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Article

Factors Enabling Access to Affordable, Reliable, Sustainable and Modern Energy in the European Union

by
Aldona Migała-Warchoł
1,*,
Bożydar Ziółkowski
1,
Agnieszka Lew
2,
Jolanta Stec-Rusiecka
1 and
Agata Warmińska
3
1
Department of Enterprise Management, Faculty of Management, Rzeszow University of Technology, 35-959 Rzeszow, Poland
2
Department of Economics, Faculty of Management, Rzeszow University of Technology, 35-959 Rzeszow, Poland
3
Department of Entrepreneurship, Management and Eco-Innovation, Faculty of Management, Rzeszow University of Technology, 35-959 Rzeszow, Poland
*
Author to whom correspondence should be addressed.
Energies 2025, 18(3), 722; https://doi.org/10.3390/en18030722
Submission received: 9 January 2025 / Revised: 28 January 2025 / Accepted: 1 February 2025 / Published: 4 February 2025
(This article belongs to the Section A: Sustainable Energy)
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Abstract

:
By 2050, Europe will become the first climate-neutral continent according to the vision of the European Union (EU). To tackle this challenge, the EU has scheduled the accomplishment of the 17 goals of the United Nations’s 2030 Agenda, with Goal 7 addressing the energy sector. The role of public policies is fundamental in this case; however, it is insufficient in some areas, e.g., when adopting green energy technologies. The purpose of this article is to identify the economic factors that are necessary to achieve Goal 7 of Agenda 2030. To realize the aim of this study and identify economic factors that are significant for implementing the targets of Goal 7 of the 2030 Agenda, two statistical methods were used: the Pearson linear correlation coefficient and linear regression modeling with a scatter plot to present the relationships. The results of this study confirm that in the EU, the possibility of achieving Goal 7 is dependent on the three economic determinants analyzed, i.e., GDP per capita, unemployment rate, and gross domestic spending on research and development. The analysis revealed that the impact of single economic factors on the realization of all SDG 7 targets is small because no economic factor correlates with even half of SDG 7 indicators.

1. Introduction

All domains of contemporary economies depend on energy so much that it is compared to the blood in the circulatory system. Access to energy was a breaking point for the development of the Industrial Age and caused a significant increase in energy consumption. As a result of industrialization, energy consumption grew faster “than the change in world population” [1]. For many decades, the benefits of energy production generated by burning fossil fuels (coal, gas, petroleum) and firewood coexisted along with such environmental aspects as, e.g., emissions of carbon dioxide (CO2), methane (CH4) nitrous oxide (N2O), industrial gases and steam. After the announcement of their harmful impact on the Earth’s atmosphere, resulting in the stimulation of the greenhouse effect, the emissions were blamed for climate change. Greenhouse gases are produced mainly by the energy sector; thus, “the climate problem is mostly an energy problem” [2]. This climate–energy nexus is in line with a plethora of reports on environmental and social changes regarding the energy industry, and the historical and current energy crises, e.g., oil shocks of the 1970s and during the COVID-19 pandemic [3,4] and Russia’s military aggression against Ukraine in 2022 [5], are highlighting the need to pursue the sustainable development idea faster than ever before. Sustainable energy development includes sustainable, safe and efficient energy supplies [6], although it is multi-faceted and dependent on the user’s perspective and the context in which it occurs [7]. The introduction of sustainable development scenarios needs revolutionary decisions to limit negative effects on the demand and supply sides [8]. In the case of the energy sector, this means transformation towards a “modern energy supply support system” [9], which guarantees “economic growth, social equity and environmental sustainability” [10]. The sustainability orientation is “inextricably linked to technological advancement” [11], particularly in the energy industry. Advanced technologies are enabling sustainable production processes [12] and circular business models [13,14]. In the case of the energy sector, the role of cutting-edge technologies in transforming industry became evident with the emergence of Industry 4.0, focused on digitalization [15,16], and subsequently the concept of Industry 5.0, concentrated on human well-being, sustainability and resilience [17,18].
Novel and emerging technologies, along with innovations, are fundamental for achieving the vision of Europe as the first climate-neutral continent by 2050 [19]. The “European Green Deal, Europe Fit for the Digital Age and an Economy that Works for People” [20] with policy initiatives devoted to the energy transformation in the EU, e.g., Fit for 55, Sustainable recovery, REPowerEU, Net Zero Industry Act, EU Taxonomy [21], aims at supporting this challenging vision. All aforementioned policy instruments, with the Green Deal especially, are integral parts of the “Commission’s strategy to implement the United Nation’s 2030 Agenda and the sustainable development goals” [19]. The opportunity to overcome the energy crisis when realizing the strategy is accompanied by the chance to improve the EU’s geopolitical position on the energy map. This regards the end-use of modern energy consumption per capita in the EU, which was below the Middle East, Japan and Korea, Eurasia and the United States, according to the ranking of the World Energy Outlook 2023 [21]. Some other issues, e.g., the instability of energy supplies, energy poverty and the lack of access to energy, have a chance to be resolved after the successful implementation of the 2030 Agenda for Sustainable Development. The 2030 Agenda sets out 17 goals, including Goal 7 “affordable & clean energy”, aimed at ensuring everyone has the right to sources of modern, sustainable energy services at an affordable price [22]. The presented context of the EU’s sustainable energy development and its relevance for the 2030 Agenda implementation should be supplemented by recent research on the importance of SDG 7 and its further implications for the EU. Achievement of this goal is critical to humans in the context of well-being, satisfying economic growth and mitigating climate changes [23]. In the EU, a strong synergy between renewable electricity consumption (which is the component of SDG 7) and the average electricity price was identified [24]. The assessment of the implementation of SDG 7 (quantified as a composite indicator) revealed a significant negative impact of the unemployment rate on the SDG 7 realization, whereas the rest of the analyzed economic variables were conducive [25].
However, when considering the existing problems, e.g., the insufficiency of public policies in driving the adoption of green energy technologies [26,27,28,29], the lack of detailed indicators and analyses and also deficit of “new tools to support the monitoring of progress in implementing the sustainable development strategy” [30], research on determinants of the sustainable transformation in the energy sector is justified. Moreover, the numerous approaches in this field pertain to SDG 7 as one composite indicator instead of its single targets. The knowledge gap on economic factors affecting energy transformation in the context of the targets of SDG 7 is the research problem scrutinized in this paper. Four economic factors influencing access to affordable, reliable, sustainable and modern energy in the European Union are addressed in this study. The lack of knowledge on the real impact of economic factors on single targets of the SDG 7 hinders the development of effective policies in the European Union regarding the energy transition strategy. The identification of statistically significant factors is important for constituting a set of reliable economic indicators both for monitoring progress in implementing the aforementioned strategy and cultivating effective plans by the European Union’s decision-makers. When fulfilling this research gap, the policy instruments can be better oriented on SDG 7 targets.
The examined research question is as follows: Which economic factors can significantly affect targets in Sustainable Development Goal 7 (SDG 7: ensure access to affordable, reliable, sustainable and modern energy for all)? This study aims to identify factors that are significant for implementing single targets of Goal 7 in the 2030 Agenda. This paper investigates the relationship between economic indicators and the success of implementing SDG 7 in the European Union. To this end, the following research hypotheses have been formulated:
H1. 
There is a statistically significant relationship between the GDP per capita and the realization of SDG 7.
H2. 
There is a statistically significant relationship between the unemployment rate and the realization of SDG 7.
H3. 
There is a statistically significant relationship between the government consolidated gross debt and the realization of SDG 7.
H4. 
There is a statistically significant relationship between the gross domestic expenditure on research and development and the realization of SDG 7.
To verify the hypotheses, the statistical significance of the relationship between selected economic factors and SDG 7 indicators was calculated.
The unique value of this research is the identification of the economic factors that significantly affect SDG 7 targets in the EU.
The next subsections of this article summarize the sustainable development idea and Goal 7 of the 2030 Agenda. The second section of this article is devoted to the applied methods, research model, and data. Finally, the research results and extensive discussion are presented.

