Journal of Environmental Treatment Techniques  
2020, Volume 8, Issue 2, Pages: 639-645  
J. Environ. Treat. Tech.  
ISSN: 2309-1185  
Journal web link: http://www.jett.dormaj.com  
Management of a Sustainable Development of the  
Oil and Gas Sector in the Context of  
Digitalization  
1
2
3
Alexey I. Shinkevich , Damir R. Baygildin , Ekaterina L. Vodolazhskaya  
1
Department of Logistics and Management, Kazan National Research Technological University (KNRTU), Kazan, Russia  
2
Department of Public and Municipal Administration, The Institute of Management, Economics and Finance, Kazan (Volga region) Federal  
University Kazan, Russia  
3
Department of Business Statistics and Economics, Kazan National Research Technological University (KNRTU), Kazan, Russia  
Received: 10/01/2020  
Accepted: 14/03/2020  
Published: 20/05/2020  
Abstract  
The oil and gas sector is characterized by a high level of polluting emissions, which confirms the need for the development of  
a management mechanism in the field of automation and greening of technological processes. Thus, in the conditions of the fourth  
industrial revolution, digital transformation is an integral element of sustainable development. The purpose of the study is to  
develop a methodology for assessing the sustainable development of the oil and gas sector of the Russian economy, taking into  
account aspects of digitalization. The methodological base covers the method of systematization of the collected information, which  
made it possible to track the dynamics of changes in the environmental and economic indicators of the oil and gas sector and in the  
mining industry as a whole; modeling method (including the correlation-regression method and the method of principal  
components), which determined the mathematical relationships between indicators of sustainable development and digital  
transformation of the oil and gas sector; forecasting method, which presents scenarios of changes in the level of environmental  
friendliness of the oil and gas sector. As a result, a linear regression model is proposed that reflects the dependence of emissions  
of harmful substances by mining enterprises on the financial leverage ratio and determines the necessitates to increase the ratio in  
order to reduce harmful emissions; alternatives options of forecasting the level of harmful emissions by the mining industry of the  
Russian economy are developed; to assess the sustainable development of the oil and gas sector of the Russian economy in the  
context of digitalization, an integrated sustainable development index is elaborated through the use of the factor analysis tool. The  
factors identified by the principal component analysis enable to evaluate the influence of digitalization on the sustainable  
development of the oil and gas sector of the Russian economy. In addition, correlation coefficients between each selected factor  
and each variable were pairwise estimated. Based on the simulation results, interdependencies of two key aspects of the study - the  
sustainable development of the oil and gas sector and its digital transformation are observed. The practical significance of the  
obtained model lies in the possibility of its application in order to predict the sustainable development of the oil and gas sector in  
Russia, taking into account the industry digitalization trend. The results of this study can be taken into account in strategic  
documents and programs for the development of the oil and gas sector and digital transformation of the industrial complex of the  
Russian Federation.  
Keywords: Oil and gas sector, Sustainable development, Digital technologies, Factor analysis, Sustainable development index  
1
Introduction  
1
respectively [1]. Energy production is directly accompanied  
by emissions of harmful substances. Technological  
development, automation of production processes and  
modernization of monitoring systems make it possible to  
timely capture and neutralize atmospheric pollutants and  
help to reduce harmful effects on the environment. The goal  
of sustainable socio-economic development of Russia is  
enshrined in documents such as the Decree of the President  
of the Russian Federation “On the Concept of the Transition  
of the Russian Federation to Sustainable Development” [2],  
State Program of the Russian Federation “Development of  
Industry and Increasing Its Competitiveness” [3], State  
Program of the Russian Federation “Economic Development  
and innovative economy” [4], “Strategy for the socio-  
economic development of the Republic of Tatarstan until  
The basis of this study is the concept of “sustainable  
development”, which is inaccurate reflected in the Russian  
translation, since the definition of “sustainable  
development” at first glance does not take into account the  
environmental aspect. The primary source, which firstly  
mentioned «sustainable development» term was the World  
Conservation Strategy. Today, the concept of sustainable  
development, which firmly entrenched in the theory and  
practice of economic systems, involves the consolidation of  
three factors - economic, social and environmental.  
