Energy Use Greenization, Carbon Dioxide Emissions, and Economic Growth: An Empirical Analysis Based in China

Introduction

Environmental issues, such as climate change and global warming, have become critical issues at the global level and have begun to pose a serious threat to sustainable development (Bekun et al., 2019; Yam et al., 2021). Owing to industrialization and urbanization, the world has experienced considerable economic growth over the past few decades (Li et al., 2021). Carbon dioxide emissions are likely to grow at the second-fastest pace on record this year as global economies recover from the COVID-19 recession and invest stimulus money into fossil fuels (Zheng et al., 2019a). Fossil fuels will remain an important source of the energy mix in many countries (Liang et al., 2022). The drastic economic development of the BRIC countries has led to a large number of environmental problems, especially the emission of carbon dioxide (Pata, 2021). Substantial economic growth is in one way or another related to fossil fuel consumption that produces large amounts of greenhouse gases (GHGs) in the environment, which warms the atmosphere (Pata and Kumar, 2021; Yin et al., 2021). The increasing concentration of GHGs is primarily responsible for global warming and climate change. The production of GHGs is considered a major factor affecting carbon dioxide emissions (Wu et al., 2021). Climate change has certain adverse impacts on human health, and among many factors, carbon dioxide is the most important gas that deteriorates the environment and human health. Brazil, India, China, and South Africa are fast emerging economies (FECs) owing to their strong fundamental base and reliance on fossil fuel energy sources, leading to increased GHG emissions and adverse effects on human health (Liu et al., 2020). The European Union (EU) considers that renewable energy sources can mitigate the effects of climate change (Bekun et al., 2021c). Reducing CO₂ emissions has become the primary priority for all economies throughout the world. Countries ratified the United Nations Framework Convention on Climate Change in 1992 to slow the global climate crisis, which is also the premise and foundation of cooperation among countries worldwide. In 2015, the Paris Climate Change Summit established a sustainable development goal for 2030. With the rapid development of the Chinese economy, China’s dependence on energy consumption is increasing every year. The overall energy consumption of China in 2018 was 4.644 billion tons of standard coal, 3.3% higher than the previous year, and the total carbon emissions were 2.5% higher than the preceding year (Zheng et al., 2020; Zhou et al., 2021). Although the proportion of coal consumption has decreased by 1.4% from the previous year, it still accounts for 59% of the total energy consumption (Liu and Cai., 2018). Based on the statistical report of the International Energy Agency (IEA), China is the world’s largest emitter of CO₂ and carbon emissions still continue to increase rapidly. China is highly concerned about the climate change problem. China has increased its efforts to promote low-carbon development in recent years by efficiently reducing GHG emissions, effectively boosting the adaptive capacity of the climate and continuously improving systems and mechanisms of operation.

China has also contributed positively to the Paris Agreement’s finalization, adopting stronger policies to achieve sustainable development by 2030 and carbon neutrality by 2060 (Chi et al., 2021). Zheng et al. (2019a) suggest that the energy intensity per person may greatly reduce CO₂ emissions from energy-related companies in China, and the gross domestic product (GDP) is a crucial factor influencing the increase in industrial CO₂ emissions. Renewable energy is considered an alternative to overcome global warming and an effective choice to continue fossil fuel growth (Zheng et al., 2019b). Renewable technologies help to reduce CO₂ emissions from conventional energy sources to achieve a sustainable energy consumption system (Asongu et al., 2018). Furthermore, energy-saving solutions can help close the gap between CO₂ emissions and economic growth, enabling long-term development. To achieve sustainable energy development, China needs to continuously promote energy use greenization, complete the economic transformation, control CO₂ emissions, and bear the responsibility of major countries to reduce CO₂ emissions from a strategic standpoint.

