11.54 years and a weekly work time of 43.51 hours. Most participants (94.5%) were male; technical unit workers comprised 71.6%. Health issues included smoking (39.8%) and chronic diseases (19.9%). Concerns about the working environment include insufficient knowledge about safety (25.4%) and lack of knowledge about risk assessments (32.3%). Many workers reported lacking personal protective equipment (11.4%) and rest areas (15.4%). Negative health impacts from work were noted by 31.8%. In addition, 51.2% believed that noise levels were outside the acceptable range. Two-thirds of employees reported inadequate measures against physical risks in the workplace. Many participants experienced work-life conflict (13.9%) and burnout (14.5%). High work-life conflict was significantly associated with younger age groups, less tenure, and negative perceived health status. Burnout was significantly related to the duration of employment, weekly working hours, and perceived health status. CONCLUSION: The study highlights the seriousness of burnout and work-life conflict among hydropower plant workers, emphasizing the need for administrative and organizational interventions to alleviate these issues. Regular occupational health and safety training, involvement in risk assessments, fair workload distribution, supportive work environments, and counseling services are recommended to reduce burnout and improve work-life balance.

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Since the 2011 Fukushima nuclear power plant accident, multiple social network disruptions have been reported among the community in Fukushima, while posttraumatic stress symptoms among the residents have persisted. In this study, we aimed to explore the influence of time and social networks on the recovery of posttraumatic stress symptoms based on longitudinal data from community residents in Fukushima, following up five to ten years after the nuclear power plant accident. We conducted five questionnaire surveys quasi-annually, the targets of which were randomly sampled 4900 non-evacuee community residents. In this study, the data of 1809 respondents who participated in at least one survey were used (36.9% of the initial target). Setting posttraumatic stress symptoms as the outcome, we examined the interaction between time and social network size using a mixed model, adjusting for sociodemographic characteristics and disaster-related events. Their interaction was statistically significant, and the posttraumatic stress symptoms of those with small social networks persisted, while those with larger social networks recovered. Maintaining and promoting social networks may contribute to mental health recovery after a nuclear disaster.

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Combustion optimization is an effective way to improve the efficiency of thermal power generation and reduce carbon and NOx emissions. Real-time and precise NOx emission prediction is the basis for combustion optimization control of thermal power plants. To construct an accurate NOx concentration prediction model, a novel just-in-time learning (JITL) method based on random forest (RF) is proposed in the present work. With this method, first, an improved permutation importance algorithm is proposed to extract important variables. In addition, a similarity index that incorporates temporal and spatial measures is defined to select a local training set representative of the process data. Moreover, considering the influence of model parameters on prediction performance under different working conditions, a process monitoring method based on a moving window (MW) is used to monitor the change in working conditions and guide online updating. The experimental results show that the proposed method has excellent prediction accuracy, with a coefficient of determination of 0.9319, a root-mean-square error of 3.6960 mg/m3, and an average absolute error of 2.7718 mg/m3 on the test set, making it superior to other traditional methods.

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In the context of hydroelectric plants, this article emphasizes the imperative of robust monitoring strategies. The utilization of fiber-optic sensors (FOSs) emerges as a promising approach due to their efficient optical transmission, minimal signal attenuation, and resistance to electromagnetic interference. These optical sensors have demonstrated success in diverse structures, including bridges and nuclear plants, especially in challenging environments. This article culminates with the depiction of the development of an array of sensors featuring Fiber Bragg Gratings (FBGs). This array is designed to measure deformation and temperature in protective grids surrounding the turbines at the Santo Antônio Hydroelectric Plant. Implemented in a real-world scenario, the device identifies deformation peaks, indicative of water flow obstructions, thereby contributing significantly to the safety and operational efficiency of the plant.

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The paper aims to investigate the fuel and system options for a floating power plant (FPP) considering economic performance and the decarbonization goals of the International Maritime Organization. Various case studies have been assessed using a reference FPP, encompassing the instant and future retrofitting scenarios. The ready-to-use scenarios involve alternative fuel and organic Rankine cycle-based waste heat recovery system usage. Nuclear energy systems have been evaluated within the reference FPP since they are suitable candidates for achieving zero-carbon objectives and providing low-cost electricity. A simulation framework created in Python has calculated the fuel consumption regarding the power requirement and organized the approaches used in the study. An environmental model comparing the systems has been built to calculate upstream and operational emissions. The cost projection model for 2030 and 2050 has assessed the economic performance. Technique for Order of Preference by Similarity (TOPSIS) one of the multi-criteria decision-making approaches has ranked the systems considering the outcomes of economic and environmental models over the years. Findings demonstrate that the current fuel usage scenario of the FPP is not suitable both environmentally and economically. The other emissions can be near zero and greenhouse gases can be decreased by up to 15.95% using alternative fuels. Nuclear energy is a strong candidate to meet the 2050 targets, but its viability is largely based on economic performance.