The oil and gas industry is an intense environmental  
pollutant. Oil and gas production and energy consumption  
are steadily increasing. Oil and gas production in Russia has  
increased over the past 5 years by 5.5% and 13%  
Corresponding author: Alexey I. Shinkevich, Department of Logistics and Management, Kazan National Research Technological  
University (KNRTU), Kazan, Russia. E-mail: ashinkevich@mail.ru.  
6
39  
Journal of Environmental Treatment Techniques  
2020, Volume 8, Issue 2, Pages: 639-645  
2
030” [5] and others. Despite the fact that Russia's transition  
industrial enterprises is considered in the works of V.P.  
Meshalkin and E.R. Moshev [17], E.R. Moshev and M.A.  
Romashkin [18]. Digitalization of the industrial sector is  
reflected in the works of T.V. Kulagi, A.V. Babkina and S.A.  
Murtazaev [19], P. Gölzer and A. Fritzsche [20]. The issues  
of digitalization of the oil industry, contributing to the  
reduction of harmful emissions are the subject of A.E.  
Vorobiev, K.A. Vorobev and H. Tcharo [21]. The research  
topics mentioned above are quite extensive and are not  
limited to the specified list of researchers. However, there is  
a scarcity of studies which empirically investigates the area  
of sustainable development of the oil and gas sector, taking  
into account the digital vector of economic development.  
This fact determines the relevance of the topic covered in  
this paper and the theoretical significance of the results.  
Thus, the formation of a digital platform to control the  
environmental impact of industry is broad interest to  
scientists. However, the studies are primarily of a technical  
nature, which allows us to conclude that it is necessary to  
develop a methodology for assessing the impact of the  
industrial complex on the environment.  
to sustainable development was planned back in 1996, the  
country lags far behind developed and a number of  
developing countries. According to the level of the  
Sustainable Society Index (SSI), in 2016 among 154  
countries of the world, Russia ranked 64th in terms of human  
well-being, 144th in terms of environmental well-being and  
3
7th in terms of economic well-being [6].  
Nowadays digital technology is an important tool for  
economic development. The fourth industrial revolution  
covers the whole world and it is an unconditional catalyst for  
increasing the competitiveness of industrial complexes and  
enterprises. In the framework of the “digital” development  
vector, the National Program “Digital Economy of the  
Russian Federation” outlines the task: to put into operation  
the unified state cloud platform and a cyber-attack warning  
system by the end of 2021[7].  
As for the digitalization of the oil and gas sector of the  
Russian economy, it is necessary to note the relatively low  
“digital” activity of the industry, which negatively affects its  
competitiveness in the world market. In accordance with the  
Business Digitalization Index (Business Digitalization index  
reflects the percentage of organizations using digital  
technologies of the total number of organizations in the  
business sector), the extractive sector with an indicator of  
3
Description of Data  
According to statistical and coming from stationary  
sources data, the volumes of air polluting emissions  
generated as a result of oil and natural gas production  
decreased by 20.83% over 2012-2018, which is shown in  
Fig. 1 [8]. Over the same period, an increase in the level of  
capture of pollutants in the corresponding industry sector  
was recorded by 68.64% (Fig. 1) [8]. Nevertheless, the  
volumes of neutralized substances emanating from  
stationary sources in the field of crude oil and natural gas  
production at the end of 2018 amounted to only 3.7% of the  
total emissions. One of the key ways to reduce the degree of  
negative impact on the environment is to ensure energy  
efficiency, which has high potential in the oil and gas sector  
and involves the rationalization of energy use, taking into  
2
9.1% lags behind the telecommunications sector (42.5%),  
the trade sector (35.7%), manufacturing industry (34.9%),  
information technology industry (34.7%), etc. [23].  
