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Aviation is one of the most significant growth drivers not only for the transportation infrastructure, but also for country’s economy as it contributes to both industrial and social progress of society. The paper focuses on Sheremetyevo International Airport, one of the largest Russian airports and analyzes it in terms of short-term and long-term perspectives. Using real statistical data, the article presents the models for forecasting essential performance indicators of airports, namely, passenger traffic and revenue. By comparing quality characteristics, most suitable models were selected and checked for adequacy. Forecasts of the probable changes in the values of the performance indicators were made under the assumption of maintaining the previously formed development trend.

Closed-loop supply chain networks are gaining research popularity due to environmental, economic and social concerns. Such networks are primarily designed to overcome carbon footprints and to retrieve end of life products from customers. This study considers a multi echelon closed-loop supply chain in the presence of machine disruption. A multi-objective model is presented to optimize the total cost, the total time and emissions in a closed-loop supply chain network. The aim is to analyze the trade-off between the objectives of cost, time, and emissions and how these decisions are impacted by the selection of different available machines. A number of solution approaches are tested on a case study from the tire industry. The results suggest the improved performance of the hybrid heuristic and the importance of controlling disruption in a closed-loop supply chain network. Furthermore, there is a trade-off between the different objective functions which can help the decision maker to choose a particular solution according to the preference of an organization. Finally, conclusion and future research avenues are provided.

The oil production and refining processes are directly dependent on historical and political processes. The world wars of the 20th century were catalysts for the transformation of oil as the main energy resource. The capacity of enterprises in the oil refining industry is important for the development of politics and economies of states because oil products are one of the most sought after goods. Addressing the problem of capacity development for oil resource processing at Russian refineries is a relevant topic to build an effective policy for the distribution of global oil resources. The purpose of this paper is to identify the distribution trends in oil resource refining capacities in Russia. The developed method allows us to determine the dynamics of refining capacities in all regions of the country, establish the contributions of refinery groups to regional and countrywide capacities, and identify trends in the capacity concentrations of refineries and regions. The timeline that was used for the research period is 2009–2019. The results of the study showed increases in processing capacity in all federal districts. By 2019, the Volga Federal District provided the largest annual contribution to the countrywide capacity. The Southern Federal District moved up from the fourth to second position. It was followed by the Siberian, Central, Northwestern, Far Eastern, and Ural Federal Districts. The trends in the distribution capacities across the country indicate the prospect for building additional refineries in the Asian part of Russia. Rosneft was the leader, while Gazprom retained the second position. Independent refiners took the third position in terms of total refinery capacity, with Lukoil in the fourth position. Furthermore, Surgut-NG, Tatneft, Mini refineries, and NOVATEK followed the top four positions. The changes in concentration ratios indicated the increased monopolization of the refinery market. A decisive contribution to this process was due to by Rosneft’s takeover of TNK-BP and Bashneft’s capacities. The changes in regional concentrations were influenced by the changes in processing capacities of the Volga Federal District.

Nowadays, most countries of the world are implementing the transition to the low-carbon economy which implies the need to carry out a full-scale eco-modernization of the energy sector. Green energy may be identified as one of the core concerns of energy sector modernization as it allows a considerable decrease in emissions of harmful substances into the atmosphere. Therefore, nuclear and renewable energy may become key areas of global energy development in the near future, which is also in agreement with circular economy concepts. However, public opinion (and other controversial visions/aspects) is one of the barriers to their development. The purpose of this study is to analyze the relationship between attitudes towards nuclear and renewable energy in two countries: a EU country (Italy) and a non-EU country (Russia), considering the level of their development. The authors conducted a survey among residents regarding their attitude towards nuclear and renewable energy, as well as their attitude to the present energy policy. The cluster analysis technique was used to analyze the results. The obtained results confirmed the dependence between the level of development of nuclear and renewable energy and the public attitude towards it. The national energy policy also might influence public opinion on the development of nuclear or renewable energy. The authors identified public attitude as one of the key factors in the development of energy and the achievement of environmental and social sustainability.

