Technological Level Research Articles

EXPERIMENTAL ASSESSMENT OF CHANGES IN THE STRUCTURE OF FOOD-GRADE ANTI-CORROSION STEEL DUE TO THE USE OF FLOWDRILL TECHNOLOGY

Machining technologies are constantly evolving in line with new material development strategies, with further advances in cutting tools accelerating these changes even further. Growing demands for increased productivity and production efficiency have led us to today's advanced level of technology. Recently, steel structures made of thin sheets and strips, which are processed by bending, three-dimensional forming or pressing, often in combination with technologies such as ribbing, have been increasingly used. Open and closed rolled profiles are increasingly being replaced by more economical and lighter sheet metal strip materials, which provide similar or even higher strength at a significantly lower weight. Flowdrill technology is often used when joining light sheet metal profiles in a demountable manner, which enables the creation of a cylindrical surface necessary for the subsequent shaping of the thread. Flowdrill thermal drilling technology represents an innovative and forward-looking method of producing precise cylindrical housings in thin-walled materials such as sheets, profiles of various shapes and pipes. This technology uses frictional heat, which is generated by a combination of high tool speeds and axial force acting on the workpiece. Frictional heat causes the material to soften, allowing the tool to smoothly penetrate the workpiece and form a sleeve from the displaced material [Rimar 2023]. This process inspired experimental measurements aimed at analyzing the influence of technology parameters on the material. The aim of the experiments was to investigate structural changes in food-grade anti-corrosion steel EN ISO X10CrNi18-8 (17241) as a result of Flowdrill thermal drilling, by analyzing the state of the material before and after the application of this technology. The results of these measurements will bring valuable knowledge to technologists, which will help them choose suitable materials and drilling technologies in practice.

Impact of state capacity on entrepreneurship: does national developmental and technological level matter?

PurposeThe current study empirically examines the influence of state capacity on entrepreneurship.Design/methodology/approachThis research draws upon the national measures of 118 countries and employs a more robust measure of state capacity.FindingsThe findings show a positive correlation between state capacity and entrepreneurship. However, the results reveal that the effect of state capacity on entrepreneurship is stronger in developing low-technology nations compared to developed high-technology nations.Research limitations/implicationsWhen available, future research could employ more recent data to estimate the effects of state capacity on entrepreneurship. In addition to developmental and technological levels, various other factors can also be explored such as national culture and welfare regime type.Practical implicationsThe current study enables policymakers to identify factors critical in developing state capacity. Policymakers can also have better-tailored approaches for developing targeted initiatives and establishing entrepreneurship-supportive regulative institutional arrangements.Originality/valueAvailable literature lacks in empirically examining the influence of state capacity on entrepreneurship. The current study attempts to fill this gap.

Estimation of the distribution of deflation sites on the territory of the Nenets Autonomous Okrug by data of remote sensing

Geoinformation assessment of deflation processes in the Arctic conditions makes it possible to move to a new technological level in the planning of forest reclamation of the landscapes of the Arctic zone. The use of forest reclamation and phytomelioration of accumulative forms makes it possible to control desertification processes. To achieve the purpose of the study – to assess the spatial distribution of deflated surface areas on the territory of the Nenets Autonomous Okrug, a geoinformation analysis of current space sensing data was carried out and the degree of degradation (deflation and anthropogenic transformation) of the territory in controlled areas was revealed, on the basis of which the necessary measures are proposed to prevent land deflation and it is planned to create an information system for monitoring and forecasting the state of soil and vegetation cover. The decoding of satellite images of deflation sites in the research area made it possible to develop vector cartographic GIS layers, which show selected coastal, continental not grown and overgrown massifs. The conducted geomorphological differentiation of deflation sites makes it possible to effectively use such parameters as tiering, exposure, meso- and microclimatic differences, as well as plan anti-deflation measures. Vector cartographic layers of the spatial distribution of sandy accumulative forms have been developed and their morphometric characteristics have been determined, the features of the development of continental and coastal deflation have been established, the areas of which are 31.51 and 20.86 thousand hectares, respectively, the total number of sites allocated by vector contours exceeds 166 thousand, and their sizes vary from 0.001 hectares to more than 5.5 thousand hectares. As a result of a spatial assessment of 68 large sandy massifs overgrown with vegetation, their area of 543.85 thousand hectares has been established.