Secondly, in the structure of shipped goods, works and  
services in the Russian economy, the prevailing share of  
shipped goods and services are accounted fot the extraction  
of crude oil and natural gas (18.49% in 2018) and the  
production of coke and oil products (14.93% in 2018) [8].  
Third, well drilling operations are very complex. They are  
carried out in an environment with high risks to health and  
safety, and often cover the interactions of a wide range of  
suppliers jointly drilling of one well. Fourth, the share of  
drilling costs in the total cost structure is 40–70% of the  
capital costs of an oil and gas company [9].  
account economic and technological parameters.  
A
comparative analysis of the energy intensity of GDP in the  
world and in Russia allows us to state a high level of the  
indicator in the domestic economy, which is 2-3 times higher  
than the energy intensity in the OECD countries [22]. A  
related area for reducing atmospheric emissions is the  
digitalization of the oil and gas sector, which had the highest  
activity in 2015 (Fig. 2).  
The above emphasizes the importance of integration of  
both aspects of the modernization of the oil and gas industry  
-
development of a methodology for assessing the evolution  
of the oil and gas sector of the Russian economy.  
sustainable development and digitalization, while  
2
Literature Review  
At the same time, statistics represent only the use of  
information technologies for the automation of processes  
and production, which, in fact, does not reflect digitalization  
as such and complicates the objective assessment of the  
digitalization of these processes. However, based on the  
statistical base, we emphasize that, in general, the digital  
activity of extractive enterprises is unstable and reflects the  
low interest of business entities in digitalization. As a result,  
trends in reducing the negative impact of the industrial  
complex on the environment, but low volumes of capture of  
air polluting substances and a decrease in the digitalization  
rate of industrial enterprises determine the urgency of  
developing a system for monitoring and managing the  
sustainable development of the oil and gas industry.  
The economic aspects of the development of the oil and  
gas industry are studied in a number of papers. L.V. Eder  
10] published a series of works containing an economic  
[
assessment of the state of the oil and gas sector. T.V.  
Malysheva et al. [11] contributed to the coverage of the  
economic and environmental aspects of industrial  
development. Environmental safety issues in industrial  
development are disclosed in the works of A.N. Dyrdonova  
[12, 13]. In the papers of T.V. Alexandrova [14] provisions  
regarding the implementation of the environmental  
responsibility of oil and gas enterprises are disclosed. Also,  
she reflected the goals of sustainable business development.  
S.A. Patin [15] deeply reveals the technological features of  
the offshore oil and gas industry and presents a methodology  
for assessing environmental risk and the economic damage  
resulting from oil pollution. A methodology for assessing the  
sustainable development of an industrial region was  
proposed by O.S. Korobova [16] and represents an economic  
approach to monitoring based on an integrated indicator of  
the region’s carbon intensity.  
Moreover, the need for  
a systematic approach to  
management is obvious. According to these trends, the  
development of a rational methodology for assessing the  
impact of an industrial complex on the environment, capable  
of providing alternative options for this effect in the future,  
as well as the development of an assessment of the  
sustainable development of an industrial complex taking into  
account digital parameters, is relevant. The solution of these  
problems is proposed to be carried out through economic and  
mathematical modeling.  
Along with the foregoing, studies in the field of digital  
transformation of macro-, meso- and microeconomic  
systems are also relevant. So, information support of  
6
40  
Journal of Environmental Treatment Techniques  
2020, Volume 8, Issue 2, Pages: 639-645  
7
6
5
4
3
2
1
000  
000  
000  
000  
000  
000  
000  
0
-
20,83%  
6
8,64%  
2
012  
2013  
2014  
2015  
2016  
2017  
2018  
Emission of pollutants into atmosphere from stationary sources, thou. tonnes  
Rrecovery and disposal of industrial and municipal wastes, mln. tonnes  
Figure 1: Pollution and neutralization of harmful substances in the field of crude oil and natural gas production (compiled according to the  
Federal State Statistics Service, from: http://www.gks.ru)  
4
4
4
4
4
3
3
3
3
3
4
3
2
1
0
9
8
7
6
5
42,9  
40,9  
40,4  
40,1  
39,3  
38,1  
2
012  
2013  
2014  
2015  
2016  
2017  
Figure 2: The share of mining organizations using information technology as part of the automation of production and  
technological processes, % (compiled from the HSE) [23].  
