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Recycled polylactic acid (PLAr) was reinforced with treated nanocellulosic hemp fibers for biocomposite fabrication. Cellulosic fibers were extracted from hemp fibers chemically and treated enzymatically. Treated nanocellulosic fibers (NCF) were analyzed by Fourier-transform infrared spectroscopy, X-ray diffraction, and scanning electron microscopy. Biocomposite fabrication was done with PLAr and three concentrations of treated NCF (0.1%, 0.25%, and 1% (v/v)) and then studied for thermal stability and mechanical properties. Increased thermal stability was observed with increasing NCF concentrations. The highest value for Young’s modulus was for PLAr + 0.25% (v/v) NCF (250.28 ± 5.47 MPa), which was significantly increased compared to PLAr (p = 0.022). There was a significant decrease in the tensile stress at break point for PLAr + 0.25% (v/v) NCF and PLAr + 1% (v/v) NCF as compared to control (p = 0.006 and 0.002, respectively). No significant difference was observed between treatments for tensile stress at yield.

The importance and urgency of energy efficiency in sustainable development are increasing. Accurate assessment of energy efficiency is of considerable significance and necessity. The data envelopment analysis (DEA) method has been widely used to study energy efficiency as a total factor efficiency assessment method. In order to summarize the latest research on DEA in the field of energy efficiency, this article first analyzes the overall situation of related literature published in 2011–2019. Subsequently, the definition, measurement and evaluation variables of energy efficiency are introduced. After that, this article reviews the current DEA model and its extension models and applications based on different scenarios. Finally, considering the shortcomings of the existing DEA model, possible future research topics are proposed.

This research investigates the relationships among renewable energy consumption, economic growth, and financial development in five sub-Saharan African nations utilizing panel data from 2000 to 2020. Econometric methods are used to ascertain the existence or absence of cross-sectional dependence and the short-run and long-run connections between the following factors: Pesaran cross-sectional dependence (CD) and cross-sectionally augmented IPS (CIPS) unit root tests, pooled mean group (PMG), and dynamic ordinary least squares (DOLS) estimations. The presence of cross-sectional dependence is found and represented with the CIPS unit root test. No significant short-run relationship is found between the variables of the study, yet a significant long-run relationship is present among them. A positive relationship exists between CO2 emissions and financial development, while financial development and renewable energy consumption are found to have negative relationships with CO2 emissions. The study also supports the scale effect of the environmental Kuznets curve hypothesis. Additionally, no causality is found among the variables, and impulse response and variance decomposition estimation are carried out to recommend future effects. Policy implications of findings are discussed, with accompanying suggestions.

With regard to underground mining, methane is a gas that, on the one hand, poses a threat to the exploitation process and, on the other hand, creates an opportunity for economic development. As a result of coal exploitation, large amounts of coal enter the natural environment mainly through ventilation systems. Since methane is a greenhouse gas, its emission has a significant impact on global warming. Nevertheless, methane is also a high-energy gas that can be utilized as a very valuable energy resource. These different properties of methane prompted an analysis of both the current and the future states of methane emissions from coal seams, taking into account the possibilities of its use. For this reason, the following article presents the results of the study of methane emissions from Polish hard coal mines between 1993–2018 and their forecast until 2025. In order to predict methane emissions, research methodology was developed based on artificial neural networks and selected statistical methods. The multi-layer perceptron (MLP) network was used to make a prognostic model. The aim of the study was to develop a method to predict methane emissions and determine trends in terms of the amount of methane that may enter the natural environment in the coming years and the amount that can be used as a result of the methane drainage process. The methodology developed with the use of neural networks, the conducted research, and the findings constitute a new approach in the scope of both analysis and prediction of methane emissions from hard coal mines. The results obtained confirm that this methodology works well in mining practice and can also be successfully used in other industries to forecast greenhouse gas and other substance emissions.

Nuclear power can replace fossil fuels and will have a decisive impact on the change in the approach to conventional energy. However, nuclear (or radioactive) wastes are produced by the operation of the nuclear reactors should be safely and properly disposed of. This paper assesses the uranium resources and the global state of nuclear power plants and determines the energy mixes in different countries using the most nuclear energy. Furthermore, this paper analysed the nuclear waste management and disposal and the depletion of abiotic resources, and the primary energy sources of a basic production process using electricity mix and nuclear electricity for a basic production (PET bottle manufacturing) process. The life cycle assessment was completed by applying the GaBi 8.0 (version 10.6) software and the CML method. In this study, we limit our discussion to high-level nuclear waste (HLW) and spent nuclear fuel (SNF) waste. We do not consider waste generated from uranium mining and milling, which is usually disposed of in near-surface impoundments close to the mine or the mill. The investigation of waste management methods is limited to European countries. This research work is relevant because determining abiotic resources is important in a life cycle assessment and current literature available on LCA analysis for nuclear powers remains under-developed. These results can guide and compare manufacturing processes involving a nuclear electricity and electricity grid mix input. The results of this research can be used to develop production processes using nuclear energy with lower abiotic depletion impacts. This research work facilitates the industry in making predictions for a production-scale plant using an LCA of production processes with nuclear energy consumption.

This article discusses the problems of exhaust gas emissions in the context of the possibility of their reduction through the use of fuels with hydrogen as an additive or hydrotreatment. These fuels, thanks to their properties, may be a suitable response to more and more demanding restrictions on exhaust emissions. The use of such fuels in reactivity controlled dual fuel engines (RCCI) is currently the most effective way of using them in internal combustion (IC) engines. Low-temperature combustion in this type of engine allows the use of all modern fuels intended for combustion engines with high thermal efficiency. Thermal efficiency higher than in classic engines allows for additional reduction of CO2 emissions. In this work, the research on this subject was compiled, and conclusions were drawn as to further possibilities of popularizing the use of these fuels in a wide spectrum of applications and the prospect of using them on a mass scale.

The main objective of the research is to assess the ability of the Ukrainian economy and its individual industries to ensure, in the conditions of economic growth, a stable reduction of natural gas consumption and, consequently, to reduce dependence on its imports. Six types of relationships were identified between the change in sectoral added value and the change in the consumption of certain energy resources, in particular natural gas. The conditions are established under which the growth of sectoral added value is accompanied by a decrease in the consumption of certain energy resources. The index of sectoral efficiency of the use of certain energy resources was proposed and a model of the decomposition of the growth rate of this indicator was constructed. Quantitative indicators of measuring economic barriers on the way to introduction of energy-saving technologies are presented. Conditions under which economic growth is accompanied by a decrease in the level of dependence of the economy on imports of energy resources are modeled. The dynamics of natural gas consumption by sectors of the Ukrainian economy is analyzed. It is proved that reduction of natural gas consumption due to increased energy efficiency occurs mainly in industries with an average value of share of the cost of purchasing this energy in the total operating expenses. An estimation is undertaken of the possibility of achieving independence of the Ukrainian economy from the import of natural gas in different scenarios of changing main parameters that determine the probability of such an achievement.