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Abstract This study investigates the non-linear relationship between urbanization paths and CO2 emissions in selected South, South-East, and East Asian countries over the period 1971–2014. Based on the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) framework, we applied the advanced and robust methods of dynamic seemingly unrelated regression (DSUR), dynamic OLS (DOLS), and fully modified OLS (FMOLS) to estimate the long-term effects. The empirical findings revealed the inverted U-shaped effects of urbanization and urban agglomeration and the U-shaped impact of the largest city ratio on CO2 emissions. Urbanization and urban agglomerations improve environmental quality in the long-run and support ecological modernization theory. However, excessive concentration in the largest cities have severely affected the environmental quality and violates the notion of compact-city efficiencies. Moreover, energy intensity and economic growth positively affect CO2 emissions, while trade openness negatively influences CO2 emissions. Our robustness analysis at the country-level applies the augmented mean group (AMG) panel ARDL technique, which further supports the non-linear effect of urbanization paths on CO2 emissions except for a few countries. The results of the panel Granger non-causality approach unveil bidirectional causality of energy efficiency, economic growth, urbanization, and largest city ratio with CO2 emissions. In contrast, unidirectional causality runs from urban agglomeration to CO2 emissions. Our findings have important policy implications as we suggest green urban infrastructures, eco-friendly dwellings, smart cities, country-specific trade policies, and renewable energy options to improve the environmental quality.

Abstract Socio-technical transformations towards low-carbon energy systems are on the way in developed countries. Conversely, developing countries tend to be locked in fossil fuels and foster coal-based energy structures, emphasizing reliable and cost-effective energy provision and sidelining environmental concerns. In this study, we identified and analysed the predominant factors related to coal-based power generation in Bangladesh. We applied a mixed-method approach, initially conducting a systematic literature review and, subsequently, semi-structured expert interviews to identify and validate relevant factors. We then assessed their relative importance using an Analytical Hierarchy Process based on expert judgments. The results of this assessment reveal that socio-economic aspects and environmental issues scored highest, while technological aspects and sector regulations were considered to be less relevant for large-scale coal power implementation. We conclude that future energy policies created in Bangladesh will need to use appropriate legal instruments and address issues such as human displacement and resettlement, low levels of public acceptance, health hazards and environmental pollution. Participative policy frameworks should be deployed in coal plant projects, and active monitoring systems are necessary to reduce the negative consequences associated with increased electrification and energy consumption. To address foreseeable structural challenges, it furthermore will be crucial to explore sustainable alternatives.

Simulation of air infiltration and ventilation, and heat transfer processes of buildings are combined in a building simulation program called BUS (version 3.2). The program applies and includes an effective sparse matrix solution method for a linear set of equations. A network assumption is adopted for both air flow and thermal simulation. An iterative method, based on the SIMPLE algorithm, is used for airflow simulation, and the lumped capacitance method is selected for thermal simulation. This building simulation program BUS includes mass balance, momentum, and heat balance equations. This makes it possible to lake into consideration the interaction between ventilation and heat transfer processes, obtain more reliable simulation results than previously, and simulate time-dependent processes.

Abstract Additional experimental data concerning the kinetics of Ni-Mo codeposition were obtained by investigating cathodic polarization using a rotating disc electrode. The Ni-Mo alloys were deposited from an ammonium citrate bath. The alloy deposition was controlled by activation in the case of low values of the cathode potential and by diffusion in the case of higher values. The hydrogen discharge was found to be diffusion controlled. The inductive influence of nickel results in depolarization of the reduction of molybdenum which cannot be deposited separately. An increase in the disc rotation speed caused an increase in the maximum cathode efficiency and in the molybdenum content of the alloy.

Abstract Pollution control strategies currently in use by electric power systems are reviewed and a new minimum emission dispatch (MED) method is developed. This new method minimizes overall emission levels at an increased cost in large-scale power systems while simultaneously accommodating local pollution level requirements, as well as economic constraints.

Abstract Newer generation sources and loads are posing new challenges to the conventional power system protection schemes. Adaptive and intelligent protection methodology, based on advanced measurement techniques and intelligent fault diagnosis such as machine learning (ML), is found to be useful to meet these challenges. A large number of research works are reported on ML-based power system fault diagnosis. However, ML techniques are evolving at a very fast pace, and an inclusive, as well as state-of-the-art review on ML-based power system fault diagnosis, is not available in the literature. Given this need and growing trend towards ML, the study presented in this paper aims to provide a comprehensive review of ML-based power system fault diagnosis. At first, efforts have been made to enlist the issues present in conventional fault diagnosis which led to the popularity of ML techniques. Also, a baseline framework and workflow for ML-based fault diagnosis are presented. Next, various unsupervised and supervised learning techniques have been discussed separately which have been used by several researchers for fault diagnosis. The discussion throughout is supported with tabulated facts for fault detection, classification and localization works with techniques used, different simulation tools used, and their application system. The advantages and disadvantages of all the techniques of fault diagnosis have also been discussed which will help the readers in the selection of techniques for their research. A brief review of reinforcement learning and transfer learning is also given as they are gaining popularity in power system-related studies and have the potential to be used for fault diagnosis. Finally, the research trends, some key issues, and directions for future research have been highlighted.

Oil shale is a very important alternative energy, hydraulic mining is an effective method for oil shale utilization in Jilin Province. For the Nong'an oil shale in Jilin Province, the average compressive strength of horizontal bedding is 17.14MPa, and the average compressive strength of vertical bedding is 10.90MPa. For cone straight-shaped nozzle, when the jet pressure P is 10MPa and the nozzle outlet diameter d is 1mm, striking force generated by the jet is 15.65N, it can break the oil shale.

The results obtained at the All-Russia Scientific-Research Institute of Chemical Technology on the use of sorption processes in the hydrometallurgy of refractory metals and purposeful synthesis of the required ion-exchange materials are presented. It is shown on the basis of synthesized ionites that the ion-exchange technology is efficient for processing complex technological solutions for different types of polymetallic raw materials, including uranium ores, concentrates from enrichment of ores of refractory metals, commercial products, and waste solutions. The technological schemes developed have been successfully adopted on an industrial scale. 3 figures, 1 table, 12 references.