Y = а  
0
+ b  
1
*x  
1
+ … + b  
i
*x  
i
,
(1)  
4
Methods and Models  
The formation of a methodology for assessing the  
where Y is a dependent variable, a  
0
is the free term of the  
sustainable development of the oil and gas sector in the  
context of digitalization covers a number of stages and  
economic-mathematical models, including: 1) correlation  
and regression analysis, allowing to identify the dependence  
of the environmental component of the mining industry on  
economic indicators of the performance of the oil and gas  
sector; 2) scenario modeling, contributing to the  
construction of forecasting models that reflect the level of  
environmental friendliness of the oil and gas sector; and 3)  
factor analysis, allowing to identify the aggregated  
components of sustainable development, taking into account  
the influence of digital technologies, which as a result is  
integrated into a single methodology for assessing the  
sustainable development of the oil and gas sector. In order to  
assess the environmental impact of the industrial complex, a  
model of correlation and regression analysis was applied. In  
the framework of the correlation analysis, the closeness of  
the relationship between the dependent and independent  
variables is estimated. Significant correlation coefficients  
exceeding 0.6 are recognized. The linear regression equation  
has the form:  
i
estimation line, the value of Y at zero x; b - gradient of the  
estimated line, reflects the change in Y with increasing x by  
one; x is an independent variable. The obtained regression  
i
equation is considered to be qualitative if the determination  
2
coefficient R exceeds 0.7 (according to the Cheddock  
scale), if the calculated value of the Fisher F-criterion  
exceeds the tabular one, and the regression coefficients are  
significant if the calculated values of the t-criterion exceed  
the tabulated ones [24]. Correlation-regression analysis was  
carried out according to the following variables [1]: (a)  
atmospheric emissions of pollutants emanating from  
stationary sources in the field of mining, thousand tons (B,  
dependent variable); (b) coefficient of profitability of sales  
by net profit for the oil and gas industry in Russia,% (К  
R
);  
(c) production efficiency coefficient for the revenue of the  
oil and gas industry in Russia, rub. / t. t. (KEP); (d) asset  
turnover ratio of the oil and gas industry in Russia,% (KAT);  
(e) financial leverage ratio of the Russian oil and gas  
industry,% (RFL). At the next stage, pessimistic and  
optimistic scenarios of the impact of the oil and gas industry  
on the environment are constructed. The best prognostic  
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41  
Journal of Environmental Treatment Techniques  
2020, Volume 8, Issue 2, Pages: 639-645  
model is selected taking into account the highest value of the  
reliability of the approximation R , exceeding a level of 0.7.  
 Social options:  
x6 - average monthly nominal accrued wages of  
employees, rubles. (for mining);  
- the average annual number of employees,  
thousand people. (for mining).  
