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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Environ. Sci.</journal-id>
<journal-title>Frontiers in Environmental Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Environ. Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-665X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">871001</article-id>
<article-id pub-id-type="doi">10.3389/fenvs.2022.871001</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Environmental Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Energy Use Greenization, Carbon Dioxide Emissions, and Economic Growth: An Empirical Analysis Based in China</article-title>
<alt-title alt-title-type="left-running-head">Xinmin et al.</alt-title>
<alt-title alt-title-type="right-running-head">China Economic Growth</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Xinmin</surname>
<given-names>Wang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Iqbal</surname>
<given-names>Kashif</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1527744/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Yichu</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1607398/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>School of Business</institution>, <institution>Northwest Normal University</institution>, <addr-line>Lanzhou</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>College of International Students</institution>, <institution>Wuxi University</institution>, <addr-line>Wuxi</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>School of Oriental and African Studies</institution>, <institution>University of London</institution>, <addr-line>London</addr-line>, <country>United Kingdom</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1086671/overview">Jingli Fan</ext-link>, China University of Mining and Technology, Beijing, China</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/880530/overview">Muhammad Mohsin</ext-link>, Jiangsu University, China</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1465993/overview">Ugur Korkut Pata</ext-link>, Osmaniye Korkut Ata University, Turkey</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Kashif Iqbal, <email>kashii42@yahoo.com</email>
</corresp>
<fn fn-type="other">
<p>This article was submitted to Environmental Economics and Management, a section of the journal Frontiers in Environmental Science</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>30</day>
<month>06</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>10</volume>
<elocation-id>871001</elocation-id>
<history>
<date date-type="received">
<day>07</day>
<month>02</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>13</day>
<month>05</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Xinmin, Iqbal and Wang.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Xinmin, Iqbal and Wang</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Developing countries are constantly facing the problem of environmental degradation. Environmental degradation is caused by the consumption of non-renewable energy for economic growth, but the consequences of environmental degradation cannot be ignored. The main purpose of this study is to investigate the relationship between three variables (i.e., energy use greenization, CO<sub>2</sub> emission, and economic growth) in the case of China using simultaneous equation modeling techniques and data for the period 2000&#x2013;2018. The results indicate that (1) there is a long-term equilibrium relationship between energy use greenization, carbon emissions, and economic growth in China. Energy use greenization not only reduces carbon dioxide emissions but also promotes sustainable economic growth in China. (2) Carbon emissions and economic growth have promoted energy use greenization, indicating that the pressures of environmental climate and economic transformation in China have forced energy use greenization to a certain extent. (3) The contribution rate of energy use greenization to economic growth shows an inverted U-shaped trend that rises first and then decreases subsequently, while carbon emissions have a relatively large contribution rate to green energy use and economic growth. These results have far-reaching policy directions for the environmental sustainability goals of the Chinese economy.</p>
</abstract>
<kwd-group>
<kwd>energy use greenization</kwd>
<kwd>CO<sub>2</sub> emission</kwd>
<kwd>economic growth</kwd>
<kwd>energy economics</kwd>
<kwd>China</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>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 (<xref ref-type="bibr" rid="B7">Bekun et al., 2019</xref>; <xref ref-type="bibr" rid="B46">Yam et al., 2021</xref>). Owing to industrialization and urbanization, the world has experienced considerable economic growth over the past few decades (<xref ref-type="bibr" rid="B24">Li et al., 2021</xref>). 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 (<xref ref-type="bibr" rid="B49">Zheng et al., 2019a</xref>). Fossil fuels will remain an important source of the energy mix in many countries (<xref ref-type="bibr" rid="B25">Liang et al., 2022</xref>). The drastic economic development of the BRIC countries has led to a large number of environmental problems, especially the emission of carbon dioxide (<xref ref-type="bibr" rid="B34">Pata, 2021</xref>). 