1.1. The Phenomenon of Sustainable Development

Sustainability, used often interchangeably today with the term “sustainable development”, stems from the care about the source of energy and construction material, i.e., timber. The first notion of sustainability in Europe dates back to the year 1713, when Hans Carl von Carlowitz, the manager of the mining industry in Saxony (Germany), published the idea of sustainable wood production in his book. To resolve the wood shortage problem faced by the mining industry (consuming “enormous quantities of charcoal, firewood and construction timber”) [31] this critical and experienced practitioner, personally responsible for the wood supply chains, introduced the framework for forest management based on the concept of “sustained use” in his treatise [31]. H. C. von Carlowitz observed the dependence between the long-term consequences of short-term thinking motivated by quick profits. To prevent the severe economic, environmental and social effects of forest degradation in the times of mercantilism, Carlowitz’s understanding of sustainability assumed cutting down only as many trees as new ones can grow, i.e., rebuild in that place at the same time [32,33]. When avoiding forestry risk factors aligned with economic growth i.e., profit maximization in a short period and overconsumption, the first idea of sustainability aimed at satisfying the economic and social needs on the path of sustainable but not balanced development [34] in the forest sector.
The universal nature of the sustainable development idea and the necessity of its implementation were raised internationally in the year 1987 for the first time by the Brundtland Commission [35]. According to its Report, sustainable development is a development model “that meets the needs of the present without compromising the ability of future generations to meet their own needs” [36]. The essence of this approach is understood often as “reducing the range of poverty and social exclusion, providing future generations with conditions of development at least as good as the current ones and preserving cultural diversity” [37,38]. One of the first and most prevailing interpretations of that notion is called “three-legged stool” [39] because it enumerates three dimensions of sustainable development: social, economic and ecological/environmental. In the next few years, the dimensions were supplemented by technical and institutional–political areas as well as spatial ones [37,40,41,42]. Another model of sustainable development defines it as a result of interaction among four factors, i.e., demography, technology, values and government [38,43]. Further distinctions regarding this concept may result from covering various areas, e.g., demography, health care, education, culture, food and safety [44]. The multitude of definitions and misconceptions of sustainable development [45,46,47] decreased understanding and caused difficulties in communicating this concept not only among academics but also the business sector, which described this concept as “continuous improvement”, “social and environmental responsibility” or “excellence” [39].
Since the international conference “Earth Summit” by the United Nations in the year 1992, the contemporary idea of sustainable development gained global acceptance. The impetus for implementing this phenomenon started, however, in the last decade, in the year 2015, when the 2030 Agenda, i.e., the United Nations Resolution “Transforming our world: the 2030 Agenda for Sustainable Development”, was published. The countries accepting this document (including all from the European Union) also declared a reduction in their negative impact on the environment [48]. From the beginning, energy matters attracted the highest attention of decision-makers, because energy is treated as the “golden thread” connecting “economic growth, social equity and environmental sustainability” [10]; thus, it has a priority role in national policies.

1.2. Energy Sector in the 2030 Agenda for Sustainable Development

1.2.1. Building Blocks

Among 17 Sustainable Development Goals (SDGs) of the 2030 Agenda, there are 169 targets designed. The goals are classified into five groups of factors, i.e., planet, people, prosperity, peace, and partnership. Energy issues are acknowledged by the 2030 Agenda in the Sustainable Development Goal 7 (SDG 7): ensure access to affordable, reliable, sustainable and modern energy for all. The aforementioned goal comprises three groups of targets related to energy access, energy efficiency and sustainable energy.
Access to energy is deemed as the critical factor for establishing SDGs [49]. According to some prognoses, the incorporation of the 2030 Agenda will require increasing energy consumption and urge all engaged countries to adapt their national energy plans [50]. In clean energy considerations, the word “reliable” is worth defining. According to one definition, reliable is “one that can always be relied on” or “functioning well” [51]. Another definition presents reliability as “suitable or fit to be relied on; worthy of dependence or reliance or trust” [52], which in energy considerations provides the answer that reliable energy is that which is always and under all conditions available to anyone and at any time. “To be meaningful for households, productive enterprises, and community facilities, the energy supply supporting that access must have several attributes: it must be adequate in quantity, available when needed, of good quality, reliable, convenient, affordable, legal, healthy, and safe” [53]. A reliable energy supply is one that (in line with sustainable development) pays attention to the safety associated with clean energy production (such as fires or air pollution). “The economic perspective recognizes the importance of a reliable and available energy supply that is needed to secure economic growth” [54]. Obtaining reliable energy along with economic growth is also a challenge. “It is really difficult to keep the economic and industrial increase parallel with the consequence of SDG-7” [55].
Although energy is an essential element of economic development, a vast population does not have access to energy sources or experiences instability related to its supplies [56], including European countries. The problem remains valid for the reported 760 million individuals worldwide who still lack access to electricity in 2022 [57]. SDG 7 aims to solve this question by providing affordable and clean energy instead of focusing on the country’s competitiveness and energy “as a core production/input resource” [58]. Policy support, including a variety of incentives and creating an environment that promotes innovation, is essential for companies to deliver affordable clean energy to consumers [59]. Improving access to affordable energy is possible both by increasing energy supply and energy efficiency [60]. International organizations, including the World Bank, recognize energy efficiency “as one of the three pillars for ending energy poverty and securing access to affordable, reliable, and sustainable energy” [61]. The better achievements in energy efficiency, the better access to energy required for sustainable development [62].
The next component of the SDG 7 is sustainable and modern energy. Industry practitioners use the terms sustainable energy and renewable energy interchangeably [63] despite sustainable energy being a broader concept, and some renewable energy sources can be assessed as unsustainable [64]. The term modern energy can relate to the centralized energy system which is controlled by “states, and national or multinational energy companies” [65]. Access to modern energy services (mechanical power or electricity) includes, e.g., “electricity for cooking, lighting, or income generation” [8] but also heating and cooling houses [39]. The possibility of using affordable, renewable energy sources is increasing with the development of modern technologies, including artificial intelligence [66] and “alternative energy supply technologies to mitigate energy poverty” [67]. Renewable energy is essential in sustainable energy development strategies [68], the success of which depends on energy policy options, ensuring adjustment to the changing circumstances [69]. To fulfill the ambition of the 2030 Agenda, the governments of less and “least developed countries need to mobilize enormous investments in a short amount of time” [70] to elaborate “measures to regulate, stimulate and attract investments into the development of renewable sources and energy-efficient technologies” [71].
The change in consumption of sustainable energy, i.e., access to sustainable energy, is correlated with the change in resource conservation. Thus, energy supports sustainable development and responsibility for climate neutrality and is no longer contributing “to economic growth at the expense of the environment” [72]. As a result of increasing the share of renewable energy in gross final energy consumption, SDG 7 is achieved. Renewable energy resources and energy demand differ from country to country, and therefore, the analysis needs to be undertaken on a case-by-case basis [73]. In the analytical process, however, the problems when assessing SDGs implementation should be considered [74] considering both the national discrepancies and the coverage of various issues by 17 SDGs “which are arduous to define and quantify” [75]. Because of the betterment of global monitoring techniques and the availability of databases on single aspects of sustainability, the current potential in diagnosing the European and global progress in this area is larger than ever.
The Sustainable Development Goals are treated as “integrated and indivisible”. However, to adequately shape energy policy, it is necessary to look at the SDGs holistically, looking for the interactions that occur between SDG 7 and other goals. This will allow for better alignment of support and elimination of side effects of SDG 7 implementation [76]. For understanding the role of single components in SDG 7, reviewing its measures can be supportive.

1.2.2. Driving Factors in SDG 7

The achievements in SDG 7 are measured by a specific set of indicators adopted by the United Nations. Their attribution to single SDG 7 targets is presented in Table 1.
As a complement to the official SDG indicators, the Sustainable Development Goal Index (SDG Index) was created to measure countries’ progress in achieving SDGs. When designing public policies, the knowledge of factors influencing the SDG indicators is indispensable. A general overview of research on conditions attributed to the SDG 7 targets is presented in Table 2.
The landscape of the energy sector is currently shaped by digitalization and “shifted from intensification to rational and effective use by spreading clean energy, renewable resources, smart technologies” [111]. All countries have formulated relevant energy targets, e.g., for the share of renewable energies in total energy consumption [112]. However, some of the policy instruments do not lead to progress, as with renewable energy in the US states and the EU, analyzed between 1990 and 2008 [113]. The factors depicted as significant for development of the renewable energy were “tender, tax, and feed-in tariffs, while the quota had no significant effect” [113]. Among other determinants of sustainable energy development that have been scrutinized so far are green self-identity, knowledge, perceived privacy risks, perceived value, perceived well-being, social influence, comfort sensation, household composition, electricity consumption, economic factors, culture factors and effort [26]. Further studies of SDG accomplishments should highlight the synergy and trade-off areas [75] both in sectoral and spatial aspects.

2. Materials and Methods

This research follows the above appeals on highlighting sectoral and spatial synergy related to SDGs. To realize the aim of this study and identify economic factors that are significant for implementing Goal 7 of the 2030 Agenda, two statistical methods were used: the Pearson linear correlation coefficient that shows the relationship between the analyzed variables and linear regression modeling with a scatter plot to present the relationship graphically on a chart. The analyzed variables for SDG 7 were extracted from the Eurostat databases for years from 2004 until 2022 for all European Union countries and included the following:
  • Final energy consumption in households per capita;
  • Population unable to keep their homes adequately warm by poverty status;
  • The share of renewable energy in gross final energy consumption;
  • Primary energy consumption;
  • Final energy consumption;
  • Energy productivity;
  • Energy import dependency by product.
The group of the factors analyzed according to their relationships to the aforementioned variables embraced the following economic indicators:
  • GDP per capita;
  • Unemployment rate;
  • Government consolidated gross debt;
  • Gross domestic expenditure on research and development.
This research aimed to verify four research hypotheses regarding the relations between economic factors and indicators of SDG 7.
The research model with formulated hypotheses is presented in Figure 1.
To verify the research hypotheses, the statistical hypotheses were tested. The calculated models of regression functions provide estimates of marginal effects for each of the variables used in this research as well as the model fit statistics. The marginal effects reveal the expected magnitudes of change in the dependent variable associated with one unit increase in the value of each independent variable. The model fit statistics allow us to assess which of the factors has the greatest individual ability to predict the dependent variables described in this research. If existing differences across countries have any influence on the dependent variable, then fixed-effects models should not be used, but random-effects models are the most appropriate. The models that were used for this analysis were random-effects models. This research aimed to verify four research hypotheses regarding the relations between economic factors and indicators of SDG 7. If the goal is to measure relationships between variables, quantitative methods such as Pearson correlation coefficient and linear regression models can be used.