2
Also, due to the lack of  
a single integrated  
methodological approach to assessing sustainable  
development, including taking into account the specifics of  
the industrial complex, an index of sustainable development  
of the oil and gas complex, taking into account the  
digitalization factor, has been proposed. As a method of  
forming the index, a factor analysis tool is used, which is  
implemented in the Statistica package for statistical data  
processing. The method allows to aggregate a number of  
variables into aggregated factors, combined on the basis of  
latent relationships. Thus, indicators are classified into  
categories. The analysis is based on the principal component  
method, which assumes that the variances of the variables  
are 1. Factors include only variables that have high  
correlation coefficients (greater than 0.7). The determination  
of the optimal number of factors is carried out according to  
the Kaiser criterion, according to which factors with  
eigenvalues exceeding 1 are included in the model. Each  
factor is described by a dependence on factor loads taking  
into account the correlation coefficients between each  
variable and the aggregated factor:  
x
7
Digitalization Options:  
x
8
- the cost of information and communication  
technologies (ICT) per 1 RUB. Shipment, rub / rub. (for  
mining);  
9
x - the intensity of the use of software in organizations  
extracting minerals for the management of automated  
production and individual technical means and technological  
processes, the share of organizations in the total number of  
organizations in the business sector;  
x10 - the intensity of the use of electronic data exchange  
technologies between their and external information systems  
in organizations extracting minerals, the share of  
organizations in the total number of organizations in the  
business sector;  
x11 - the intensity of broadband Internet use in  
organizations extracting minerals, the share of organizations  
in the total number of organizations in the business sector;  
12  
x - the intensity of use of ERP-systems in  
organizations extracting minerals, the share of organizations  
in the total number of organizations in the business sector;  
 x13 - the intensity of use of CRM systems in  
n
(2)  
F  r  x ,  
i
ij  
j
i1  
organizations extracting minerals, the share of organizations  
in the total number of organizations in the business sector;  
where n is the number of identified factors; rij is the  
correlation coefficient between the ith factor and the jth  
variable (j is the number of variables), i.e. factor load; x is  
j
the value of the jth variable. The author’s model of integrated  
assessment of the sustainable development of the oil and gas  
complex is based on a formula, the general mathematical  
form of which is presented below:  
x14 - the intensity of the use of SCM systems in  
organizations extracting minerals, the share of organizations  
in the total number of organizations in the business sector.  
5
Results and Discussions  
5
.1 A model of the Dependence of Environmental Factors  
in the Oil and Gas Sector on Economic Indicators  
n
The study assessed the environmental impact of the oil  
and gas industry. Initial parameters were key indicators of  
the performance of the oil and gas sector (economic  
indicators, including profitability ratios of sales, production  
efficiency, asset turnover, financial leverage of the oil and  
gas sector, etc.). The close relationship between the level of  
atmospheric emissions of pollutants emanating from  
stationary sources (in the field of mining) and the following  
economic indicators are identified: (a) the coefficient of  
profitability of sales by net profit for the oil and gas industry  
in Russia (%) - is 0.66; (b) the coefficient of production  
efficiency for the revenue of the oil and gas industry in  
Russia (rubles / ton UT) – is -0.67; (c) asset turnover ratio of  
the oil and gas sector in Russia (%) – is 0.71; (d) financial  
leverage ratio of the Russian oil and gas sector (%) - is -0.96.  
The significant regression equation was obtained in only one  
of the following cases:  
I    F ,  
i
i
i1  
(
3)  
where λ  
i
is the eigenvalue of the ith factor. In order to switch  
to dimensionless quantities, the data was standardized using  
formula (4) [25]:  
xij  X j  
yij   
S j  
(4)  
where yij is the normalized value; S  
of the jth variable; xij is values of different dimensions; 푋 is  
j
is the sample variance  
̅
푗
the sample mean of the jth variable. The information base for  
building economic and mathematical models was data  
published in the publication of the Institute of Petroleum  
Geology and Geophysics named after A.A. Trofimuka SB  
RAS [1] and database of Federal State Statistics Service [8]  
and the Higher School of Economics [23]. So, the indicators  
characterizing the 3 components of sustainable development  
for 2011-2018 were selected. Environmental parameters:  
В = 7729,36 – 4064,42*RFL  
,
(5)  
The resulting regression equation has a high degree of  
process description, in other words it is qualitative, since the  
x
1
- emissions into the atmosphere of pollutants  
2
coefficient of determination R = 0.914. Evaluation of the  
emanating from stationary sources, thousand tons (for  
mining);  
Fisher and Student criteria allows us to conclude that the  
obtained equation is adequate, the coefficients are significant  
and the equation can be considered acceptable for predicting  
emissions in future reporting periods. Independent variable -  
x
2
- utilization and neutralization of production and  
consumption wastes, mln tons (for mining).  