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 (<xref ref-type="bibr" rid="B38">Pata and Kumar, 2021</xref>; <xref ref-type="bibr" rid="B47">Yin et al., 2021</xref>). 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 (<xref ref-type="bibr" rid="B45">Wu et al., 2021</xref>). 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 (<xref ref-type="bibr" rid="B26">Liu et al., 2020</xref>). The European Union (EU) considers that renewable energy sources can mitigate the effects of climate change (<xref ref-type="bibr" rid="B8">Bekun et al., 2021c</xref>). Reducing CO<sub>2</sub> 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&#x2019;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 (<xref ref-type="bibr" rid="B51">Zheng et al., 2020</xref>; <xref ref-type="bibr" rid="B52">Zhou et al., 2021</xref>). 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 (<xref ref-type="bibr" rid="B29">Liu and Cai., 2018</xref>). Based on the statistical report of the International Energy Agency (IEA), China is the world&#x2019;s largest emitter of CO<sub>2</sub> 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.</p>
<p>China has also contributed positively to the Paris Agreement&#x2019;s finalization, adopting stronger policies to achieve sustainable development by 2030 and carbon neutrality by 2060 (<xref ref-type="bibr" rid="B11">Chi et al., 2021</xref>). <xref ref-type="bibr" rid="B49">Zheng et al. (2019a)</xref> suggest that the energy intensity per person may greatly reduce CO<sub>2</sub> emissions from energy-related companies in China, and the gross domestic product (GDP) is a crucial factor influencing the increase in industrial CO<sub>2</sub> emissions. Renewable energy is considered an alternative to overcome global warming and an effective choice to continue fossil fuel growth (<xref ref-type="bibr" rid="B50">Zheng et al., 2019b</xref>). Renewable technologies help to reduce CO<sub>2</sub> emissions from conventional energy sources to achieve a sustainable energy consumption system (<xref ref-type="bibr" rid="B3">Asongu et al., 2018</xref>). Furthermore, energy-saving solutions can help close the gap between CO<sub>2</sub> 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 CO<sub>2</sub> emissions, and bear the responsibility of major countries to reduce CO<sub>2</sub> emissions from a strategic standpoint.</p>
<p>Thus, given this background, it is important to evaluate the nexuses between energy use greenization, CO<sub>2</sub> emissions, and economic growth in China. Some pioneering studies (<xref ref-type="bibr" rid="B2">Anwar, 2016</xref>; <xref ref-type="bibr" rid="B21">Ishaque, 2017</xref>; <xref ref-type="bibr" rid="B44">Shahzad et al., 2017</xref>) have empirically investigated the nexus between CO<sub>2</sub> emissions and macroeconomic variables on the economy as a whole. In China, only few studies exist on the relationship between energy use greenization, CO<sub>2</sub> emissions, and economic growth. Second, based on the generalized method of moments (GMM) and structural modeling, this study analyzes CO<sub>2</sub> 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 (<xref ref-type="bibr" rid="B4">Baydoun and Aga, 2021</xref>). The results of this study will provide important information for the development of environment and economic growth policies.</p>
<p>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.</p>
</sec>
<sec id="s2">
<title>A Brief Literature Review</title>
<p>The literature has shown widespread concern about the links between energy use, economic growth, and CO<sub>2</sub> 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 (<xref ref-type="bibr" rid="B16">He et al., 2021</xref>). Energy use directly and/or indirectly contributes to economic growth (<xref ref-type="bibr" rid="B45">Wu et al., 2021</xref>). Conversely, other studies showed that energy use is determined by economic growth and not vice versa (<xref ref-type="bibr" rid="B22">Lan et al., 2021</xref>); several studies also found that both true GDP and energy use are interdependent, and there is bidirectional causality between them (<xref ref-type="bibr" rid="B8">Bekun et al., 2021c</xref>). However, some studies found that there is no causal relationship between energy use and economic development (<xref ref-type="bibr" rid="B6">Bekun et al., 2021b</xref>; <xref ref-type="bibr" rid="B14">Fang et al., 2022</xref>). The development of clean energy has a positive impact on the economic growth of new EU members (<xref ref-type="bibr" rid="B31">Regulation of the European Parliament and of the Council, 2021</xref>). Moreover, renewable energy is a dynamic force for economic growth in the OECD and G-7 economies (<xref ref-type="bibr" rid="B7">Bekun et al., 2019</xref>). 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.</p>