3. Results

The research process of discovering the statistical significance of relationships between analyzed factors started from descriptive analyses. Table 3 presents descriptive statistics for the European Union countries including such variables as final energy consumption in households per person, population unable to keep their homes adequately warm by poverty status, share of renewable energy in gross final energy consumption, primary energy consumption, final energy consumption, energy productivity, energy import dependency by products, GDP per capita, unemployment rate, government consolidated gross debt and gross domestic expenditure on research and development. The coefficient of variation for all variables is above 20%, and therefore, all variables can be included for further analysis. The asymmetry coefficient for only one variable is negative (for energy import dependency by products), which means that statistical observations for this variable are concentrated at feature values greater than the arithmetic mean. For the remaining variables, statistical observations for these variables are concentrated at feature values smaller than the arithmetic mean.
Table 4 presents the Pearson linear correlation coefficients between the variables reported by Eurostat regarding Goal 7 of the 2030 Agenda and analyzed economic variables, i.e., GDP per capita, unemployment rate, government consolidated gross debt and gross domestic expenditure on research and development. Correlation coefficient values are underlined and show statistically significant values. Six such values were obtained. For the statistically significant values of the correlation coefficients, the regression functions are additionally shown in Figure 2, Figure 3, Figure 4, Figure 5, Figure 6 and Figure 7.
The confirmation of H1 can be found in Table 4: there is a statistically significant relationship between GDP per capita and the achievement of SDG 7. The mediating power of GDP per capita was observed for two SDG 7 variables, i.e., the population unable to maintain adequate heat at home due to poverty status (r = −0.40) and energy productivity (r = 0.83).
The statistical relationship between energy productivity and GDP per capita is shown in Figure 2. The mediating power of GDP per capita was observed towards two SDG 7 variables, i.e., population unable to keep their homes adequately warm by poverty status (r = −0.40) and energy productivity (r = 0.83). The unemployment rate revealed its interplay with one SDG 7 variable, i.e., population unable to keep their homes adequately warm by poverty status (r = 0.46). Gross domestic expenditure on research and development correlates with three SDG 7 variables, i.e., final energy consumption in households per capita (r = 0.59), population unable to keep their homes adequately warm by poverty status (r = −0.50) and share of renewable energy in gross final energy consumption (r = 0.42).
The analyses revealed that the population unable to keep their homes adequately warm by poverty status depends statistically significantly on GDP per capita in the EU countries. It is presented in Figure 2 as a scatter plot, which visually represents and evaluates the relationship between two continuous variables. A scatter plot shows individual data points in a two-dimensional coordinate system. Each point refers to the variables GDP per capita and population unable to keep their homes adequately warm by poverty status for all EU countries. The X-axis represents the independent variable, GDP per capita; the Y-axis represents the dependent variable, population unable to keep their homes adequately warm by poverty status. Each point in the scatter plot corresponds to a specific EU country, and its coordinates are determined by the values of two variables. The analysis showed a moderate negative relationship for all EU countries. When highlighting extremes, it is worth noticing that Bulgaria has the highest percentage of population unable to keep their homes adequately warm by poverty status, and Finland the lowest one.
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Figure 2. Scatter chart for the relationship between GDP per capita and population unable to keep their homes adequately warm by poverty status. Note: country names in blue boxes are made by the Statistica software and are not significant for the interpretation of the results. Source: authors’ calculations.
Figure 2. Scatter chart for the relationship between GDP per capita and population unable to keep their homes adequately warm by poverty status. Note: country names in blue boxes are made by the Statistica software and are not significant for the interpretation of the results. Source: authors’ calculations.
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The analyses also showed that the population unable to keep their homes adequately warm due to poverty statistically significantly depends on GDP per capita in EU countries. This is presented in Figure 3 as a scatter plot, which visually presents and assesses the relationship between two continuous variables. The scatter plot shows individual data points in a two-dimensional coordinate system. Each point refers to the variables GDP per capita and population unable to keep their homes adequately warm by poverty for all EU countries. The X-axis shows the independent variable, GDP per capita; the Y-axis shows the dependent variable, population unable to keep their homes adequately warm due to poverty. Each point in the scatter plot corresponds to a specific EU country, and its coordinates are defined by the values of two variables. The analysis shows a moderate negative relationship for all EU countries. Highlighting the extremes, it is worth noting that Bulgaria has the highest percentage of the population that is unable to maintain adequate heat at home due to poverty status, and Finland has the lowest.
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Figure 3. Scatter chart for the relationship between GDP per capita and energy productivity. Note: country names in blue boxes are made by the Statistica software and are not significant for the interpretation of the results. Source: authors’ calculations.
Figure 3. Scatter chart for the relationship between GDP per capita and energy productivity. Note: country names in blue boxes are made by the Statistica software and are not significant for the interpretation of the results. Source: authors’ calculations.
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Hypothesis 2, as shown in Table 4, was confirmed in one variable: the unemployment rate revealed its correlation with one SDG 7 variable, i.e., the population unable to maintain adequate heat at home due to poverty status (r = 0.46).
The analysis also proved that the population that is unable to adequately heat their homes by poverty status in EU countries depends significantly on the unemployment rate. There is a statistically significant, moderately positive relationship (r = 0.46) for all EU countries. Figure 4 is a scatter plot of the unemployment rate and the population unable to heat a home depending on poverty status. The chart shows individual data points in a two-dimensional coordinate system. On the X-axis is displayed the independent variable, the unemployment rate; the Y-axis shows the dependent variable, the population that is unable to adequately heat their homes by poverty. There is a positive correlation because the scores increase together from left to right. It is worth paying attention to outliers such as Bulgaria and Cyprus, which have the highest percentage of households experiencing difficulties in heating their homes. In Bulgaria, nearly a quarter of the population struggles with a lack of access to the necessary energy due to poverty despite relatively low unemployment. It can be concluded that energy in this country is simply too expensive for many citizens, possibly because of the capital-intensive nature of its production. In Lithuania, Cyprus, Greece, Spain, Portugal and Romania, approximately one-fifth of the population has difficulty accessing energy. The biggest problems are in Greece and Spain, which face not only high energy poverty but also high unemployment rates, potentially causing a spiraling problem. The lowest rates of exclusion due to unemployment are found in Scandinavian countries and the Benelux.
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Figure 4. Scatter chart for the relationship between the unemployment rate and the population unable to keep their homes adequately warm by poverty status. Note: country names in blue boxes are made by the Statistica software and are not significant for the interpretation of the results. Source: authors’ calculations.
Figure 4. Scatter chart for the relationship between the unemployment rate and the population unable to keep their homes adequately warm by poverty status. Note: country names in blue boxes are made by the Statistica software and are not significant for the interpretation of the results. Source: authors’ calculations.
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Hypothesis 4 was also confirmed: gross domestic expenditure on research and development correlates with three SDG 7 variables, i.e., final energy consumption in households per capita (r = 0.59), population unable to keep their homes adequately warm by poverty status (r = −0.50) and share of renewable energy in gross final energy consumption (r = 0.42).
In the case of the government consolidated gross debt, no statistically significant relationship was obtained in comparison to the analyzed variables from Goal 7 of the 2030 Agenda.
There is a statistically significant, moderate positive relationship (r = 0.59) for all EU countries regarding the gross domestic expenditure on research and development and final energy consumption in households per capita. Figure 5 shows individual data points in a two-dimensional coordinate system. On the X-axis is shown the independent variable, the gross domestic expenditure on research and development, and the Y-axis shows the dependent variable, final energy consumption in households per capita. There is a positive correlation because the scores increase together from left to right. It is worth paying attention to outliers such as Finland, which has the highest value of final energy consumption in households per capita.
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Figure 5. Scatter chart for relationship between gross domestic expenditure on research and development and final energy consumption in households per capita. Note: country names in blue boxes are made by the Statistica software and are not significant for the interpretation of the results. Source: authors’ calculations.
Figure 5. Scatter chart for relationship between gross domestic expenditure on research and development and final energy consumption in households per capita. Note: country names in blue boxes are made by the Statistica software and are not significant for the interpretation of the results. Source: authors’ calculations.
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Between the gross domestic expenditure on research and development and the population unable to keep their homes adequately warm by poverty status, there is also a statistically significant, moderate negative relationship for all EU countries (r = −0.51). Figure 6 shows the independent variable, the gross domestic expenditure on research and development, on the X-axis and the dependent variable, the population unable to keep their homes adequately warm by poverty status, on the Y-axis. There is a negative correlation because the scores decrease together from left to right. It is worth paying attention to outliers such as Bulgaria, Romania and Cyprus, which have the highest percentage of the population unable to keep their homes adequately warm by poverty status.
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Figure 6. Scatter chart for the relationship between gross domestic expenditure on research and development and population unable to keep their homes adequately warm by poverty status. Source: authors’ calculations.
Figure 6. Scatter chart for the relationship between gross domestic expenditure on research and development and population unable to keep their homes adequately warm by poverty status. Source: authors’ calculations.
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In the case of the gross domestic expenditure on research and development and the share of renewable energy in gross final energy consumption, a statistically significant, moderate positive (r = 0.42) relationship for all EU countries was achieved. Figure 7 shows the independent variable, the gross domestic expenditure on research and development, on the X-axis and the dependent variable, the share of renewable energy in gross final energy consumption, the Y-axis. There is a positive correlation because the scores increase together from left to right. The outlier Sweden has the highest value of the share of renewable energy in gross final energy consumption.
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Figure 7. Scatter chart for the relationship between gross domestic expenditure on research and development and the share of renewable energy in gross final energy consumption. Note: country names in blue boxes are made by the Statistica software and are not significant for the interpretation of the results. Source: authors’ calculations.
Figure 7. Scatter chart for the relationship between gross domestic expenditure on research and development and the share of renewable energy in gross final energy consumption. Note: country names in blue boxes are made by the Statistica software and are not significant for the interpretation of the results. Source: authors’ calculations.
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The summary of results after testing the analyzed relationships (Table 5) is a basis for assessing the planned hypothesis. A statistically significant relationship occurs for the following pair of variables: final energy consumption in households per capita and gross domestic expenditure on research and development. For the population unable to keep their homes adequately warm by poverty status indicator, a relationship was obtained with three variables: GDP per capita, unemployment rate and gross domestic expenditure on research and development. A statistically significant relationship was also revealed between the share of renewable energy in gross final energy consumption and the gross domestic expenditure on research and development. The last statistically significant relationship was observed for the following pair of variables: energy productivity and GDP per capita.