Economic parameters:  
- profit margin of sales by net profit for the oil and  
RFL is of interest. It reflects the ratio of liabilities to equity.  
х
3
In the oil and gas sector of the Russian economy, this  
indicator for the years 2012-2018 ranges from 0.43% to  
0.75% [1], which indicates the use by enterprises own equity  
mainly. Given the inverse dependence of polluting emissions  
by mining enterprises on the financial leverage ratio, it must  
gas industry in Russia,%;  
- coefficient of economic efficiency of capital  
investments in the oil and gas industry of Russia,%;  
- net profit of the oil and gas sector, billion rubles  
x
4
x
5
6
42  
Journal of Environmental Treatment Techniques  
2020, Volume 8, Issue 2, Pages: 639-645  
be concluded that active attracting and using borrowed  
capital, will increase the environmental friendliness of  
industrial production. In addition, the optimal level of RFL  
in the Russian economy is 1 (or 100%), i.e. equal ratio of  
own and borrowed funds. Thus, increasing RFL is important  
both from an economic and environmental point of view.  
a) Pessimistic forecast  
7
000  
500  
6
5
.2 Forecasting Models Reflecting Alternative Scenarios of  
5
875,3  
Changes in the Level of Environmental Friendliness of the  
Oil and Gas Sector in Russia  
6000  
2
y = 75,156x - 763,99x  
6663,6  
+
5
500  
000  
The obtained regression model allows us to build  
pessimistic (Fig. 3a) and optimistic (Fig. 3b) scenarios of the  
impact of the oil and gas industry on the environment. In the  
table 1, the results are systematized and the obtained  
regression equation is verified.  
5
361,7  
5
4500  
000  
4
The forecast was calculated by two methods: based on  
the construction of a trend line described by the equation of  
dependence (polynomial and power-law trend line), and  
calculation of emissions based on the constructed regression  
equation, taking into account the trend value of the financial  
leverage ratio of the Russian oil and gas sector. In the first  
case, the predicted values of emissions polluting the  
atmosphere in 2020 under the optimistic scenario is 4,554.6  
thousand tons, with the pessimistic scenario they will  
increase to 5,875.3 thousand tons. The constructed  
regression equation also made it possible to calculate the  
predicted values: 4,552.8 thousand tons (optimistic forecast)  
and 5555.3 thousand tons of emissions (pessimistic  
forecast). We observe slight deviations of the results of two  
calculation methods - within 6%. The aforesaid allows us to  
assert that the constructed economic and mathematical  
model has passed verification.  
Emission of pollutants into atmosphere from  
stationary sources (Mining and quarrying)  
Polynomial trendline (Emission of pollutants into  
atmosphere from stationary sources (Mining and  
quarrying))  
(b) Optimistic forecast  
7
000  
500  
6
5
.3 Development of a Methodology for Assessing the  
Sustainable Development of the Oil and Gas Sector of the  
Russian Economy Based on an Integrated Approach to the  
Aggregation of Sustainable Development Components and  
Digital Factors  
6000  
-
y = 5851,1x  
0,114  
5500  
5000  
4500  
4000  
For building model, we selected indicators  
characterizing the  
3
components of sustainable  
4
616,2  
554,6  
development: environmental parameters, economic  
parameters, social parameters, as well as digitalization  
parameters. All variables were normalized by the formula  
4
(4). The results of determining the optimal number of factors  
are shown in table. 2. Thus, based on the Kaiser criterion, the  
optimal number of factors (two) was revealed with a total  
dispersion fraction of 87.68%. In this regard, as a result of  
factor analysis, 14 variables characterizing the economic,  
social, environmental and “digital” aspects are aggregated  
by two factors (Table 3). Factors are distinguished by the  
method of principal components, the Varimax raw rotation  
method is applied. Identified factors can be interpreted as  
Emission of pollutants into atmosphere from  
stationary sources (Mining and quarrying)  
Power trendline (Emission of pollutants into  
atmosphere from stationary sources (Mining and  
quarrying))  
1
follows. The first factor F - accounts for the largest share of  
the total variance - 56.3%.  