Spatial Correlation Network Characteristics and Influencing Factors of Industrial Carbon Emission Efficiency of Cities in Pearl River Basin

China has experienced rapid development of urbanization and industrialization, and urban industrial carbon reduction has become the key to green and sustainable development. Exploring urban industrial carbon emissions and its spatial correlation characteristics is of great importance for promoting collaborative cooperation between cities and achieving the "dual carbon" goal. Considering 49 cities in the Pearl River Basin as research objects, the super slacks-based measure model was used to measure the urban industrial carbon emission efficiency from 2010 to 2020, and exploratory spatiotemporal data analysis was used to explore its spatial pattern. On this basis, we used social network analysis and quadratic assignment procedure （QAP） methods to explore the spatial correlation network characteristics and influencing factors of urban industrial carbon emission efficiency. The results indicated that the industrial carbon emission efficiency of the Pearl River Basin showed a downward trend. Additionally, a strong spatial imbalance and heterogeneity was observed. The Pearl River Delta Region always dominated the spatial correlation network of carbon emission efficiency, forming a multi-level composite network system with the core network as the primary component and the conventional network as the auxiliary component. Economically developed cities, such as Guangzhou, Shenzhen, and Dongguan have long been in the center of the network and have extensive connections with other cities, while playing an intermediary role. The level of urbanization, science and technology, and industrialization have an increasingly significant positive impact on the strength of the connection between urban industrial carbon emission networks. The Pearl River Basin industrial carbon emission efficiency network has significant individual differences and hierarchical characteristics. According to the individual centrality, network role, and clustering characteristics, combined with the corresponding influencing factors, the Pearl River Basin urban collaborative carbon emission reduction strategy was formulated. This study can provide reference for the formulation and implementation of regional low-carbon collaborative development strategies.

The Role of Innovation Management in Driving Educational Technology Adoption in Emerging Economies

The rapid socio-economic changes in emerging economies demand integrating educational technologies to improve learning outcomes and prepare students for the globalized economy. The successful adoption of these technologies relies on effective innovation management, which must address challenges such as limited infrastructure and varying technological literacy levels. This research investigates the role of innovation management in facilitating the adoption of educational technologies in emerging economies. It aims to identify strategies to overcome barriers to technology integration in education and analyze their impact on academic outcomes. A mixed-methods approach was employed, combining quantitative data from global databases such as the World Bank's EdStats and UNESCO's Institute for Statistics with qualitative insights from interviews and case studies in selected emerging economies, including India, Kenya, Brazil, and Nigeria. Statistical analyses revealed a positive correlation between the Innovation Support Index and the Educational Technology Adoption Rate. For instance, India and Brazil demonstrated higher adoption rates (78% and 80%, respectively) corresponding to robust innovation support systems. In contrast, countries with lower innovation indices, like Nigeria, showed significantly lower adoption rates (50%). The study concludes that strategic innovation management is critical for driving the successful adoption of educational technologies in emerging economies. It emphasizes the need for policymakers and academic leaders to prioritize the development of innovation support systems to foster a conducive environment for technology integration. Strengthening innovation support systems significantly enhances the adoption of educational technologies, offering a pathway to improved educational equity and economic growth in these regions.

Analysis of the Impact and Mechanism of Financial Technology Levels on Green Productivity

This paper selects the data of A-share listed companies in Shanghai and Shenzhen from 2013 to 2023, and explores the impact and mechanism of enterprise financial technology level on green productivity based on the perspective of green technology innovation. It was found that improving enterprise financial technology levels significantly promotes enterprise green technology innovation, and this conclusion is still based on the discussion of endogeneity issues and a series of robustness tests. In terms of the mechanism of action, the increase in the level of enterprise financial technology increases the investment in scientific and technological innovation, which in turn effectively promotes the green technological innovation of enterprises. At the same time, the strengthening of market competition in the industry further enhances the green innovation effect. Heterogeneity analysis reveals that both the property rights and the industry have a significant impact on the improvement of the financial technology level to promote enterprise green technology innovation. This paper reveals the key role of financial technology in enterprise innovation strategy. It provides empirical evidence for the promotion of financial technology innovation and the optimization of green productivity development path.