4. Discussion

The performed calculations delivered statistical evidence for accepting three of four research hypotheses. Only Hypothesis H3 on the statistically significant relationship between the government consolidated gross debt and SDG 7 targets was not proved. The most enabling factor regarding access to affordable, reliable, sustainable and modern energy in the European Union was gross domestic expenditure on research and development. Its mediating effect occurred concerning the following three SDG 7 variables: final energy consumption in households per capita, population unable to keep their homes adequately warm by poverty status, share of renewable energy in gross final energy consumption. In turn, the second most enabling factor is GDP per capita. It determines the realization of two targets of SDG 7 which are described by the following indicators: population unable to keep their homes adequately warm by poverty status, energy productivity. The third economic indicator, i.e., unemployment rate, has a significant interplay with the population unable to keep their homes adequately warm by poverty status (r = 0.46). This means that along with the growing unemployment rate in the EU, the population unable to keep their homes adequately warm will also increase. Nevertheless, it is worth noticing that no economic factor influenced half or more of the indicators within SDG 7. Thus, the scale of influence of every single economic factor on the realization of SDG 7 (composed of seven indicators) can be assessed as small.
This research allowed us to answer the question of the significance of the relationship between economic factors and the realization of SDG 7. According to the aim of this study, the factors significantly affecting the energy transformation in the EU were identified. The factors enable access to affordable, reliable, sustainable and modern energy in the European Union just in selected areas of SDG 7. Remarkably, none of the analyzed economic factors were statistically significant for supporting three SDG 7 indicators, i.e., primary energy consumption, final energy consumption, energy import dependency by products.
Among the SDG 7 variables, only the population unable to keep their homes adequately warm by poverty status is prone to the influence of three economic factors. The fight against energy poverty, ensuring adequate energy conditions for all citizens, requires cooperation at both the national and international levels. Based on the research and literature analysis, the following recommendations for actions to improve security in countries with the highest energy poverty status can be made:
  • National level:
    • Increase or introduce subsidies to help cover high heating costs;
    • Create jobs, especially in sectors with low barriers to entry;
    • Increase investment in education programs to develop professional skills and employability;
    • Provide education on the benefits of energy efficiency and conservation;
    • Increase funding for R&D to improve the efficiency, reliability and scalability of renewable energy technologies (including storage solutions and smart grids);
    • Monitor and regulate energy prices to increase energy availability.
  • International level:
    • Share technologies, best practices and financial resources regarding energy and climate challenges and supporting international agreements (such as, e.g., the Paris Agreement);
    • Increase the structural funds for investment projects aimed at the modernization of heating systems in residential buildings;
    • Support the joint activities of the European Union member states to combat energy poverty.
The results and recommendations are especially relevant in the context of the European Green Deal deemed as Europe’s growth strategy which “is a form of a roadmap showing the way to a sustainable economy in Europe” [114]. Considering the European Green Deal 2.0 and its further versions, the knowledge of the mediating effect of economic factors can shape new regulatory mechanisms, e.g., sustainable investments, green transition, reduction of greenhouse gas emissions, renewable energy and mobility infrastructure.

5. Conclusions

Adaptation to sustainable development is a necessity when considering the future of life on our planet. Ensuring “access to affordable, reliable, sustainable, and modern energy for all” [77] becomes one of the primary challenges of modern times. To meet the expectations set in the 2030 Agenda, it is essential to remember that achieving these goals requires cooperation between governments, businesses, a civically engaged society and scientists. Monitoring whether changes are occurring is a crucial question, and it is important to determine their pace and dependencies. Access to clean and affordable energy is also pressing in the European Union. Research is responding to those trends and faces a need to perform “more detailed analyses and new tools to support monitoring progress in implementing the sustainable development strategy” since the currently applied “indicators are too general or too unified” [30].
Earlier studies by, e.g., Stern [115], related to economic growth and energy consumption emphasized the relationship between energy and GDP, which seems understandable because when there is higher economic production, there is also a higher energy demand. In contrast, the research by Drago et al. [116] points to the huge role of national policy in driving the introduction of renewable energy, which was also observed in the conducted research. In the case of energy poverty, similar conclusions were reached by Bouzarovski and Petrova [117], who also emphasized the economic and political dimensions of energy poverty.
In this analysis, economic variables are examined to pinpoint factors that facilitate access to affordable, reliable, sustainable, and modern energy in the European Union. After calculating statistical correlations between all SDG 7 targets of the 2030 Agenda and four selected economic indicators, as well as verification of research hypotheses, the research goal was realized. In the EU, the significance of the implementation of Goal 7 is focused on three analyzed economic determinants i.e., GDP per capita, unemployment rate, gross domestic expenditure on research and development. Only hypothesis H3 could not be accepted, because there is no statistically significant relationship between the government consolidated gross debt and the realization of SDG 7. The mediating role of single economic indicators was observed towards the following SDG 7 variables:
  • GDP per capita towards population unable to keep their homes adequately warm by poverty status (r = −0.40) and energy productivity (r = 0.83).
  • Unemployment rate towards population unable to keep their homes adequately warm by poverty status (r = 0.46).
  • Gross domestic expenditure on research and development towards final energy consumption in households per capita (r = 0.59), population unable to keep their homes adequately warm by poverty status (r = −0.50) and share of renewable energy in gross final energy consumption (r = 0.42).
The analysis revealed that the scale of impact of single economic factors on realizing all SDG 7 targets is small because no economic factor correlates with even half of the SDG 7 indicators.
From the data, contained in the graphs, one can see correlations related to economic differences in access to cheap and clean energy. It is not surprising that mostly high-income countries show more advanced energy infrastructure and easier access to it. For lower-income countries, there are barriers related to the availability of cheap energy. It is also noteworthy that upward trends related to the use of renewable energy are emerging in all countries, and this is a positive aspect of the activities of national economies. Countries like Sweden exemplify the synergy between economic stability and proactive clean energy policies. The analysis also shows a significant relationship between energy poverty and unemployment/GDP per capita, which makes it possible to show the interconnectedness and interdependence associated with economic hardship and access to energy.
Future research directions could focus on linking economic factors to social or environmental factors related to SDG 7. It would be worthwhile to examine how education, cultural attitudes or campaigns promoting civic engagement for clean energy could influence energy consumption patterns and renewable energy use. It would also be worth examining the impact of geographical factors or regional differences within countries on the development of renewable energy infrastructure.
The presented results address the research gap related to implementing the tasks stated in the 2030 Agenda for Sustainable Development and can be helpful for scientists to deepen and expand research in this area. This research supports also the UN’s appeal to ‘leave no one behind’ [118] when achieving the 2030 Agenda. For this reason, the discussed results should be pertinent to developing challenges for better public management and creating policies promoting affordable, reliable, sustainable and modern energy in the selected countries of the European Union. This is especially relevant when developing priorities for the European Green Deal and its regulatory mechanisms dedicated to green transition and sustainable investments. Further research encouraged by the presented results should fill a research gap regarding the interplay between social factors and SDG 7. A similar analysis could embrace other Sustainable Development Goals of the 2030 Agenda.

