• Energy Research
• 2021-2025close
• Open Access close
• 7. Clean energy close
• 1. No poverty close

Tsunamis pose a significant threat to the construction of Nuclear Power Plants. Therefore, it is necessary to carry out a comprehensive study regarding the potential threat of tsunamis and mitigation measures using detailed data at prospective locations. This assessment is a prerequisite for effective environmental impact planning and analysis. To determine the suitability of a prospective location, careful consideration of natural factors, including earthquakes as triggers for tsunamis, is essential. The main objective of this tsunami research is to assess the level of safety of potential locations against tsunami hazards and develop appropriate mitigation strategies. This research uses the Cornell Multigrid Coupled Tsunami (COMCOT) tsunami modeling technique. This modeling approach utilizes topographic and bathymetric data obtained through extensive field surveys. In addition, this research aims to determine the maximum tsunami height in the inundation area and identify potential tsunami hazards arising from various scenarios related to the active tectonic potential of the Philippine Manila Trench. The Bengkayang Gosong Beach area and West Kalimantan are among the candidate locations that may be affected with the estimated tsunami height being between 0.48 meters and 0.62 meters. The tsunami arrival time was between 9 hours 10 minutes to 9 hours 24 minutes. These findings play an important role in conducting comprehensive risk assessments for nuclear power plant development, ensuring that necessary steps are taken to reduce potential hazards associated with tsunamis.

Climate change is a global problem, which affects the various geographical regions at different levels. It is also associated with a wide range of human health problems, which pose a burden to health systems, especially in regions such as Africa. Indeed, across the African continent public health systems are under severe pressure, partly due to their fragile socioeconomic conditions. This paper reports on a cross-sectional study in six African countries (Ghana, Nigeria, South Africa, Namibia, Ethiopia, and Kenya) aimed at assessing their vulnerabilities to climate change, focusing on its impacts on human health. The study evaluated the levels of information, knowledge, and perceptions of public health professionals. It also examined the health systems’ preparedness to cope with these health hazards, the available resources, and those needed to build resilience to the country’s vulnerable population, as perceived by health professionals. The results revealed that 63.1% of the total respondents reported that climate change had been extensively experienced in the past years, while 32% claimed that the sampled countries had experienced them to some extent. Nigerian respondents recorded the highest levels (67.7%), followed by Kenya with 66.6%. South Africa had the lowest level of impact as perceived by the respondents (50.0%) when compared with the other sampled countries. All respondents from Ghana and Namibia reported that health problems caused by climate change are common in the two countries. As perceived by the health professionals, the inadequate resources reiterate the need for infrastructural resources, medical equipment, emergency response resources, and technical support. The study’s recommendations include the need to improve current policies at all levels (i.e., national, regional, and local) on climate change and public health and to strengthen health professionals’ skills. Improving the basic knowledge of health institutions to better respond to a changing climate is also recommended. The study provides valuable insights which may be helpful to other nations in Sub-Saharan Africa.

AbstractThe concept of a ‘just transition’ to a low‐carbon economy is firmly embedded in mainstream global discourses about mitigating climate change. Drawing on Karl Polanyi's political economy elaborated inThe Great Transformation, we interrogate the idea of a just transition and place it within its historical context. We address a major contradiction at the core of global energy transition debates: the rapid shift to low‐carbon energy‐systems will require increased extraction of minerals and metals. In doing so, we argue that extractive industries are energy and carbon‐intensive, and will enlarge and intensify social and ecological injustice. Our findings reveal the importance of understanding how the idea of a just transition is used, and by who, and the type of justice that underpins this concept. We demonstrate the need to ground just transition policies and programmes in a notion of justice as fairness.

Thermal comfort is very important for the well-being and safety of vehicle occupants, as discomfort can elevate stress, leading to distracted attention and slower reaction times. This creates a riskier driving environment. Addressing this, high-induction air diffusers emerge as a significant innovation, enhancing indoor environmental quality (IEQ) by efficiently mixing cool air from the heating ventilation and air conditioning (HVAC) system with the cabin’s ambient air. This process ensures uniform airflow, diminishes temperature discrepancies, prevents draft sensations, and boosts overall air quality by improving air circulation. In addition to enhancing thermal comfort in vehicles, the novel air diffuser also offers significant potential for personalized ventilation systems, allowing for individualized control over airflow and temperature, thereby catering to the specific comfort needs of each occupant. This study introduces a novel air diffuser that demonstrates a 48% improvement in air entrainment compared to traditional diffusers, verified through Ansys Fluent simulations and laser Doppler velocimetry (LDV) measurements. At a fresh airflow rate of 31.79 m3/h, the total air entrainment rate at 0.6 m for the standard air diffuser is 73.36 m3/h, while for the innovative air diffuser, it is 109.26 m3/h. This solution has the potential to increase the level of thermal comfort and air quality within vehicles, and also signals potential applications across various enclosed spaces, underscoring its importance in advancing automotive safety and environmental standards.

Datacenter power demand has been continuously growing and is the key driver of its cost. An accurate mapping of compute resources (CPU, RAM, etc.) and hardware types (servers, accelerators, etc.) to power consumption has emerged as a critical requirement for major Web and cloud service providers. With the global growth in datacenter capacity and associated power consumption, such models are essential for important decisions around datacenter design and operation. In this paper, we discuss two classes of statistical power models designed and validated to be accurate, simple, interpretable and applicable to all hardware configurations and workloads across hyperscale datacenters of Google fleet. To the best of our knowledge, this is the largest scale power modeling study of this kind, in both the scope of diverse datacenter planning and real-time management use cases, as well as the variety of hardware configurations and workload types used for modeling and validation. We demonstrate that the proposed statistical modeling techniques, while simple and scalable, predict power with less than 5% Mean Absolute Percent Error (MAPE) for more than 95% diverse Power Distribution Units (more than 2000) using only 4 features. This performance matches the reported accuracy of the previous started-of-the-art methods, while using significantly less features and covering a wider range of use cases.

A large part of incident solar radiation on photovoltaic (PV) modules is converted into heat, leading to overheating and reduction of PV modules performance. The present work investigates the impact of rectangular aluminium fins (RAFs) and evaporative cooling represented by cotton wicks immersed water (CWWs) on the performance and thermal behaviour of the PV module. Results indicate that the evaporative cooling attained better cooling potential than RAFs, in which the PV module temperature was reduced by 22.3%, and the output power was enhanced by 73% thanks to continuous cooling of the PV module. A slight improvement in the PV module performance was observed with RAFs due to the increased heat transfer area, which reduced temperature by up to 6.7% and increased the output power of the PV module by up to 21.3 %. Exergy analysis shows a gradual increment of the electrical exergy and exergy efficiency using CWWs, which reduces the entropy generation of it more than RAFs. The study concluded that PV modules without cooling in hot climate areas may deteriorate their performance significantly.

The utilization of autonomous unmanned aerial vehicles (UAVs) has increased rapidly due to their ability to perform a variety of tasks, including industrial inspection. Conducting testing with actual flights within industrial facilities proves to be both expensive and hazardous, posing risks to the system, the facilities, and their personnel. This paper presents an innovative and reliable methodology for developing such applications, ensuring safety and efficiency throughout the process. It involves a staged transition from simulation to reality, wherein various components are validated at each stage. This iterative approach facilitates error identification and resolution, enabling subsequent real flights to be conducted with enhanced safety after validating the remainder of the system. Furthermore, this article showcases two use cases: wind turbine inspection and photovoltaic plant inspection. By implementing the suggested methodology, these applications were successfully developed in an efficient and secure manner.