Short-term stock indices as a tool for assessing and forecasting scientific and technological security

Objectives. Ensuring scientific and technological sovereignty, defined as one of the objectives of the Concept of Technological Development for the period until 2030, approved by the Order of the Government of the Russian Federation No. 1315-r dated May 20, 2023, implies the use of effective mechanisms for managing the country’s economy. Under contemporary conditions, technology is a crucial element in the country’s economic development and a key component of scientific and technological security. Thus, the aim of the present work is to develop existing methods for analyzing economically significant information relating to the monitoring and diagnostics of scientific and technological security at the meso- and macrolevels.Methods. The developed method for scientific and technological security level monitoring and forecasting, which is based on the dynamics analysis of the values of corporate securities, includes economic and statistical analysis methods, machine learning and time series analysis tools.Results. The approach towards information processing and enhancement of analysis mechanisms in managerial decisions, which relies on diagnostic, analysis, and forecasting tools for socioeconomic system scientific and technological security, is based on information-processing, economic, and mathematical methods. The presented results constitute a developed method for the analysis of systemically important enterprises stock indices, supporting research and development to assess and predict scientific and technological security dynamics at meso- and macro levels of the economy. In order to verify the methodology, a numerical experiment was carried out using statistical data from systemically important companies.Conclusions. The developed methodology is aimed at improved managerial decision-making accuracy and speed when solving problems connected with scientific and technological security underpinning socioeconomic systems. The experimental results quantitatively confirm the significant contribution made by systemically important companies to Russian Federation’s scientific and technological security ensuring.

Digital Transformation of Enterprises and Labor Force Structure Upgrading: Research Progress and Prospect

The transformation of the enterprise digital economy has had a profound effect on the employment of the labor force. Although extant document has discussed the digital economy, there is still a large space for deep analysis and theoretical framework construction of the impact of the digital Economy in Workforce Transformation. This research will look at the intrinsic impact of the digital economy on labor transfer or distribution. Digital capital complements a highly skilled labor force and promotes the upgrading of enterprise labor skill structure; digital transformation mainly affects three aspects: adopting new digital technology, optimizing labor organization form and adjusting business model. Changes of labor force in all respects as a result of the digitalization of business. In the background of the popularization of digital technology, the demand for low-skilled labor rises in the market, which promotes the upgrade of a commodity economy and the pursuit of a higher level of life; Digital transformation promotes the upgrading of enterprise labor skill structure, and different development regions and sizes have distinct differences in labor substitution. The effects of the digital transition can positively affect the innovation of the business model. Based on digitalization, The labor market's iterative renewal will have a decisive impact on the improvement of technology levels and the changing labor force structures.

The impact of agricultural production agglomeration on agricultural economic resilience: based on spatial spillover and threshold effect test

This study focuses on the role of agricultural production agglomeration in strengthening agricultural economic resilience, exploring the threshold effect of agricultural technological innovation level and the spatial spillover effect of agricultural production agglomeration on agricultural economic resilience. We conducted research across 31 provinces (including autonomous regions and municipalities) in China from 2007 to 2022. By constructing the evaluation index system of agricultural economic resilience, the entropy value method is used to measure the value of agricultural economic resilience, and then kernel density estimation and spatial econometrics model, threshold regression model are used to analyze the relationship between agricultural production agglomeration, agricultural technological innovation and agricultural economic resilience. (1) The analysis of the spatiotemporal evolution trend shows that the overall level of China’s agricultural economic resilience continued to rise, and presented a spatial development pattern of “high in the east and low in the west.” The overall level of agricultural production agglomeration in China shows a trend of first rising and then falling, among which the level of agricultural production agglomeration in the central region is significantly higher than that in the northwest and southeast regions. (2) The spatial Durbin model shows that agricultural production agglomeration can not only effectively improve the level of local agricultural economic resilience, but also have a positive impact on neighboring agriculture economic resilience produces positive spatial spillover effects. (3) Agricultural production agglomeration can improve the level of agricultural economic resilience by promoting agricultural social service. (4) The impact of agricultural production agglomeration on agricultural economic resilience shows great differences in different geographical regions. Among them, agricultural production agglomeration in the central region has a significant positive impact on the agricultural economic resilience of both local and adjacent areas. (5) The threshold effect model shows that the impact of agricultural production agglomeration on agricultural economic resilience has significant nonlinear characteristics, and its impact shows an increasing marginal effect as the level of agricultural technological innovation increases. To address this, policymakers should reinforce agricultural cluster construction, boost innovation capacity and treasure spillover effects between regions. These insights provide valuable direction for policymakers in crafting effective measures to enhance agricultural economic resilience.