Figure 3: Scenarios for changing the environmental level of the oil  
and gas sector (built on the basis of data) [1]  
Table 1: Forecast indicators of emissions of harmful substances in general for mining (compiled by the authors)  
Period  
018  
В, thousands tons  
4851,4  
5361,7  
5875,3  
4616,2  
4554,6  
5555,3  
4552,8  
RFL, %  
2
0,66  
0,38  
0,53  
0,80  
0,78  
0,53  
0,78  
2
Pessimistic scenario for 2019 (polynomial trend line, R = 0.896)  
Pessimistic scenario for 2020 (polynomial trend line, R = 0.896)  
Optimistic scenario for 2019 (power trend line, R = 0.796)  
Optimistic scenario for 2020 (power trend line, R = 0.796)  
Pessimistic scenario: В2020 = 7729,36 – 4064,42* RFL  
Optimistic scenario : В2020 = 7729,36 – 4064,42* RFL  
2
2
2
6
43  
Journal of Environmental Treatment Techniques  
2020, Volume 8, Issue 2, Pages: 639-645  
This factor is characterized by capacity and covers the  
economic, social and environmental, and the characteristics  
of the integral component of the fourth industrial revolution  
- the digital one. The unity of approach distinguishes the  
author’s model from the capacious system of indicators  
developed by the UN Commission on Sustainable  
Development [26].  
1 2  
environmental aspect (variables x and x ), social (variables  
, x ) and digital (x , x10, x12, x13, x14). The second factor F  
is mainly microeconomic in nature, combining directly the  
economic indicators of the oil and gas sector (x , x , x ) and  
also the “digital” control factor (x and x11). It has been  
x
6
7
8
2
3
4
5
9
revealed that digitalization firmly permeates sustainable  
development, which is determined by the high correlation  
coefficients of “digital” variables with two distinguished  
factors.  
An assessment of the nature of the revealed  
dependencies allows us to state the negative impact of the  
6
Conclusion  
The study, which focuses on two main aspects -  
sustainable development and digitalization, reflects the  
characteristics of the Russian economy. It is revealed that  
monitoring the impact of the industrial complex on the  
environment is important in the framework of sustainable  
development. Digital technologies relevant for the modern  
economy are called upon to act as a catalyst for this process.  
Based on the processing of statistical data and the  
construction of a regression model, it is found that the  
environmental factor (level of air polluting substances) is  
highly dependent on the economic (asset turnover and  
financial leverage ratio of the Russian oil and gas sector). It  
is determined that increasing the financial leverage ratio due  
to more active attraction and use of borrowed capital  
contribute to the reduction of harmful emissions by  
industrial facilities. The model allows us to build optimistic  
and pessimistic forecasts of the impact of the oil and gas  
sector on the environment, which makes it possible to  
assume the need to strengthen monitoring and its  
digitalization in order to develop along an optimistic vector.  
In general, environmental indicators of the mining industry  
are characterized by positive trends: a decrease in pollutant  
emissions both in mining and in the sphere of extraction of  
crude oil and natural gas and an increase in neutralized  
pollutants and production and consumption wastes [8].  
The second aspect is digital transformation. As a result  
of factor analysis, 2 factors were selected that take into  
account “digital” variables. Both identified factors reflect the  
low-efficiency use of digital technologies in the activities of  
extractive organizations, including the oil and gas sector. At  
this stage of development in the industry, digital  
technologies do not yet provide a synergistic effect in  
consolidation with the implementation of the concept of  
sustainable development. This is also due to the fact that, in  
general, in the Russian economy, the field of information and  
communication technologies is in its infancy compared with  
developed countries [27].  
volume of polluting emissions x  
and communication technologies per 1 rub shipment x  
the socio-environmental factor F , which indicates an  
insufficiently efficient expenditure of investments of  
industrial enterprises in ICT. The economic factor F is  
inversely related to the intensity of automation of production  
and the intensity of use of broadband Internet x11. A  
1
and the cost of information  
8
on  
1
2
x
9
negative coefficient for two “digital” variables also indicates  
a low contribution of digitalization to revenue generation.  