Author Contributions

Conceptualization, A.M.-W., B.Z. and J.S.-R.; methodology, A.M.-W.; software, A.M.-W., B.Z. and J.S.-R.; validation, B.Z.; formal analysis, A.M.-W.; investigation, A.M.-W.; resources, B.Z., A.L., J.S.-R. and A.W.; data curation, A.M.-W.; writing—original draft preparation, A.M.-W., B.Z., A.L., J.S.-R. and A.W.; writing—review and editing, A.M.-W., B.Z. and J.S.-R.; visualization, B.Z.; supervision, A.M.-W.; project administration, J.S.-R.; funding acquisition, J.S.-R. and A.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Analyzed data were obtained from Eurostat databases: https://ec.europa.eu/eurostat/web/main/data/database.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Müller-Steinhagen, H.; Nitsch, J. The Contribution of Renewable Energies to a Sustainable Energy Economy. Process Saf. Environ. Prot. 2005, 83, 285–297. [Google Scholar] [CrossRef]
  2. MacKay, D.J. Sustainable Energy—Without the Hot Air; UIT: Cambridge, UK, 2009. [Google Scholar] [CrossRef]
  3. Bourghelle, D.; Jawadi, F.; Rozin, P. Oil Price Volatility in the Context of COVID-19. Int. Econ. 2021, 167, 39–49. [Google Scholar] [CrossRef]
  4. Šebo, J.; Prester, J.; Šebová, M. The Role of Environmental Management Systems and Energy Management Systems in the Adoption of Energy Recuperation Technologies in Central European Manufacturing Companies. Sustainability 2023, 15, 16913. [Google Scholar] [CrossRef]
  5. European Commission EU Action to Address the Energy Crisis. Available online: https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/european-green-deal/eu-action-address-energy-crisis_en (accessed on 4 June 2024).
  6. Graczyk, A. Wskaźniki Zrównoważonego Rozwoju Energetyki. Optim. Stud. Ekon. 2017, 4, 53–68. [Google Scholar] [CrossRef]
  7. Cherp, A.; Jewell, J. The Concept of Energy Security: Beyond the Four As. Energy Policy 2014, 75, 415–421. [Google Scholar] [CrossRef]
  8. Gunnarsdottir, I.; Davidsdottir, B.; Worrell, E.; Sigurgeirsdottir, S. Sustainable Energy Development: History of the Concept and Emerging Themes. Renew. Sustain. Energy Rev. 2021, 141, 110770. [Google Scholar] [CrossRef]
  9. Liu, J.; Niu, D.; Song, X. The Energy Supply and Demand Pattern of China: A Review of Evolution and Sustainable Development. Renew. Sustain. Energy Rev. 2013, 25, 220–228. [Google Scholar] [CrossRef]
  10. Jeuland, M.; Fetter, T.R.; Li, Y.; Pattanayak, S.K.; Usmani, F.; Bluffstone, R.A.; Chávez, C.; Girardeau, H.; Hassen, S.; Jagger, P.; et al. Is Energy the Golden Thread? A Systematic Review of the Impacts of Modern and Traditional Energy Use in Low- and Middle-Income Countries. Renew. Sustain. Energy Rev. 2021, 135, 110406. [Google Scholar] [CrossRef]
  11. Kunecová, J.; Bikfalvi, A.; Marques, P. Sustainability Orientation, Industrial Big Data and Product Innovation: Evidence from the European Manufacturing Sector. Comput. Ind. Eng. 2024, 191, 110163. [Google Scholar] [CrossRef]
  12. Šebo, J.; Šebová, M.; Palčič, I. Implementation of Circular Economy Technologies: An Empirical Study of Slovak and Slovenian Manufacturing Companies. Sustainability 2021, 13, 12518. [Google Scholar] [CrossRef]
  13. Prester, J.; Bikfalvi, A.; Palčič, I. The Effect of Product Complexity on Servitization and Deservitization: A Multi-Country Quantitative Analysis. Sustainability 2022, 14, 11885. [Google Scholar] [CrossRef]
  14. Vilkas, M.; Bikfalvi, A.; Rauleckas, R.; Marcinkevicius, G. The Interplay between Product Innovation and Servitization: The Mediating Role of Digitalization. J. Bus. Ind. Mark. 2022, 37, 2169–2184. [Google Scholar] [CrossRef]
  15. Heilala, J.; Salminen, A.; Bessa, W.M.; Kantola, J. Optimizing Smart Factories: A Data-Driven Approach. Glob. J. Res. Eng. 2023, 23, 15–30. [Google Scholar] [CrossRef]
  16. Koh, L.; Orzes, G.; Jia, F. (Jeff) The Fourth Industrial Revolution (Industry 4.0): Technologies Disruption on Operations and Supply Chain Management. Int. J. Oper. Prod. Manag. 2019, 39, 817–828. [Google Scholar] [CrossRef]
  17. Golovianko, M.; Terziyan, V.; Branytskyi, V.; Malyk, D. Industry 4.0 vs. Industry 5.0: Co-Existence, Transition, or a Hybrid. Procedia Comput. Sci. 2023, 217, 102–113. [Google Scholar] [CrossRef]
  18. Lerch, C.M.; Heimberger, H.; Jäger, A.; Horvat, D.; Schultmann, F. AI-Readiness and Production Resilience: Empirical Evidence from German Manufacturing in Times of the Covid-19 Pandemic. Int. J. Prod. Res. 2024, 62, 5378–5399. [Google Scholar] [CrossRef]
  19. European Commission. The European Green Deal. Available online: https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/european-green-deal_en (accessed on 4 June 2024).
  20. European Commission; Breque, M.; De Nul, L.; Petridis, A. Industry 5.0–Towards a Sustainable, Human-Centric and Resilient European Industry; Publications Office of the European Union: Luxembourg, 2021. [Google Scholar]
  21. IEA. World Energy Outlook 2023; IEA: Paris, France, 2023.
  22. Reddy, S.; Kvangraven, I.H. Global Development Goals: If at All, Why, When and How? 2015. Available online: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2666321 (accessed on 16 September 2024).
  23. Firoiu, D.; Ionescu, G.H.; Pîrvu, R.; Cismaș, L.M.; Tudor, S.; Patrichi, I.C. Dynamics of Implementation of SDG 7 Targets in EU Member States 5 Years after the Adoption of the Paris Agreement. Sustainability 2021, 13, 8284. [Google Scholar] [CrossRef]
  24. Swain, R.B.; Karimu, A. Renewable Electricity and Sustainable Development Goals in the EU. World Dev. 2020, 125, 104693. [Google Scholar] [CrossRef]
  25. Kuc-Czarnecka, M.; Markowicz, I.; Sompolska-Rzechuła, A.; Stundžienė, A. Factors Hindering and Boosting SDG7 Implementation in EU Countries. Technol. Econ. Dev. Econ. 2025, 31, 23–44. [Google Scholar] [CrossRef]
  26. Coelho, J.; Oliveira, T.; Neves, C.; Karatzas, S. Adoption of Digital Twins as a Sustainable Energy Solution: Determinants to Adoption in Household. Heliyon 2024, 10, e25782. [Google Scholar] [CrossRef] [PubMed]
  27. Minas, A.M.; García-Freites, S.; Walsh, C.; Mukoro, V.; Aberilla, J.M.; April, A.; Kuriakose, J.; Gaete-Morales, C.; Gallego-Schmid, A.; Mander, S. Advancing Sustainable Development Goals through Energy Access: Lessons from the Global South. Renew. Sustain. Energy Rev. 2024, 199, 114457. [Google Scholar] [CrossRef]
  28. Woerter, M.; Stucki, T.; Arvanitis, S.; Rammer, C.; Peneder, M. The Adoption of Green Energy Technologies: The Role of Policies in Austria, Germany, and Switzerland. Int. J. Green Energy 2017, 14, 1192–1208. [Google Scholar] [CrossRef] [PubMed]
  29. York, J.G.; Vedula, S.; Lenox, M.J. It’s Not Easy Building Green: The Impact of Public Policy, Private Actors, and Regional Logics on Voluntary Standards Adoption. Acad. Manag. J. 2018, 61, 1492–1523. [Google Scholar] [CrossRef]
  30. Cheba, K.; Bąk, I. Environmental Production Efficiency in the European Union Countries as a Tool for the Implementation of Goal 7 of the 2030 Agenda. Energies 2021, 14, 4593. [Google Scholar] [CrossRef]
  31. Schmithüsen, F.J. Three Hundred Years of Applied Sustainability in Forestry. Working Paper. 2013. Available online: https://www.research-collection.ethz.ch/handle/20.500.11850/154087 (accessed on 28 April 2024).
  32. Zabłocki, G. Rozwój Zrównoważony: Idee, Efekty, Kontrowersje (Perspektywa Socjologiczna); Wydawnictwo Uniwersytetu Mikołaja Kopernika: Toruń, Poland, 2002. [Google Scholar]
  33. Ziółkowski, B. Foresight w Strategicznym Rozwoju Ekoinnowacji Regionu–Pierwsze Doświadczenia Polski; Oficyna Wydawnicza Politechniki Rzeszowskiej: Rzeszów, Poland, 2009. [Google Scholar]
  34. Lusawa, R. Hans Carl von Carlowitz twórca pojęcia “trwałości”. Rocz. Nauk. Wydziału Zarządzania W Ciechanowie 2009, 3, 5–16. [Google Scholar]
  35. Ziółkowski, B. Ewolucyjne Podejście Do Ekoinnowacji i Zrównoważonego Rozwoju–Ujęcie Systemowe; Poligrafia Wyższego Seminarium Duchownego w Rzeszowie: Rzeszów, Poland, 2012. [Google Scholar]