Examination of elementary school students digital literacy levels in terms of different variables

The aim of this study is to examine the digital literacy levels of primary school students according to different variables. The survey model was used to investigate how technology, which has become one of the most important needs of today, affects the digital literacy of primary school students who have experienced distance education. The participants of the study consisted of 100 students studying in a city center located in the Black Sea region of Turkey. The data were obtained by using the personal information form developed by the researchers and the "Digital Literacy" scale developed by Pala and Başıbüyük (2010). In the analysis of the data, percentage, arithmetic mean, gender, independent sample t-test for the variables of availability of technological tools, one-way analysis of variance (ANOVA) was used for the variables of parental education level, place of residence, time spent with technology and family income level. As a result of the research, it was seen that the digital literacy level of the students was at an average level and that the digital literacy of the students showed significance according to the family income level and the availability of internet at home, while there was no significant difference according to variables such as gender, parental education level, and the availability of technological devices. Based on the data of the study, it is recommended to include related courses in the curriculum for the positive development of students' digital literacy.

OM Forum—Asset-Level Perspectives on the Clean Energy Transition

Problem definition: The clean energy transition is an important component of the net zero transformation, which aims at averting potentially disastrous climate change related to excessive global warming by practically eliminating new global greenhouse gas emissions within 2050. The resulting move toward decarbonized energy systems is projected to encompass massive investments in assets that employ technologies with low environmental impact, some of which are innovative or yet unproven or even undeveloped, an area known as CleanTech. The typical analyses that are informing the dialogue on this process in practice provide insights into decarbonization paths at the technology level. In contrast, managers need to make decisions about assets. Methodology/results: Taking an asset-level view of the clean energy transition that complements its technology outlook, this essay provides a concise entry point into this topic based on both the practitioner literature and personal reflections, highlighting CleanTech innovations and related operational considerations in carbon capture, use, and storage; sustainable fuels; hydrogen; electricity; and concomitant government support activities. Managerial implications: Further, this work advocates for potential CleanTech research or teaching pursuits, especially ones aimed at directly supporting managerial decision making, for which it provides an example from the literature.

Physics and technology maturity level required for the K-DEMO design points

The conceptual design study for the Korean fusion demonstration reactor (K-DEMO) has been conducted, placing an emphasis on the imperative to reduce the reactor's dimension as a means to cost minimization. The design space of K-DEMO was delineated based on maturity level of physics and technology. Advanced technology features such as a use of a tungsten carbide (WC) shield, a tritium breeding blanket concept of He cooled lithium lead (HCLL), the maximum allowable magnetic field at the TF coil, Bmax = 16 T with a Nb3Sn superconducting material, etc. were adopted. With specified design criteria, including a net electric power ≥ 300 MW, a fusion gain, Q > 20.0, a neutron wall loading < 2.0 MW/m2, an indicator of divertor power handling capability (ratio of power to divertor to major radius), Pdiv/R0 < 25 MW/m, and the capability for steady-state operation, a design space of the K-DEMO was established based on the energy confinement scaling law of IPB98[y,2] under physics level of Greenwald density fraction, ne/nG < 1.2, normalized plasma beta (ratio of plasma pressure to magnetic pressure normalized by plasma current divided by the product of minor radius and toroidal magnetic field), βN < 3.0, confinement enhancement factor, H < 1.3, and a direct cost ≤ 7.5 B$. After an exploration of system parameters, prospective design points for K-DEMO were identified, characterized by a major radius, R0 ∼ 6.8 m, an aspect ratio, A = 3.1, a toroidal magnetic field at plasma center, BT ≥ 6.5 T, and a fusion power, Pfusion ∼ 1,500 MW. When β-independent energy confinement scaling law was applied, the design points were accessible with smaller ne/nG, βN, H, Pfusion, and larger BT. From a sensitivity analysis of the minimum major radius to the input parameters, strong sensitivities to Greenwald density fraction, ne/nG, normalized plasma beta, βN, confinement enhancement factor, H, edge safety factor, qedge, and elongation, κ were found. Additionally, the operational envelope in physics and technology parameters was established with system parameters associated with the design points.

Research on factors influencing total carbon emissions of construction based on structural equation modeling: A case study from China

As a pillar industry in China, the construction sector plays a crucial role in advancing the country's carbon emission (CE) reduction initiatives. The factors influencing CE in the construction industry (CI) are numerous and complex. This paper analyzes the influencing factors of CE in the CI based on structural equation modeling. Firstly, by combining the relevant literature and actual situation of CE in the CI, 38 common influencing factors corresponding to the building, economic, social, technological and energy levels are initially selected, and the data corresponding to each influencing factor in each province and city in China for 10 years are collected and then processed without dimension. Secondlyd, 12 hypothetical relationships between building, economic, social, technological and energy and CE from the CI are established based on the actual situation, and the initial CE in the CI structural equation model is established after the data set is tested for normal distribution, reliability and validity. Thirdly, the model is evaluated for path significance and model fit, and the modified structural equation model of CE from the CI is obtained after the initial model is modified, and the modified model is evaluated again. Finally, based on the modified model, the influence degree and effect of CE influencing factors in the CI are analyzed. It is concluded that economy, technology, and energy are the main factors successively affecting the total CE of buildings.