Thus, given this background, it is important to evaluate the nexuses between energy use greenization, CO₂ emissions, and economic growth in China. Some pioneering studies (Anwar, 2016; Ishaque, 2017; Shahzad et al., 2017) have empirically investigated the nexus between CO₂ emissions and macroeconomic variables on the economy as a whole. In China, only few studies exist on the relationship between energy use greenization, CO₂ emissions, and economic growth. Second, based on the generalized method of moments (GMM) and structural modeling, this study analyzes CO₂ emissions, energy use greenization, and economic growth by using simultaneous equations. The primary goal of using the simultaneous system approach is just to account for simultaneity issues to avoid potential problems in error estimations of econometric researchers (Baydoun and Aga, 2021). The results of this study will provide important information for the development of environment and economic growth policies.

The remainder of this study is structured in the following manner. First, we provide a literature review and the econometric models and data are then examined. Subsequently, empirical analysis and debate are presented. Finally, the findings are addressed, and the policy implications.

A Brief Literature Review

The literature has shown widespread concern about the links between energy use, economic growth, and CO₂ emissions. As mentioned previously, the present literature can be classified into three sections of research; the first section focuses on the relationship between energy use and economic growth. The relationship between energy and growth is of great interest to not only economists but also to policymakers, because of its significant policy implications. Some researchers suggest that both key macro-variables and economic growth are the most important pillars of energy use; thus, the application of these candidate series to energy development programs is advocated (He et al., 2021). Energy use directly and/or indirectly contributes to economic growth (Wu et al., 2021). Conversely, other studies showed that energy use is determined by economic growth and not vice versa (Lan et al., 2021); several studies also found that both true GDP and energy use are interdependent, and there is bidirectional causality between them (Bekun et al., 2021c). However, some studies found that there is no causal relationship between energy use and economic development (Bekun et al., 2021b; Fang et al., 2022). The development of clean energy has a positive impact on the economic growth of new EU members (Regulation of the European Parliament and of the Council, 2021). Moreover, renewable energy is a dynamic force for economic growth in the OECD and G-7 economies (Bekun et al., 2019). The development of renewable energy is an important part of green economic growth and it also depends on the implementation of environmental regulation policies, which have made important contributions to the development of renewable energy.

The second section focuses on renewable energy consumption and environmental issues. With the rapid development of green energy, more researchers have studied the fundamental contribution of green energy development to the mitigation of emissions at the national, regional, and world levels. Many recent studies have confirmed the beneficial effects of green energy on environmental quality (Bekun, 2022). For example, the use of green energy leads to a drop in CO₂ emissions (Bekun et al., 2021a; Irfan et al., 2022). The development of green energy has contributed significantly to environmental improvements in 85 developed and developing economies (Osobajo et al., 2020). In addition, several researchers have found a bidirectional causal relationship between green energy and environmental quality (Ahukaemere et al., 2020; Manta et al., 2020). However, the empirical results of some studies do not demonstrate a causal relationship between renewable energy consumption and environmental quality (Liu et al., 2021). Conversely, the exploitation of green energy has reduced CO₂ emissions in five selected African economies (Baydoun and Aga, 2021). In the face of economic growth trajectories, renewable energy is a panacea for sustainable development.

The third section of the literature examines the relationship between renewable energy and economic growth, and the validity of the Environmental Kuznets Curve (EKC) Hypothesis. According to the EKC hypothesis, the relationship between economic growth and environmental deterioration resembles an inverted U-shaped curve. Many scholars, such as Osobajo et al. (2020), have proven the inverted U-shaped relationship between economic growth and CO₂ emissions, but the “EKC hypothesis” was generally regarded as a phenomenon to be tested in the present research. In some existing studies, the inverted U-shaped curve confirms that the growth of low-income per capita intensifies environmental deterioration until it stabilizes at middle-income levels, at which point fresh growth leads to improved environmental conditions (Liu and Cai, 2018; Iqbal et al., 2022). Several studies have validated the EKC hypothesis in a single nation (Liu et al., 2019; Pata and Isik, 2021). However, the EKC hypothesis does not hold true for China (Pata and Aydin, 2020; Pata and Caglar, 2020). In five EU nations, there was an inverted U-shaped relationship between CO₂ emissions and economic development (Zheng et al., 2019a; Chen and Ma, 2021). Some studies found that economic growth boosts the usage of renewable energy (Chi et al., 2021). These findings suggest that the relationship between non-renewable energy, renewable energy, and economic growth appears to be U-shaped in the economy of India (Sarfraz et al., 2021). In the long run, CO₂ emissions have an N-shaped relationship with the real GDP per capita, rather than the traditional U-shaped curve given by the EKC hypothesis (Olivier and Peters, 2020). Through a comparative study, the economic growth in Australia accelerated CO₂ emissions. In the long run, Canadian trade appears to increase CO₂ emissions, while economic growth and urban population also boost CO₂ emissions (Shah et al., 2021).