According to the formula (1), the dependence of factors on  
1
the selected variables is formalized. Where F is a socio-  
environmental factor that takes into account the influence of  
digital technologies; F is an economic factor that takes into  
2
account the impact of digital technology. According to  
formula (2), a methodology for determining the integral  
index of sustainable development is presented:  
IУР  7,94 F  4,34 F  
1
2
Thus, the proposed model of the dependence of  
environmental factors of the oil and gas sector on economic  
ones suggested two alternative development scenarios: with  
an optimistic forecast, the level of emissions in 2020 is about  
4
,552.8 thousand tons, while a pessimistic one is 5555.3  
thousand tons. Note that by the end of 2020, in the first case,  
the financial leverage ratio rises to 0.78, in the second case  
it decreases to 0.53. Since the coefficient level equal to 1 is  
recognized as optimal, it is recommended that enterprises in  
the oil and gas sector in Russia review the capital structure  
and more actively attract and use borrowed capital. The  
resulting model of the integral index of sustainable  
development allows one to take into account the indicators  
of the three main components of sustainable development -  
F  0,81 x 0,93x 0,97 x 0,88 x 0,72 x 0,87 x 0,99 х 0,98 х 0,79 х ,  
14  
1
1
2
6
7
8
10  
12  
13  
F  0,72 х 0,93 х 0,87 х 0,75 х 0,92 х  
11  
2
3
4
5
9
Table 2: Eigenvalues of factors. Principal component analysis. (Compiled according to the Federal State Statistics Service, from:  
http://www.gks.ru)  
The proportion of  
factor in the total Accumulated eigenvalues  
variance  
Eigenvalues  
factors  
of  
Accumulated share in total  
variance  
Factors  
1
2
3
4
5
6
7
7,936833  
4,338182  
0,732858  
0,495654  
0,300075  
0,126886  
0,069512  
56,69167  
30,98702  
5,23470  
3,54038  
2,14339  
0,90633  
0,49652  
7,93683  
56,6917  
87,6787  
92,9134  
96,4538  
98,5972  
99,5035  
100,0000  
12,27502  
13,00787  
13,50353  
13,80360  
13,93049  
14,00000  
6
44  
Journal of Environmental Treatment Techniques  
2020, Volume 8, Issue 2, Pages: 639-645  
Table 3: Factor loads of variables for identified factors,  
taking into account the rotation of factors (compiled by the  
authors)  
Technical Conference Smart Energy Systems. (SES-2019),  
1
24;04013. 2019.  
[
13] Dyrdonova AN, Shinkevich AI, Galimulina FF, Malysheva  
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Variables  
Factor 1  
-0,811349  
0,932936  
-0,645732  
-0,185894  
0,330573  
0,968547  
0,880131  
-0,720691  
-0,498242  
0,872459  
0,029981  
0,985159  
0,982286  
0,785352  
7,884100  
0,563150  
Factor 2  
0,347441  
0,293899  
0,721626  
0,933407  
0,871915  
0,154488  
0,282310  
-0,157737  
-0,751370  
-0,399520  
-0,919811  
-0,111965  
-0,051886  
0,563645  
4,390916  
0,313637  
х
х
х
х
х
х
х
х
х
х
х
х
х
х
1
2
3
4
2
019;9(129): 55–70.  
5
[
15] Patin SA. Oil and the ecology of the continental shelf: in 2  
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of shelf hydrocarbon resources. Moscow: VNIRO Publishing  
House. 2017.  
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[
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10  
11  
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2
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Expl. Var  
Prp. Totl  
4
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Acknowledgments  
The research was carried out within the framework of the  
grant of the President of the Russian Federation for state  
support of leading scientific schools of the Russian  
Federation, project number NSH-2600.2020.6.  
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