<p>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 (<xref ref-type="bibr" rid="B9">Bekun, 2022</xref>). For example, the use of green energy leads to a drop in CO<sub>2</sub> emissions (<xref ref-type="bibr" rid="B5">Bekun et al., 2021a</xref>; <xref ref-type="bibr" rid="B20">Irfan et al., 2022</xref>). The development of green energy has contributed significantly to environmental improvements in 85 developed and developing economies (<xref ref-type="bibr" rid="B33">Osobajo et al., 2020</xref>). In addition, several researchers have found a bidirectional causal relationship between green energy and environmental quality (<xref ref-type="bibr" rid="B1">Ahukaemere et al., 2020</xref>; <xref ref-type="bibr" rid="B30">Manta et al., 2020</xref>). However, the empirical results of some studies do not demonstrate a causal relationship between renewable energy consumption and environmental quality (<xref ref-type="bibr" rid="B28">Liu et al., 2021</xref>). Conversely, the exploitation of green energy has reduced CO<sub>2</sub> emissions in five selected African economies (<xref ref-type="bibr" rid="B4">Baydoun and Aga, 2021</xref>). In the face of economic growth trajectories, renewable energy is a panacea for sustainable development.</p>
<p>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 <xref ref-type="bibr" rid="B33">Osobajo et al. (2020)</xref>, have proven the inverted U-shaped relationship between economic growth and CO<sub>2</sub> emissions, but the &#x201c;EKC hypothesis&#x201d; 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 (<xref ref-type="bibr" rid="B29">Liu and Cai, 2018</xref>; <xref ref-type="bibr" rid="B19">Iqbal et al., 2022</xref>). Several studies have validated the EKC hypothesis in a single nation (<xref ref-type="bibr" rid="B27">Liu et al., 2019</xref>; <xref ref-type="bibr" rid="B37">Pata and Isik, 2021</xref>). However, the EKC hypothesis does not hold true for China (<xref ref-type="bibr" rid="B35">Pata and Aydin, 2020</xref>; <xref ref-type="bibr" rid="B36">Pata and Caglar, 2020</xref>). In five EU nations, there was an inverted U-shaped relationship between CO<sub>2</sub> emissions and economic development (<xref ref-type="bibr" rid="B49">Zheng et al., 2019a</xref>; <xref ref-type="bibr" rid="B10">Chen and Ma, 2021</xref>). Some studies found that economic growth boosts the usage of renewable energy (<xref ref-type="bibr" rid="B11">Chi et al., 2021</xref>). 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 (<xref ref-type="bibr" rid="B41">Sarfraz et al., 2021</xref>). In the long run, CO<sub>2</sub> emissions have an N-shaped relationship with the real GDP per capita, rather than the traditional U-shaped curve given by the EKC hypothesis (<xref ref-type="bibr" rid="B32">Olivier and Peters, 2020</xref>). Through a comparative study, the economic growth in Australia accelerated CO<sub>2</sub> emissions. In the long run, Canadian trade appears to increase CO<sub>2</sub> emissions, while economic growth and urban population also boost CO<sub>2</sub> emissions (<xref ref-type="bibr" rid="B43">Shah et al., 2021</xref>).</p>
<p>Based on structural modeling and the GMM estimator, this study used simultaneous equations to analyze the relationship between energy use greenization, CO<sub>2</sub> 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 (<xref ref-type="bibr" rid="B15">Hassan et al., 2019</xref>). The interconnection between economic growth, energy consumption, and CO<sub>2</sub> 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&#x2019;s second-largest producer and consumer of energy and the second-largest emitter of CO<sub>2</sub>. 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&#x2019;s energy use greenization, CO<sub>2</sub> emissions, economic growth, energy conservation, and emission reduction through energy policy and policy formulation.</p>
<p>Compared with that of previous studies, the marginal contribution of this study is as follows: first, based on the existing literature, the Cobb&#x2013;Douglas production function model was used to introduce CO<sub>2</sub> emissions and construct a regression equation for carbon dioxide emissions. Second, an empirical study of the link between energy use greenization, CO<sub>2</sub> 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.</p>
</sec>
<sec id="s3">
<title>Model Building and Data</title>
<sec id="s3-1">
<title>Model Building</title>
<p>To study the relationship between economic growth, CO<sub>2</sub> emissions, and energy use greenization, we used the Cobb&#x2013;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 (<xref ref-type="bibr" rid="B40">Rousseeuw and Yohai, 1984</xref>). Generally, the extended Cobb&#x2013;Douglas production function is expressed as follows:<disp-formula id="e1">
<mml:math id="m1">
<mml:mrow>
<mml:mi>Y</mml:mi>
<mml:mo>&#x3d;</mml:mo>
<mml:mi>A</mml:mi>
<mml:msup>
<mml:mi>K</mml:mi>
<mml:mrow>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
</mml:mrow>
</mml:msup>
<mml:msup>
<mml:mi>L</mml:mi>
<mml:mrow>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
</mml:mrow>
</mml:msup>
<mml:msup>
<mml:mi>E</mml:mi>
<mml:mrow>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>3</mml:mn>
</mml:msub>
</mml:mrow>
</mml:msup>
<mml:msup>
<mml:mi>e</mml:mi>
<mml:mi>&#x3b5;</mml:mi>
</mml:msup>
<mml:mo>,</mml:mo>
</mml:mrow>
</mml:math>
<label>(1)</label>
</disp-formula>where <italic>Y</italic> represents the income level; <italic>A</italic> represents the level of technology; <italic>K</italic> represents the capital; <italic>L</italic> represents the labor; <italic>E</italic> represents energy use; and <italic>&#x3b2;</italic>
<sub>
<italic>1</italic>
</sub>
<italic>, &#x3b2;</italic>
<sub>
<italic>2</italic>
</sub>
<italic>,</italic> and <italic>&#x3b2;</italic>
<sub>
<italic>3,</italic>