  36. United Nations. General Assembly Report of the World Commission on Environment and Development. Annex: Our Common Future, Forty-Second Session. Item 83 (e) of the Provisional Agenda, A/42/427. Development and International Economic Co-Operation: Environment. 1987. Available online: https://documents.un.org/doc/undoc/gen/n87/184/67/pdf/n8718467.pdf (accessed on 20 April 2018).
  37. Borys, T. Wskaźniki Zrównoważonego Rozwoju; Wydawnictwo Ekonomia i Środowisko: Białystok/Warszawa, Poland, 2005. [Google Scholar]
  38. Skowron, S.; Szymoniuk, B. Marketing and Sustainable Development. Probl. Ekorozwoju 2014, 9, 39–46. [Google Scholar]
  39. Newport, D.; Chesnes, T.; Lindner, A. The “Environmental Sustainability” Problem: Ensuring That Sustainability Stands on Three Legs. Int. J. Sustain. High. Educ. 2003, 4, 357–363. [Google Scholar] [CrossRef]
  40. Banse, G. Nachhaltige Entwicklung Und Kultur-Anregungen Zur Diskussion. Humanit. Soc. Sci. 2014, XIX, 9–24. [Google Scholar]
  41. Burchard-Dziubińska, M. Rozwój Instytucji Na Rzecz Zrównoważonego Rozwoju. In Zrównoważony Rozwój na Poziomie Lokalnym i Regionalnym, Teoria i Praktyka; Burchard-Dziubińska, M., Rzeńca, A., Eds.; Wydawnictwo Uniwersytetu Łódzkiego: Łódź, Poland, 2010; pp. 81–105. [Google Scholar]
  42. Migała-Warchoł, A.; Ziółkowski, B.; Babiarz, P. The Circular Economy vs the Sustainable Development Approach to Production and Consumption: The Case of the European Union Countries. Humanit. Soc. Sci. 2023, 30, 59–74. [Google Scholar] [CrossRef]
  43. Brunnhuber, S. Money and Sustainability. The Missing Link. In Proceedings of the Lecture at a Seminar at the Faculty of Environmental Engineering, Lublin, Poland, 18 October 2013. [Google Scholar]
  44. Górka, K.; Poskrobko, B.; Radecki, W. Ochrona Środowiska. Problemy Społeczne, Ekonomiczne i Prawne; PWE: Warszawa, Poland, 1998. [Google Scholar]
  45. Leal Filho, W. Dealing with Misconceptions on the Concept of Sustainability. Int. J. Sustain. High. Educ. 2000, 1, 9–19. [Google Scholar] [CrossRef]
  46. Tsalis, T.A.; Malamateniou, K.E.; Koulouriotis, D.; Nikolaou, I.E. New Challenges for Corporate Sustainability Reporting: United Nations’ 2030 Agenda for Sustainable Development and the Sustainable Development Goals. Corp. Soc. Responsib. Environ. Manag 2020, 27, 1617–1629. [Google Scholar] [CrossRef]
  47. Ziółkowski, B. “Europa 2020” w Zarządzaniu Zrównoważonym Rozwojem Unii Europejskiej. Humanit. Soc. Sci. 2013, XVIII, 117–125. [Google Scholar] [CrossRef]
  48. Lyeonov, S.; Pimonenko, T.; Bilan, Y.; Štreimikienė, D.; Mentel, G. Assessment of Green Investments’ Impact on Sustainable Development: Linking Gross Domestic Product Per Capita, Greenhouse Gas Emissions and Renewable Energy. Energies 2019, 12, 3891. [Google Scholar] [CrossRef]
  49. Santika, W.G.; Anisuzzaman, M.; Bahri, P.A.; Shafiullah, G.M.; Rupf, G.V.; Urmee, T. From Goals to Joules: A Quantitative Approach of Interlinkages between Energy and the Sustainable Development Goals. Energy Res. Soc. Sci. 2019, 50, 201–214. [Google Scholar] [CrossRef]
  50. Santika, W.G.; Anisuzzaman, M.; Simsek, Y.; Bahri, P.A.; Shafiullah, G.M.; Urmee, T. Implications of the Sustainable Development Goals on National Energy Demand: The Case of Indonesia. Energy 2020, 196, 117100. [Google Scholar] [CrossRef]
  51. WN PWN Niezawodność-Definicja, Synonimy, Przykłady Użycia. Available online: https://sjp.pwn.pl/slowniki/niezawodno%C5%9B%C4%87.html (accessed on 11 October 2024).
  52. HarperCollins The American Heritage Dictionary Entry: Reliability. Available online: https://www.ahdictionary.com/word/search.html?q=reliability+ (accessed on 11 October 2024).
  53. Mikul, B.; Niki, A. Beyond Connections: Energy Access Redefined; ESMAP Technical Report; World Bank: Washington, DC, USA, 2015. [Google Scholar]
  54. Andriuškevičius, K.; Štreimikienė, D.; Alebaitė, I. Convergence between Indicators for Measuring Sustainable Development and M&A Performance in the Energy Sector. Sustainability 2022, 14, 10360. [Google Scholar] [CrossRef]
  55. Trinh, V.L.; Chung, C.K. Renewable Energy for SDG-7 and Sustainable Electrical Production, Integration, Industrial Application, and Globalization: Review. Clean. Eng. Technol. 2023, 15, 100657. [Google Scholar] [CrossRef]
  56. Soliński, J. Główne tezy raportu Organizacji Narodów Zjednoczonych i Światowej Rady Energetycznej pt. “Światowa ocena energetyczna-energia i wyzwanie szans rozwojowych”. Polityka Energetyczna 2001, 4, 5–44. [Google Scholar]
  57. IEA; IRENA; UNSD; World Bank; WHO. Tracking SDG 7: The Energy Progress Report 2024; World Bank: Washington, DC, USA, 2024.
  58. Miskiewicz, R. Clean and Affordable Energy within Sustainable Development Goals: The Role of Governance Digitalization. Energies 2022, 15, 9571. [Google Scholar] [CrossRef]
  59. Mukoro, V.; Sharmina, M.; Gallego-Schmid, A. A Review of Business Models for Access to Affordable and Clean Energy in Africa: Do They Deliver Social, Economic, and Environmental Value? Energy Res. Soc. Sci. 2022, 88, 102530. [Google Scholar] [CrossRef]
  60. de la Rue du Can, S.; Letschert, V.; Agarwal, S.; Park, W.Y.; Kaggwa, U. Energy Efficiency Improves Energy Access Affordability. Energy Sustain. Dev. 2022, 70, 560–568. [Google Scholar] [CrossRef]
  61. de la Rue du Can, S.; Pudleiner, D.; Pielli, K. Energy Efficiency as a Means to Expand Energy Access: A Uganda Roadmap. Energy Policy 2018, 120, 354–364. [Google Scholar] [CrossRef]
  62. Zakari, A.; Khan, I.; Tan, D.; Alvarado, R.; Dagar, V. Energy Efficiency and Sustainable Development Goals (SDGs). Energy 2022, 239, 122365. [Google Scholar] [CrossRef]
  63. Wigley, R. Renewable Energy vs. Sustainable Energy: What’s the Difference? MA in Sustainable Energy. 2021. Available online: https://energy.sais.jhu.edu/articles/renewable-energy-vs-sustainable-energy/ (accessed on 7 July 2024).
  64. Gargalo, C.L.; Yu, H.; Vollmer, N.; Arabkoohsar, A.; Gernaey, K.V.; Sin, G. A Process Systems Engineering View of Environmental Impact Assessment in Renewable and Sustainable Energy Production: Status and Perspectives. Comput. Chem. Eng. 2024, 180, 108504. [Google Scholar] [CrossRef]
  65. Sovacool, B.K.; Brisbois, M.-C. Elite Power in Low-Carbon Transitions: A Critical and Interdisciplinary Review. Energy Res. Soc. Sci. 2019, 57, 101242. [Google Scholar] [CrossRef]
  66. Klass, D.L. A Critical Assessment of Renewable Energy Usage in the USA. Energy Policy 2003, 31, 353–367. [Google Scholar] [CrossRef]
  67. Muhumuza, R.; Zacharopoulos, A.; Mondol, J.D.; Smyth, M.; Pugsley, A. Energy Consumption Levels and Technical Approaches for Supporting Development of Alternative Energy Technologies for Rural Sectors of Developing Countries. Renew. Sustain. Energy Rev. 2018, 97, 90–102. [Google Scholar] [CrossRef]
  68. Bhattacharyya, S.C. Renewable Energies and the Poor: Niche or Nexus? Energy Policy 2006, 34, 659–663. [Google Scholar] [CrossRef]
  69. Emodi, N.V.; Boo, K.-J. Sustainable Energy Development in Nigeria: Current Status and Policy Options. Renew. Sustain. Energy Rev. 2015, 51, 356–381. [Google Scholar] [CrossRef]
  70. Gardumi, F.; Petrarulo, L.; Sesay, S.; Caulker, D.; Howells, M.; Pappis, I. Supporting a Self-Sustained Energy Planning Ecosystem: Lessons from Sierra Leone. Energy Sustain. Dev. 2022, 70, 62–67. [Google Scholar] [CrossRef]
  71. Polcyn, J.; Us, Y.; Lyulyov, O.; Pimonenko, T.; Kwilinski, A. Factors Influencing the Renewable Energy Consumption in Selected European Countries. Energies 2021, 15, 108. [Google Scholar] [CrossRef]
  72. Sośnicki, M.; Wiśniewski, D. Koncepcja Zrównoważonego Rozwoju-Perspektywa Eko-Energetyki. Wiedza Obron. 2023, 283, 1–58. [Google Scholar] [CrossRef]
  73. Lu, B.; Blakers, A.; Stocks, M.; Cheng, C.; Nadolny, A. A Zero-Carbon, Reliable and Affordable Energy Future in Australia. Energy 2021, 220, 119678. [Google Scholar] [CrossRef]
  74. Matusiak, B.E.; Matejun, M.; Różańska-Bińczyk, I. Koncepcja zrównoważonego rozwoju jako środowisko implementacji praktyk green HR we współczesnych przedsiębiorstwach. In Wyzwania Społeczne i Technologiczne a Nowe Trendy w Zarządzaniu Współczesnymi Organizacjami; Urbaniak, M., Tomaszewski, A., Eds.; Oficyna Wydawnicza SGH: Warszawa, Poland, 2020; pp. 111–124. [Google Scholar]