Based on structural modeling and the GMM estimator, this study used simultaneous equations to analyze the relationship between energy use greenization, CO₂ emissions, and economic growth from an empirical research perspective, and the results were compared with those from existing research. The primary motivation for using the simultaneous system technology was to compensate for the simultaneity problems and prevent a potentially biased evaluation by econometric researchers (Hassan et al., 2019). The interconnection between economic growth, energy consumption, and CO₂ emissions has been examined extensively by researchers both at home and abroad, offering a solid framework for this research. China is rapidly developing as a country. China is the world’s second-largest producer and consumer of energy and the second-largest emitter of CO₂. China faces enormous pressure from the international community to save energy and reduce emissions. The subject of this case study is the connection between China’s energy use greenization, CO₂ emissions, economic growth, energy conservation, and emission reduction through energy policy and policy formulation.

Compared with that of previous studies, the marginal contribution of this study is as follows: first, based on the existing literature, the Cobb–Douglas production function model was used to introduce CO₂ emissions and construct a regression equation for carbon dioxide emissions. Second, an empirical study of the link between energy use greenization, CO₂ emissions, and economic growth was conducted through the simultaneous equation modeling approach. Third, this study uses the proportion of clean energy consumption such as natural gas, nuclear power, and hydropower in total energy consumption as a measure of energy use greenization.

Model Building and Data

Model Building

To study the relationship between economic growth, CO₂ emissions, and energy use greenization, we used the Cobb–Douglas production function model, wherein the income is influenced by the level of technology, labor, and capital. Apart from these factors, energy as a potential factor in economic growth has also been cited (Rousseeuw and Yohai, 1984). Generally, the extended Cobb–Douglas production function is expressed as follows:

$Y=A{K}^{{\beta }_1}{L}^{{\beta }_2}{E}^{{\beta }_3}{e}^{\epsilon },(1)$

where Y represents the income level; A represents the level of technology; K represents the capital; L represents the labor; E represents energy use; and β₁, β₂, and β_3, respectively, represent the output elastic coefficients of capital, labor, and energy use. There is a linear relation between CO₂ emissions (CE) and energy use, and at any time: E = b.CE at a specific level of technology. Furthermore, some energy economists discovered that renewable energy may reduce CO₂ emissions while also increasing economic growth; hence, renewable energy can be used as a component in the production function model (Tiwari, 2011; Mahjabeen, 2020; Venkatraja, 2020). Therefore, the extended Cobb–Douglas production function model is expressed as follows:

$Y=A{K}^{{\beta }_1}{L}^{{\beta }_2}bC{E}^{{\beta }_3}R{E}^{{\beta }_4}{e}^{\epsilon }.(2)$

We considered the logarithm of the Cobb–Douglas production function model (2) and obtained the following result:

$\ln Y_t={\beta }_0+{\beta }_1\ln C{E}_t+{\beta }_2\ln EU{G}_t+{\beta }_3\ln L_t+{\beta }_4\ln K_t+{\epsilon }_t,(3)$

where β₀ = ln A; t is the subscript; T represents the time period; Y indicates the income level; CE indicates the CO₂ emissions per capita; EUG indicates energy use greenization; K represents the capital; L indicates labor; and ε is a random variable. The production function model was separated into multiple analysis models to inspect the relationship between energy use greenization, economic growth, and CO₂ emissions. These new models were established on the foundation of past theoretical and empirical research. Energy use greenization and CO₂ emissions can be used as the dependent or independent variables. To examine the causality of income, capital (K), labor (L), energy use (EU), squared GDP (Y²), direct foreign investment (F), trade openness (T), oil prices (OP), financial development (FD), and urbanization (U) are defined as independent variables.