Abstract Mitigating the effects of environmental deterioration requires a focus on not just CO2 emissions from energy consumption, but also environmental pollution from industry sectors. To reach this goal, recent studies have extended ecological footprint (EF) analysis to identify the ecological drivers of various key industry sectors. The role of the phosphorus (P) industry on the EF within the environmental Kuznets curve (EKC) framework for China is the emphasis of this study. Autoregressive distributive lag (ARDL) as well as the impulse response function and robustness analysis were used to consider a time from 1985 to 2018. The study verifies the EKC hypothesis for China in both the long and the short run, and indispensable determinants are proposed to be included to assure the model’s fitness and robustness when conducting EF analysis of industry sectors. Energy consumption–based carbon emissions have been verified as the dominant contributor to EF, but P use and urbanization have a significant lagged positive influence on EF in the short run. P exports, in particular, have been highlighted as a critical driver of the EF of China’s P industry. The conducted frequency domain causality test reinforced the above findings and demonstrated bidirectional causality at different frequencies. This work suggests that formulating plausible P export policies to alleviate the conflict between the output of China’s P industry and the environmental sustainability of this industry are necessary. In this context, “multidisciplinary, multidimensional, and practical solutions” are most desirable for sustainable P management.

The concept of the “Energy strategy of Russia for the period up to 2035” implies a comprehensive structural transformation of the energy sector and its transition to a qualitatively new level through the use of digital technologies. One of the first steps in building a model of the Internet of energy in Russia may be the introduction of a mechanism for creating industrial microgrids, for which a draft resolution of the government of the Russian Federation has already been developed. The article considers the features of functioning of a new subject of electric power industry - active energy complexes, their conceptual, economic and legal features, and also developed a method for evaluating the system effects of their implementation.

The purpose of the article is to study the dynamics of volumes and stability of the structure of energy resource consumption at manufacturing enterprises, the analysis of the technical readiness of energy systems to implement the ideas of digital transformation. As the main research methods used in this article there are the method of dipole energy analysis to determine the priority of types of energy carriers, the method of graphical visualization of data to find the release points of values from the zone of relative stability, the method of classifying objects to assign products to a group of objects on the level of energy sustainability. The article analyzes the current trends in energy consumption with the determination of the vector of sustainable energy consumption and the parameters of reserves for improving energy efficiency; prioritized separate types of energy production of petrochemical plants; the types of products were classified according to the level of sustainability of energy consumption with the establishment of control points having emissions of values from the zone of relative stability and unproductive consumption of energy resources; the high technical readiness of energy systems of manufacturing industries to automate production processes with the subsequent development of digital technologies has been proved.

Over the last few decades, environmental deterioration has accelerated significantly. Environmental degradation has been a subject of research across the world because of its impact on billions of people. However, there has been no international agreement on lowering the utilization of energy and CO2 emissions (CO2), while demand for fossil fuels grows in emerging economies. On the other hand, the recent COP26 summit brought all parties together to accelerate action toward reaching the goals of the Paris Agreement and the UN Framework Convention on Climate Change. Although previous research shows that international trade promotes positive socioeconomic outcomes, other experts argue that it contributes to natural resource shortages and ecological deterioration. Thus, the current research considers the effect of international trade, renewable energy use and technological innovation on consumption-based carbon emissions (CCO2), coupled with the role of financial development and economic growth in the BRICS economies between 1990 and 2018. Moreover, this research utilizes the common correlated effects mean group (CCEMG), augmented mean group (AMG) and Dumitrescu and Hurlin (2012) causality methods to assess these interrelationships. The study findings reveal that renewable energy use, exports and technological innovation mitigate CCO2, whereas economic growth and imports trigger CCO2 in the BRICS economies. The panel causality outcomes also reveal that all the variables except financial development can predict CCO2 emissions. Based on the study findings, we recommend the adoption of policies, regulations and the development of legislative frameworks that promote technological innovation and the shift toward sustainable energy.