  75. Kuc-Czarnecka, M.; Markowicz, I.; Sompolska-Rzechuła, A. SDGs Implementation, Their Synergies, and Trade-Offs in EU Countries–Sensitivity Analysis-Based Approach. Ecol. Indic. 2023, 146, 109888. [Google Scholar] [CrossRef]
  76. McCollum, D.; Gomez-Echeverri, L.; Busch, S.; Pachauri, S.; Parkinson, S.; Rogelj, J.; Krey, V.; Minx, J.; Nilsson, M.; Stevance, A.-S.; et al. Connecting the Sustainable Development Goals by Their Energy Inter-Linkages. Environ. Res. Lett. 2018, 13, 033006. [Google Scholar] [CrossRef]
  77. United Nations Goal 7 | Department of Economic and Social Affairs. Available online: https://sdgs.un.org/goals/goal7#targets_and_indicators (accessed on 17 September 2024).
  78. Cihák, M.; Demirgüç-Kunt, A.; Feyen, E.; Levine, R. Benchmarking Financial Systems around the World; Policy Research Working Papers; The World Bank: Washington, DC, USA, 2012. [Google Scholar]
  79. Ziolo, M.; Bak, I.; Cheba, K. The role of sustainable finance in achieving sustainable development goals: Does it work? Technol. Econ. Dev. Econ. 2020, 27, 45–70. [Google Scholar] [CrossRef]
  80. Burchardt, T.; Vizard, P. Definition of Equality and Framework for Measurement: Final Recommendations of the Equalities Review Steering Group on Measurement. 2007. Available online: https://ssrn.com/abstract=1159351 (accessed on 14 July 2008).
  81. Apergis, N.; Eleftheriou, S.; Payne, J.E. The Relationship between International Financial Reporting Standards, Carbon Emissions, and R&D Expenditures: Evidence from European Manufacturing Firms. Ecol. Econ. 2013, 88, 57–66. [Google Scholar] [CrossRef]
  82. Moner-Girona, M.; Szabo, S.; Bhattacharyya, S. 1.05-Finance Mechanisms and Incentives for Off-Grid Photovoltaic Technologies in the Solar Belt. In Comprehensive Renewable Energy, 2nd ed.; Letcher, T.M., Ed.; Elsevier: Oxford, UK, 2022; pp. 82–113. ISBN 978-0-12-819734-9. [Google Scholar]
  83. Yang, G.; Zhang, G.; Cao, D.; Zha, D.; Gao, X.; Su, B. China’s Provincial-Level Sustainable Energy Transition Requires Accelerating Renewable Energy Technological Innovation. Energy 2024, 288, 129672. [Google Scholar] [CrossRef]
  84. Luo, G.; Zhang, X. Universalization of Access to Modern Energy Services in Tibetan Rural Households—Renewable Energy’s Exploitation, Utilization, and Policy Analysis. Renew. Sustain. Energy Rev. 2012, 16, 2373–2380. [Google Scholar] [CrossRef]
  85. Chien, F.; Vu, T.L.; Hien Phan, T.T.; Van Nguyen, S.; Viet Anh, N.H.; Ngo, T.Q. Zero-Carbon Energy Transition in ASEAN Countries: The Role of Carbon Finance, Carbon Taxes, and Sustainable Energy Technologies. Renew. Energy 2023, 212, 561–569. [Google Scholar] [CrossRef]
  86. Battulga, S.; Dhakal, S. Stakeholders’ Perceptions of Sustainable Energy Transition of Ulaanbaatar City, Mongolia. Renew. Sustain. Energy Rev. 2024, 189, 114020. [Google Scholar] [CrossRef]
  87. Bieszk-Stolorz, B.; Markowicz, I. Decline in Share Prices of Energy and Fuel Companies on the Warsaw Stock Exchange as a Reaction to the COVID-19 Pandemic. Energies 2021, 14, 5412. [Google Scholar] [CrossRef]
  88. Sueyoshi, T.; Goto, M. Energy Intensity, Energy Efficiency and Economic Growth among OECD Nations from 2000 to 2019. Energies 2023, 16, 1927. [Google Scholar] [CrossRef]
  89. Deka, A.; Ozdeser, H.; Seraj, M. The Effect of GDP, Renewable Energy and Total Energy Supply on Carbon Emissions in the EU-27: New Evidence from Panel GMM. Environ. Sci. Pollut. Res. Int. 2023, 30, 28206–28216. [Google Scholar] [CrossRef]
  90. Popa, A.; Sahlian, D.; Crețu, R.F. Does the Increase in Renewable Energy Influence GDP Growth? An EU-28 Analysis. Energies 2021, 14, 4762. [Google Scholar] [CrossRef]
  91. Pan, X.-X.; Chen, M.-L.; Ying, L.-M.; Zhang, F.-F. An Empirical Study on Energy Utilization Efficiency, Economic Development, and Sustainable Management. Environ. Sci. Pollut. Res. Int. 2020, 27, 12874–12881. [Google Scholar] [CrossRef]
  92. Kaufmann, R. The Mechanisms for Autonomous Energy Efficiency Increases: A Cointegration Analysis of the US Energy/GDP Ratio. Energy J. 2004, 25, 63–86. [Google Scholar] [CrossRef]
  93. Brockway, P.E.; Sorrell, S.; Semieniuk, G.; Heun, M.K.; Court, V. Energy Efficiency and Economy-Wide Rebound Effects: A Review of the Evidence and Its Implications. Renew. Sustain. Energy Rev. 2021, 141, 110781. [Google Scholar] [CrossRef]
  94. Ahmed, N.; Sheikh, A.A.; Hamid, Z.; Senkus, P.; Borda, R.C.; Wysokińska-Senkus, A.; Glabiszewski, W. Exploring the Causal Relationship among Green Taxes, Energy Intensity, and Energy Consumption in Nordic Countries: Dumitrescu and Hurlin Causality Approach. Energies 2022, 15, 5199. [Google Scholar] [CrossRef]
  95. Chu, L.K.; Le, N.T.M. Environmental Quality and the Role of Economic Policy Uncertainty, Economic Complexity, Renewable Energy, Energy Intensity: The Case of G7 Countries. Environ. Sci. Pollut. Res. 2022, 29, 2866–2882. [Google Scholar] [CrossRef]
  96. Adedoyin, F.; Nwulu, N.; Victor Bekun, F. Environmental Degradation, Energy Consumption and Sustainable Development: Accounting for the Role of Economic Complexities with Evidence from World Bank Income Clusters. Bus. Strategy Environ. 2021, 30, 2727–2740. [Google Scholar] [CrossRef]
  97. Lee, C.W.; Zhong, J. Top down Strategy for Renewable Energy Investment: Conceptual Framework and Implementation. Renew. Energy 2014, 68, 761–773. [Google Scholar] [CrossRef]
  98. Azarova, E.; Jun, H. Investigating Determinants of International Clean Energy Investments in Emerging Markets. Sustainability 2021, 13, 11843. [Google Scholar] [CrossRef]
  99. Dogan, E.; Inglesi-Lotz, R.; Altinoz, B. Examining the Determinants of Renewable Energy Deployment: Does the Choice of Indicator Matter? Int. J. Energy Res. 2021, 45, 8780–8793. [Google Scholar] [CrossRef]
  100. Ragosa, G.; Warren, P. Unpacking the Determinants of Cross-Border Private Investment in Renewable Energy in Developing Countries. J. Clean. Prod. 2019, 235, 854–865. [Google Scholar] [CrossRef]
  101. Gatzert, N.; Vogl, N. Evaluating Investments in Renewable Energy under Policy Risks. Energy Policy 2016, 95, 238–252. [Google Scholar] [CrossRef]
  102. Wall, R.; Grafakos, S.; Gianoli, A.; Stavropoulos, S. Which Policy Instruments Attract Foreign Direct Investments in Renewable Energy? Clim. Policy 2019, 19, 59–72. [Google Scholar] [CrossRef]
  103. Kahn, E. The Production Tax Credit for Wind Turbine Powerplants Is an Ineffective Incentive. Energy Policy 1996, 24, 427–435. [Google Scholar] [CrossRef]
  104. Olatayo, K.; Wichers, J.; Stoker, P. The Advanced and Moderate-Growth Development Paths for the Viability and Future Growth of Small Wind Energy Systems. Renew. Sustain. Energy Rev. 2020, 117, 109496. [Google Scholar] [CrossRef]
  105. Sepetis, A. Sustainable finance and circular economy. In Circular Economy and Sustainability, 1st ed.; Stefanakis, A., Nikolaou, I., Eds.; Elsevier: Amsterdam, The Netherlands, 2021; pp. 207–226. [Google Scholar]
  106. Fatima, N.; Li, Y.; Ahmad, M.; Jabeen, G.; Li, X. Factors Influencing Renewable Energy Generation Development: A Way to Environmental Sustainability. Environ. Sci. Pollut. Res. 2021, 28, 51714–51732. [Google Scholar] [CrossRef] [PubMed]
  107. Aguirre, M.; Ibikunle, G. Determinants of Renewable Energy Growth: A Global Sample Analysis. Energy Policy 2014, 69, 374–384. [Google Scholar] [CrossRef]
  108. Marques, A.; Fuinhas, J.A.; Manso, J.R. Motivations Driving Renewable Energy in European Countries: A Panel Data Approach. Energy Policy 2010, 38, 6877–6885. [Google Scholar] [CrossRef]
  109. Ricciolini, E.; Tiralti, A.; Paolotti, L.; Rocchi, L.; Boggia, A. Sustainable Development According to 2030 Agenda in European Union Countries: Evidence of the Enlargement Policy. Sustain. Dev. 2023, 32, 1894–1912. [Google Scholar] [CrossRef]
  110. Carrillo, M. Measuring Progress towards Sustainability in the European Union within the 2030 Agenda Framework. Mathematics 2022, 10, 2095. [Google Scholar] [CrossRef]