An empirical study of the link between energy use greenization, CO₂ emissions, and economic growth is conducted through the following three function models:

$\ln Y_t={\beta }_0+{\beta }_1\ln C{E}_t+{\beta }_2\ln EU{G}_t+{\beta }_3\ln K_t+{\beta }_4\ln L_t+{\epsilon }_t,(4)$

$\ln C{E}_t={\beta }_0+{\beta }_1\ln Y_t+{\beta }_2\ln EU{G}_t+{\beta }_3\ln Y_t^2+{\beta }_4\ln E{U}_t+{\beta }_5\ln U_t+{\beta }_6\ln F_t+{\epsilon }_t,(5)$

$\ln EU{G}_t={\beta }_0+{\beta }_1\ln Y_t+{\beta }_2\ln C{E}_t+{\beta }_3\ln O{P}_t+{\beta }_4\ln F{D}_t+{\beta }_5\ln T_t+{\epsilon }_t.(6)$

Model (4) shows that the GDP is affected by CO₂ emissions, renewable energy, labor, and capital (Danish et al., 2017). Model (5) indicates that the amount of CO₂ emissions is affected by the GDP per capita, renewable energy, energy use, squared GDP per capita, urbanization, and direct foreign investment (Lee and Brahmasrene, 2014). Model (6) indicates that energy use greenization is affected by the GDP, oil prices, CO₂ emissions, and external trade (Ishaque, 2017).

Models (4–6) are tested by using the GMM, which is a frequently used multidirectional model. The GMM can be used to solve the problem of endogeneity, and an effective and reliable evaluation is conducted when any heteroscedasticity occurs. In addition, two diagnostic examinations are required for estimating models (4–6); namely, Hansen’s test for excessive identification limits and Durbin–Wu–Hausman’s (DWH) test for examining the issue of endogeneity (Engle and Granger, 1987). The first test provides proof of the validity of the instrumental variable. This tests the hypothesis that these instruments are suitable, and this hypothesis was consequently rejected. The second test was used to examine endogeneity issues in the three forecasted models. The alternative hypothesis affirms the endogeneity of the instruments. If the hypothesis is accepted, the technology of the instrumental variable is unsuitable.

Data and Descriptive Statistics

To evaluate models (4–6), we collected the annual data of China from 2000 to 2018. These data are sourced from the Chinese Energy Statistic Yearbook and the Chinese Statistical Yearbook. To eliminate the possible heteroscedasticity problem, the horizontal time series data are processed by a natural logarithm to obtain lnEUG, lnCE, and lnY, as shown in Figure 1. Figure 1 shows the changing trends of lnEUG, lnCE, and lnY. It shows that since 2000, the proportion of clean energy consumption in China generally transitioned from a slow increase (2000–2008) to a rapid increase (2009–2018); namely, from 5.5% in 2000 to 15.7% in 2018, indicating that China has achieved certain results in energy use greenization and energy consumption structure optimization. Simultaneously, although China’s CO₂ emissions are increasing every year, the growth rate has slowed down significantly since 2012. This shows that the continuous optimization of the industrial structure and energy consumption structure has significantly reduced the growth rate of carbon emissions, even in 2016, which showed a negative growth of 0.3%. In addition, China’s per capita GDP also showed a steady growth trend during the sample period, but the growth rate has declined in recent years.

FIGURE 1

FIGURE 1. Time series of lnEUG, lnCE, and lnY.

Table 1 shows that during the sample period, the GDP per capita ranged from 5,305.8 to 11,817.6 Yuan; the per capita CO₂ emissions ranged from 0.57 to 29.5 tons; and energy use greenization accounted for 0.007–0.054% of the total ultimate energy consumption.

TABLE 1

TABLE 1. Descriptive statistics.

Table 2 shows that the GDP and CO₂ emissions per capita showed the largest correlation, whereas the urbanization variable showed the lowest. Moreover, there is a significant negative relationship between CO₂ emissions and energy use greenization. Energy use greenization is positively correlated with the GDP per capita, which implies that increasing energy use greenization in the total ultimate energy use may reduce CO₂ emissions per capita and increase the GDP per capita.