Technostress levels of science field faculty members in the Kyrgyz Republic

The purpose of this study was to examine the technostress levels of science field faculty members in the Kyrgyz Republic. The relational survey model was used to investigate whether there was a significant difference and a relationship between demographic variables such as gender, age, field of science, seniority, technological education level, and availability of a personal computer in terms of technostress and its sub-dimensions. The sample of the study consisted of 274 science faculty members, with 156 females and 118 males working at different universities in the Kyrgyz Republic. “Personal Data Form” and “Defining Teachers’ Technostress Levels Scale” were used as data collection tools in the study. The results showed that the general technostress levels of the participants were at a medium level. General technostress levels and technostress sub-dimensions scores of science faculty members did not differ by their genders, ages, seniorities, technology educations, and availability of their computers. There was a low level of positive correlation between age and the scores of the occupational and personal sub-dimensions of technostress; It was determined that there was a low-level, positive, statistically significant relationship between the seniority variable and the personal-oriented sub-dimension. It can be concluded that as the year of seniority progresses, academicians' technostress scores also increase. These findings reveal that seniority has certain effects on the technostress levels of academicians, but these effects vary based on sub-dimensions.

Intelligent Monitoring System for Roller-Compacted Earth-Rock Dam Construction Process

Abstract The conventional quality control method of earth-rock dam is insufficient to meet the requirements of intelligent and fine management of dam filling construction in the new stage. With the expansion of construction scale and the overall improvement in information technology level, the traditional compaction quality control methods no longer meet the demands of modern mechanized rapid construction or provide real-time compaction information for engineering contractors. In response to the current conventional design and construction schemes for earth-rock dams, an intelligent real-time monitoring system established in this paper for compaction construction of earth-rock dams. This system utilizes advanced Beidou high-precision positioning and navigation technology, vibration-sensing IoT technology, real-time processing of massive construction information, and BIM technology. It achieves real-time intelligent monitoring of key compaction processes in dam construction and refined management of unit engineering. The intelligent system established provides crucial technical support for the safe and reliable operation of water conservancy and hydropower projects. Simultaneously, it enables real-time, remote, and intelligent monitoring of dam construction processes, significantly enhancing the technological content and informatization level of water conservancy engineering construction.

Technoeconomic analysis of supercritical water gasification of canola straw for hydrogen production

Production of hydrogen from renewable sources is gaining popularity to reduce our dependency on non-renewable fossil fuels to meet growing hydrogen demand. However, despite the great prospect of production of hydrogen from sustainable sources such as lignocellulosic biomass via supercritical water gasification (SCWG), it has not been commercialized at a large industrial scale. This is due to the lack of detailed economic analysis of SCWG of lignocellulosic biomass, owing to the complexity of the SCWG process and the heterogeneous nature of biomass. Therefore, to address this knowledge gap, in this study, a detailed technoeconomic analysis (TEA) of a conceptual SCWG pilot having the capacity to process 200 tons/day of canola straw for the production of green hydrogen was conducted. Mass and energy balance of conceptual pilot was performed using Aspen Plus ® simulation by utilizing experimental data and hydrogen yield of 41.62 mmol/g was obtained at optimized reaction conditions of 500 °C, 23 MPa, and 10 wt%. Economic analysis based on calculated mass and energy balance was performed using SuperPro software. Cash flow analysis for capital expenses (CAPEX) of 81 Million USD showed a high internal rate of return (IRR) of 38.9% and an undiscounted net present value (NPV) of 548 million USD. A minimum selling price (MSP) of 3.38 USD/kg H2 for produced hydrogen was estimated, which is lower than other renewable hydrogen production processes and comparable to non-renewable hydrogen production technologies. A high positive IRR and NPV, while a lower MSP showed that despite having a low technological readiness level (TRL) of 4, SCWG of lignocellulosic biomass is a technically feasible and economically viable process for the production of hydrogen. Furthermore, sensitivity analysis also revealed that capital expenses (CAPEX) and canola straw price had the highest influence on net present value (NPV) and MSP. However, overall NPV and MSP were highly stable to changes in parameters highlighting the robustness of the economic analysis.