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In this study, a digital twin model of a hydroelectric power plant has been created. Models of the entire power plant have been created and malfunction situations of a sensor located after the inlet valve of the plant have been analyzed using a programmable logic controller (PLC). As a feature of the digital twin (DT), the error prediction and prevention function has been studied specifically for the pressure sensor. The accuracy and reliability of the data obtained from the sensor are compared with the data obtained from the DT model. The comparison results are evaluated and erroneous data are identified. In this way, it is determined whether the malfunction occurring in the system is a real malfunction or a malfunction caused by measurement or connection errors. In the case of sensor failure or measurement-related malfunction, this situation is determined through the digital twin-based control mechanism. In the case of actual failure, the system is stopped, but in the case of measurement or connection errors, since the data are calculated by the DT model, the value in the specified region is known and thus there is no need to stop the system. This prevents production loss in the hydroelectric power plant by ensuring the continuity of the system in case of errors.

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To build a comprehensive framework for virtual power plant (VPP) development aligned with market dynamics and to devise effective strategies to foster its growth, this study undertakes several key steps. Firstly, it constructs a VPP development framework based on market conditions, to drive the evolution of new power systems and facilitating energy transformation. Secondly, through a blend of theoretical analysis and model construction, the fundamental principles of VPP are systematically elucidated, and a decision model for the VPP development framework, focusing on price demand response, is formulated. Lastly, an optimal scheduling model for the new power system is developed, with its efficacy validated across three distinct scenarios. The findings underscore the critical importance of integrating energy storage technologies, particularly pumped storage hydropower systems, for achieving balance and optimization within new power systems. Model verification reveals that the incorporation of energy storage power stations significantly enhances system stability and efficiency, particularly in addressing the volatility associated with renewable energy sources. Additionally, the analysis indicates that while the adoption of energy storage technologies may marginally increase overall power generation costs, the total power generation cost declines with the integration of battery storage and pumped storage hydropower stations. This suggests that leveraging energy storage technologies not only enhances system operational reliability but also contributes to reducing the overall cost of power production to a certain extent. In summary, this study presents an economic and environmentally sustainable scheduling model for new power systems within the context of market trading environments. By offering both theoretical insights and practical guidance, it aims to support sustainable development and energy transformation initiatives. Ultimately, the study is poised to foster the adoption of clean energy, facilitate the establishment of smart grids, and bolster the sustainable utilization of energy resources, thereby advancing environmental conservation efforts.

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PURPOSE OF REVIEW: Numerous epidemiological studies have shown increased health risks among workers and residents living near nuclear power plants exposed to radiation levels meeting regulatory dose limits. This study aimed to evaluate the association between radiation exposure and disease risks among these populations exposed to radiation levels meeting the current regulatory dose limits. RECENT FINDINGS: We searched four databases (Cochrane Library, PubMed, ScienceDirect, and Web of Science) for studies published before August 2023, screened eligible studies (inclusion and exclusion criteria based on population, exposure, comparator, and outcome framework), and collected data on exposure indicators and disease risks. We applied random-effects models of meta-analysis to estimate the pooled effects and meta-regression to assess the dose-response relationship (radiation dose rate for workers and distance for residents). We identified 47 studies, 13 with worker and 34 with resident samples, covering 175 nuclear power plants from 17 countries, encompassing samples of 480,623 workers and 7,530,886 residents. Workers had a significantly lower risk for all-cancer and a significantly higher risk for mesothelioma. Residents had significantly higher risks for all-cancer, thyroid cancer, and leukemia. Notably, children under 5 years old showed the highest risk for all-cancer. Our meta-regression showed a significantly positive dose-response relationship between cumulative dose of radiation exposure and risk for circulatory disease among workers. Our findings demonstrated higher risks for mesothelioma for workers and all-cancer, thyroid cancer, and leukemia for residents exposed to low-dose radiation from nuclear power plants. Some included studies did not adjust for cancer risk confounders, which could overestimate the association between radiation exposure and cancer risk and increase the risk of bias.

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For over 12 years since the 2011 East Japan Earthquake, the decontamination of radioactive materials is still incomplete. Although evacuation orders had been lifted in ~15% of Futaba town, the site of the Fukushima Daiichi Nuclear Power Plant, by August 2022, anxiety regarding the effects of nuclear radiation persists among evacuees, and their intention to return (ITR) remains low. As of August 2023, only 90 residents lived there. As the only town with government functions relocated outside Fukushima Prefecture, Futaba has more residents who evacuated outside the prefecture. Although numerous factors affect risk perception and ITR to the place of previous residence, the impact of evacuation destination on risk perception remains unknown. Therefore, this study aimed to evaluate the impact of evacuation destination on radiation risk perception. In 2022, a survey was conducted on 404 evacuees aged >18 years. The responses were compared between groups outside and inside Fukushima using the chi-square test and multivariate logistic regression analysis. Significant relationships were found between the evacuation destination and risk perception of genetic effects in the next generation (odds ratio [OR] = 1.92, 95% confidence interval [CI]: 1.15-3.20) and of the health effects of radiation (OR = 1.76, 95%CI: 1.10-2.84), which were both higher in those who had evacuated outside Fukushima. These findings stress the importance of evacuation destination choice and information access for evacuees' risk perception. Enhanced education and support efforts are necessary to help evacuees not only in Fukushima but also throughout Japan.

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