TABLE 2

TABLE 2. Variable correlations.

Empirical Results and Discussion

Through Hansen’s test and the DWH test, the evaluation coefficients of models (4–6) are presented in Table 3. The empirical findings of model (4) indicate that CO₂ emissions show a significant negative correlation with the GDP. If the per capita CO₂ emissions increase by 1%, the economic growth is expected to decrease by about 0.1%. This result was confirmed by the survey results of Pata (2018), who showed that Turkey’s GDP per capita had not reached a level to reduce environmental pollution, and the consumption of renewable energy was not a solution to reduce CO₂ emissions. However, China’s energy use greenization has a remarkable impact on economic growth, which confirms the growth hypothesis. These results are supported by the cases of developing countries (Zheng et al., 2019a; Iqbal et al., 2019). In addition, the capital and labor force coefficients show significantly positive and negative correlations with the economic growth, respectively.

TABLE 3

TABLE 3. Simultaneous equation generalized method of moment estimation for the models.

The empirical results of model (5) show that the per capita GDP influences CO₂ emissions per capita. The research shows that there is a positive relationship between the per capita GDP and per capita CO₂ emissions. If the GDP per capita increases by 0.1%, the CO₂ emissions per capita are expected to increase by about 0.70%. This shows that the improvement of economic growth worsens the environmental quality. This result was confirmed by the findings of Höhne et al. (2011) for 15 European countries. We found a negative correlation between energy use greenization and CO₂ emissions. If energy use greenization increases by 1%, CO₂ emissions per capita are expected to decrease by about 0.05%. This result is the same as that in the references (Shahzad et al., 2017). However, our result contradicts the findings of one of the references (Shabani and Shahnazi, 2019). Energy use shows a significant positive correlation with CO₂ emissions per capita. If energy use increases by 1%, the CO₂ emissions per capita are expected to rise by about 0.41%. Similarly, urbanization and trade openness have positive correlations with CO₂ emissions per capita.

Finally, the empirical findings of model (6) display that the GDP per capita is significantly positive for energy use greenization at a level of 5%. Energy use greenization is expected to increase by about 0.22% if the economic growth increases by 1%. This finding shows that there is a positive and significant relationship between energy use greenization and economic growth, which implies that the increase in economic growth will lead to an increase in energy use greenization. Regarding the environmental variable, we found a positive correlation between CO₂ emissions per capita and the demand for renewable energy. If CO₂ emissions per capita increase by 1%, energy use greenization is expected to increase by about 0.24%. These results show that CO₂ emissions per capita increase environmental degradation and promote the production and consumption of carbon-free sustainable energy, while lower CO₂ emissions lead to lower renewable energy consumption. We also found a positive correlation between financial development and the demand for renewable energy. If financial development increased by 1%, the energy use greenization was expected to increase by about 0.21%. This result showed that financial development was an important catalyst to promote production and energy use greenization in China.

The aforementioned results indicated that (i) energy use greenization promotes per capita GDP growth; (ii) increased economic growth leads to higher CO₂ emissions, and continued increases in CO₂ emissions may reduce economic growth; and (iii) increased CO₂ emissions can boost the demand for renewable energy, thereby reducing CO₂ emissions.

Discussion and Conclusion

The main objective of this study was to investigate the relationship between CO₂ emissions, energy use greenization, and economic growth. Our findings show that energy use greenization may have narrowed the gap between China’s economic growth and CO₂ emissions from 2000 to 2018. This study tested these interrelations using the simultaneous equation model approach. This approach enables us to simultaneously examine the relationship between energy use greenization, CO₂ emissions, and GDP. Our empirical results show that energy use greenization can promote economic growth. We also found that economic growth leads to increased CO₂ emissions, which promotes energy use greenization. Our findings also emphasize that energy use greenization can narrow the gap between China’s economic growth and CO₂ emissions.