Nuclear Waste Management in India Vis-A-Vis Sustainable Development: Policies and Practices

Energy is everything that comes from the sun to the air we breathe, to water and wind. Now the population is increasing and so is technology level, we are using Energy from every resource that is available on the earth. We now know that there are all forms of energy known to this planet upon which we base our civilization, some renewable, some non-renewable or in the language jargon of today: conventional or non-conventional that have a great deal to do with said improvement in quality of life. Energy is utilized by all sectors such as industry, commerce, agriculture, household, transport and also for telecommunication etc. Thus, in simplest terms Energy is Work done. We can go to the moon or expedition Antarctica just because of harnessing energy fuels. We are moving ahead in the era of modernism and among them, the dependency on energy is rising. Rapidly depleting all other forms of resources, the technology has now turned to nuclear capabilities. Nuclear is not just the largest source of energy, it is also a very clean option for producing power. The management of nuclear wastes in India is a crucial area that at the intersection of larger goals for sustainable development. With India in process of expanding its nuclear power programme by the year 2050 to meet energy needs and to cut down its carbon emissions, responsible management of nuclear waste will become even more vital, for environmental sustainability as well as public safety. Some even confirmed to the query Are we headed towards a nuclear future? &amp; Is nuclear energy indeed be the answer to India's increasing power needs?

Advancing Neural Networks: Innovations and Impacts on Energy Consumption

AbstractThe energy efficiency of Artificial Intelligence (AI) systems is a crucial and actual issue that may have an important impact on an ecological, economic and technological level. Spiking Neural Networks (SNNs) are strongly suggested as valid candidates able to overcome Artificial Neural Networks (ANNs) in this specific contest. In this study, the proposal involves the review and comparison of energy consumption of the popular Artificial Neural Network architectures implemented on the CPU and GPU hardware compared with Spiking Neural Networks implemented in specialized memristive hardware and biological neural network human brain. As a result, the energy efficiency of Spiking Neural Networks can be indicated from 5 to 8 orders of magnitude. Some Spiking Neural Networks solutions are proposed including continuous feedback‐driven self‐learning approaches inspired by biological Spiking Neural Networks as well as pure memristive solutions for Spiking Neural Networks.

TECHNOLOGICAL PROSPECTION OF THE USAGE OF BARU FRUIT (DIPTERYX ALATA VOG.) TO IMPROVE THE LIVING CONDITIONS OF QUILOMBOLAS, EXTRACTIVIST COMMUNITIES IN BRAZIL

Barueiro (Dipteryx alata Vog.) is an arboreal plant species native to Brazil's fertile Cerrado region. holds great promise for cultivation and technological development due to its versatile uses and the complete reuse of its parts. Given its local significance, increased research support is essential, as the species has the potential to generate high-value products and offer a sustainable income source for its producers. This study is a prospective analysis of articles and patents on barueiro (baru fruit), highlighting that most technologies have low technological readiness levels (TRL 3-4) and remain at the bench stage, with most patents filed by universities. Collaboration between extractive communities and academia is crucial for knowledge transfer, cooperative creation, and project development for processing centers, training, and decentralized energy generation, thereby supporting SDGs and circular economy principles by adding value and improving community well-being. Once these cooperatives and processes are established, applying for geographical indication could further enhance the value of baru-based products.

Diversifying the Business of Oil and Gas Companies in the Context of Global Climate Policy

In 2019, Russia, being a climate-conscious country, ratified the Kyoto Protocol to the UN Framework Convention on Climate Change caused by anthropogenic emissions of greenhouse gases. The increase in the emissions is primarily driven by the advancements in energy production. The existing level of technology for processing and using raw materials in many energy industries leads to dangerous environmental pollution and causes an increase in environmental problems. Many companies have adopted their carbon neutrality strategies to use "green energy" based on ESG criteria, which allows them to increase their competitive advantages. Achieving carbon neutrality involves minimizing direct emissions during production processes or shifting to renewable energy sources. The paper examines the transformation of the oil and gas companies towards cutting greenhouse gas emissions and analyzes the mechanisms for achieving decarbonization. To assess the effectiveness of investment projects in the field of low-carbon energy, the paper analyzes an approach and proposes a dynamic simulation model based on a modification of the discounted cash flow method. The model is tested under the assumption that carbon regulation is carried out through the introduction of a carbon border tax.