  111. Wang, Q.; Chen, Y.; Guan, H.; Lyulyov, O.; Pimonenko, T. Technological Innovation Efficiency in China: Dynamic Evaluation and Driving Factors. Sustainability 2022, 14, 8321. [Google Scholar] [CrossRef]
  112. Prokopenko, O.; Cebula, J.; Chayen, S.; Pimonenko, T. Wind Energy in Israel, Poland and Ukraine: Features and Opportunities. Int. J. Ecol. Dev. 2017, 32, 98–107. [Google Scholar]
  113. Kilinc-Ata, N. The Evaluation of Renewable Energy Policies across EU Countries and US States: An Econometric Approach. Energy Sustain. Dev. 2016, 31, 83–90. [Google Scholar] [CrossRef]
  114. Szpilko, D.; Ejdys, J. European Green Deal—Research Directions. a Systematic Literature Review. Ekon. Sr. 2022, 81, 8–38. [Google Scholar] [CrossRef]
  115. Stern, D.I. The Role of Energy in Economic Growth. Ann. N. Y. Acad. Sci. 2011, 1219, 26–51. [Google Scholar] [CrossRef]
  116. Drago, C.; Gatto, A. Policy, Regulation Effectiveness, and Sustainability in the Energy Sector: A Worldwide Interval-Based Composite Indicator. Energy Policy 2022, 167, 112889. [Google Scholar] [CrossRef]
  117. Bouzarovski, S.; Petrova, S. A Global Perspective on Domestic Energy Deprivation: Overcoming the Energy Poverty-Fuel Poverty Binary. Energy Res. Soc. Sci. 2015, 10, 31–40. [Google Scholar] [CrossRef]
  118. United Nations. General Assembly Transforming Our World: The 2030 Agenda for Sustainable Development, Resolution Adopted by the General Assembly on 25 September 201; United Nations: San Francisco, CA, USA, 2015.
Energies 18 00722 g001
Figure 1. Research model and hypotheses. Source: authors’ calculations.
Figure 1. Research model and hypotheses. Source: authors’ calculations.
Energies 18 00722 g001
Table 1. Targets and indicators in Sustainable Development Goal 7 of the 2030 Agenda.
Table 1. Targets and indicators in Sustainable Development Goal 7 of the 2030 Agenda.
SDG 7 TargetsIndicators for SDG 7 Targets
Target 7.1. By 2030, ensure universal access to affordable, reliable and modern energy services7.1.1. Proportion of population with access to electricity
7.1.2. Proportion of population with primary reliance on clean fuels and technology
Target 7.2. By 2030, substantially increase the share of renewable energy in the global energy mix7.2.1. Renewable energy share in the total final energy consumption
Target 7.3. By 2030, double the global rate of improvement in energy efficiency7.3.1. Energy intensity measured in terms of primary energy and GDP
Target 7.a. By 2030, enhance international cooperation to facilitate access to clean energy research and technology, including renewable energy, energy efficiency and advanced and cleaner fossil fuel technology, and promote investment in energy infrastructure and clean energy technology7.a.1. International financial flows to developing countries in support of clean energy research and development and renewable energy production, including in hybrid systems
Target 7.b. By 2030, expand infrastructure and upgrade technology for supplying modern and sustainable energy services for all in developing countries, in particular, least developed countries, small island developing States and land-locked developing countries, in accordance with their respective programs of support7.b.1. Installed renewable energy-generating capacity in developing and developed countries (in watts per capita)
Source: authors’ own work based on [77].
Table 2. Determinants of Sustainable Development Goal 7 of the 2030 Agenda.
Table 2. Determinants of Sustainable Development Goal 7 of the 2030 Agenda.
SDG IndicatorsDriving Factors
EconomicSocialEnvironmental
7.1.1
7.1.2		[78,79][79,80][30,79,81]
7.2.1[1,82,83,84,85][67,69,86]
7.3.1[55,79,87,88,89,90][91,92,93][75,94,95,96]
7.a.1[97,98,99,100,101,102,103,104,105][106][98,100,107,108]
7.b.1[109][109][109,110]
Note: The SDG indicators comply with the numbers in Table 1. Source: author’s own work.
Table 3. Descriptive statistics for variables from Goal 7 of the 2030 Agenda and analyzed economic variables in the European Union.
Table 3. Descriptive statistics for variables from Goal 7 of the 2030 Agenda and analyzed economic variables in the European Union.
Analyzed VariablesDescriptive Statistics
MeanMedianMinMaxsCVAs
Final energy consumption in households per capita548.22550.00215.001016.00169.8330.980.30
Population unable to keep their homes adequately warm by poverty status 8.647.001.4022.506.2572.340.90
The share of renewable energy in gross final energy consumption 25.7320.8013.1166.0012.7549.571.54
Primary energy consumption46.5620.900.90260.1064.16137.802.23
Final energy consumption34.8316.700.70203.1048.01137.842.32
Energy productivity8.657.242.5326.774.9256.902.20
Energy import dependency by products61.0568.566.1699.0122.4736.80−0.48
GDP per capita29,357.0424,560.007680.0085,850.0019,107.3565.091.60
Unemployment rate5.795.602.2012.902.5343.711.40
Government consolidated gross debt2,569,174.34350,692.806657.4048,841,865.009,302,196.59362.075.10
Gross domestic expenditure on research and development1.741.460.463.430.9152.510.60
Legend: s—standard deviation; CV—coefficient of variation; As—asymmetry coefficient. Source: authors’ calculations.
Table 4. Pearson linear correlation coefficients between variables from Goal 7 of the 2030 Agenda and analyzed economic indicators in the European Union.
Table 4. Pearson linear correlation coefficients between variables from Goal 7 of the 2030 Agenda and analyzed economic indicators in the European Union.
SDG 7 VariablesPearson Linear Correlation Coefficients
The Coefficients Are Significant with p < 0.05
GDP per CapitaUnemployment RateGovernment Consolidated Gross DebtGross Domestic Expenditure on Research and Development
Final energy consumption in households per capita0.34−0.210.080.59
Population unable to keep their homes adequately warm by poverty status −0.400.46−0.14−0.50
Share of renewable energy in gross final energy consumption −0.020.23−0.170.42
Primary energy consumption0.040.070.020.33
Final energy consumption0.050.050.020.34
Energy productivity0.830.02−0.120.15
Energy import dependency by products0.330.100.01−0.20
Note: Bold and underline values are statistically significant. Source: authors’ calculations.
Table 5. Results of testing statistical hypotheses on relationships.
Table 5. Results of testing statistical hypotheses on relationships.
SDG 7 IndicatorsE1E2E3E4
Final energy consumption in households per capitaNNNTRUE
Population unable to keep their homes adequately warm by poverty statusTRUETRUENTRUE
Share of renewable energy in gross final energy consumptionNNNTRUE
Primary energy consumptionNNNN
Final energy consumptionNNNN
Energy productivityTRUENNN
Energy import dependency by productsNNNN
Legend: E1: GDP per capita; E2: unemployment rate; E3: government consolidated gross debt; E4: gross domestic expenditure on research and development. TRUE—existing relationship; N—no relationship. Source: authors’ calculations.
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Migała-Warchoł, A.; Ziółkowski, B.; Lew, A.; Stec-Rusiecka, J.; Warmińska, A. Factors Enabling Access to Affordable, Reliable, Sustainable and Modern Energy in the European Union. Energies 2025, 18, 722. https://doi.org/10.3390/en18030722

AMA Style

Migała-Warchoł A, Ziółkowski B, Lew A, Stec-Rusiecka J, Warmińska A. Factors Enabling Access to Affordable, Reliable, Sustainable and Modern Energy in the European Union. Energies. 2025; 18(3):722. https://doi.org/10.3390/en18030722

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Migała-Warchoł, Aldona, Bożydar Ziółkowski, Agnieszka Lew, Jolanta Stec-Rusiecka, and Agata Warmińska. 2025. "Factors Enabling Access to Affordable, Reliable, Sustainable and Modern Energy in the European Union" Energies 18, no. 3: 722. https://doi.org/10.3390/en18030722

APA Style

Migała-Warchoł, A., Ziółkowski, B., Lew, A., Stec-Rusiecka, J., & Warmińska, A. (2025). Factors Enabling Access to Affordable, Reliable, Sustainable and Modern Energy in the European Union. Energies, 18(3), 722. https://doi.org/10.3390/en18030722

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