The key policy implications emerging from the aforementioned results are as follows. First, we found a significant relationship between the GDP and CO₂ emissions. The results indicate that economic growth leads to an increase in CO₂ emissions, and the continuous increase of CO₂ emissions reduces economic growth. Hence, to solve the contradiction between energy supply and security, economic growth, and environmental protection, the Chinese government has promulgated the Energy Law of the People’s Republic of China. The Chinese government encourages the development of clean energy and defines hydropower, nuclear energy, natural gas, coal-bed methane, wind energy, biomass energy, solar energy, geothermal energy, and ocean energy as clean and low-carbon energy. Moreover, energy greenization should be an important component of the CO₂ emission mechanism. Increased CO₂ emissions can increase the demand for energy use greenization, thereby continuously reducing CO₂ emissions. Second, there is a significant relationship between energy use greenization and CO₂ emissions. An increase in CO₂ emissions can increase the demand for energy use greenization and continuously reduce CO₂ emissions. High fossil fuel consumption and the sharp increase in CO₂ emissions have brought severe challenges to the sustainable development of China’s economy. Energy structure transformation and CO₂ emission reduction have become important issues for China. Therefore, China is geographically well-positioned and has a high potential for the production of renewable energy from solar and wind energy. The Chinese government has increased the proportion of renewable energy usage in total energy consumption through measures to adjust the energy structure. In terms of economic and social aspects, the Chinese government not only encourages energy use greenization, but also provides funds to improve renewable energy consumption and industrial energy use. China implements green finance policies and reduces investments in high-polluting and high-emission industries. These measures will enable China to profit entirely from the interests of energy use greenization. On the one hand, energy use greenization is changing the traditional energy consumption structure, transitioning from coal-fired cogeneration in the past to distributed energy structures, combined natural gas cooling, heating, and power, and complementary clean and renewable energy. Simultaneously, the peak adjustment capacity of clean energy reserves should also be improved to expand its utilization scope. Conversely, owing to China’s high demand for coal in the short term, the development and application of coal cleaning technology need to be accelerated, and black energy (coal) needs to be transformed into green energy.

Suggestions and Policy Implementations

We need to acknowledge the positive role of energy use greenization in reducing CO₂ emissions to achieve sustainable economic growth. Simultaneously, as a developing country, China should pay special attention to maintaining economic growth and employment stability in the process of energy use greenization. Therefore, it is necessary to promote the transformation of the traditional energy production industry (such as coal and oil industries) to mechanization and intelligence, transition from simple resource mining to deep processing, and eliminate the backward production capacity. Some manufacturing industries (with large traditional energy consumption, such as power production and supply industries) need to be encouraged to purchase green raw materials and green production equipment, increase the proportion of clean energy and renewable energy input, and realize energy use greenization from the production side. For the green energy-related industries (such as the new energy vehicle industry), policy support, including subsidies and research and development tax incentives, is required in the initial stage of enterprise incubation and green technology research.

On the one hand, energy use greenization requires changing the traditional energy consumption structure, from the cogeneration of coal and power to distributed energy, cold, heat, and electricity systems, and complementary clean energy and renewable energy. Simultaneously, the peak regulation capacity of clean energy reserves should also be improved to expand its scope of utilization. Conversely, because China still has a high demand for coal in the short term, the development and application of clean coal technologies should be accelerated; these include carbon emission control technologies, carbon sequestration (including carbon capture), and clean coal combustion technologies, including circulating fluidized bed combustion to promote the transformation of coal to green energy. This study intends to accelerate the market-oriented reform of energy and the power system, and promote the role of the market mechanism on the sides of power generation and sales. In addition, with the continuous development of China’s green economy, the related green energy industry has a large capital gap. Therefore, it is necessary to comprehensively use green financial methods, such as green credit, to meet the capital needs in the process of energy use greenization.

This study discusses the relationship between energy use greenization, CO₂ emissions, and economic growth, and provides a theoretical basis and policy recommendations for the sustainable promotion of energy use greenization in China. However, this study was only conducted at the national level and can be conducted at the regional or industry level in the future.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author.

Author Contributions

WX: writing an initial draft. KI coordinated the work and writing—analysis. YW: proofreading.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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