</sub> respectively, represent the output elastic coefficients of capital, labor, and energy use. There is a linear relation between CO<sub>2</sub> emissions (CE) and energy use, and at any time: E &#x3d; b.CE at a specific level of technology. Furthermore, some energy economists discovered that renewable energy may reduce CO<sub>2</sub> emissions while also increasing economic growth; hence, renewable energy can be used as a component in the production function model (<xref ref-type="bibr" rid="B53">Tiwari, 2011</xref>; <xref ref-type="bibr" rid="B54">Mahjabeen, 2020</xref>; <xref ref-type="bibr" rid="B55">Venkatraja, 2020</xref>). Therefore, the extended Cobb&#x2013;Douglas production function model is expressed as follows:<disp-formula id="e2">
<mml:math id="m2">
<mml:mrow>
<mml:mi>Y</mml:mi>
<mml:mo>&#x3d;</mml:mo>
<mml:mi>A</mml:mi>
<mml:msup>
<mml:mi>K</mml:mi>
<mml:mrow>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
</mml:mrow>
</mml:msup>
<mml:msup>
<mml:mi>L</mml:mi>
<mml:mrow>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
</mml:mrow>
</mml:msup>
<mml:mi>b</mml:mi>
<mml:mi>C</mml:mi>
<mml:msup>
<mml:mi>E</mml:mi>
<mml:mrow>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>3</mml:mn>
</mml:msub>
</mml:mrow>
</mml:msup>
<mml:mi>R</mml:mi>
<mml:msup>
<mml:mi>E</mml:mi>
<mml:mrow>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>4</mml:mn>
</mml:msub>
</mml:mrow>
</mml:msup>
<mml:msup>
<mml:mi>e</mml:mi>
<mml:mi>&#x3b5;</mml:mi>
</mml:msup>
<mml:mo>.</mml:mo>
</mml:mrow>
</mml:math>
<label>(2)</label>
</disp-formula>
</p>
<p>We considered the logarithm of the Cobb&#x2013;Douglas production function model <xref ref-type="disp-formula" rid="e2">(2)</xref> and obtained the following result:<disp-formula id="e3">
<mml:math id="m3">
<mml:mrow>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:msub>
<mml:mi>Y</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x3d;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>C</mml:mi>
<mml:msub>
<mml:mi>E</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>E</mml:mi>
<mml:mi>U</mml:mi>
<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>3</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:msub>
<mml:mi>L</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>4</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:msub>
<mml:mi>K</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b5;</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
</mml:mrow>
</mml:math>
<label>(3)</label>
</disp-formula>where <italic>&#x3b2;</italic>
<sub>
<italic>0</italic>
</sub> &#x3d; ln <italic>A</italic>; <italic>t</italic> is the subscript; <italic>T</italic> represents the time period; <italic>Y</italic> indicates the income level; <italic>CE</italic> indicates the CO<sub>2</sub> emissions per capita; <italic>EUG</italic> indicates energy use greenization; <italic>K</italic> represents the capital; <italic>L</italic> indicates labor; and <italic>&#x3b5;</italic> 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 CO<sub>2</sub> emissions. These new models were established on the foundation of past theoretical and empirical research. Energy use greenization and CO<sub>2</sub> emissions can be used as the dependent or independent variables. To examine the causality of income, capital (<italic>K</italic>), labor (L), energy use (EU), squared GDP (Y<sup>2</sup>), direct foreign investment (F), trade openness (T), oil prices (OP), financial development (FD), and urbanization (U) are defined as independent variables.</p>
<p>An empirical study of the link between energy use greenization, CO<sub>2</sub> emissions, and economic growth is conducted through the following three function models:<disp-formula id="e4">
<mml:math id="m4">
<mml:mrow>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:msub>
<mml:mi>Y</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x3d;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>C</mml:mi>
<mml:msub>
<mml:mi>E</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>E</mml:mi>
<mml:mi>U</mml:mi>
<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>3</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:msub>
<mml:mi>K</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>4</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:msub>
<mml:mi>L</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b5;</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
</mml:mrow>
</mml:math>
<label>(4)</label>
</disp-formula>
<disp-formula id="e5">
<mml:math id="m5">
<mml:mrow>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>C</mml:mi>
<mml:msub>
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<mml:mo>&#x3d;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:msub>
<mml:mi>Y</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>E</mml:mi>
<mml:mi>U</mml:mi>
<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>3</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:msubsup>
<mml:mi>Y</mml:mi>
<mml:mi>t</mml:mi>
<mml:mn>2</mml:mn>
</mml:msubsup>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>4</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>5</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>6</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:msub>
<mml:mi>F</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b5;</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
</mml:mrow>
</mml:math>
<label>(5)</label>
</disp-formula>
<disp-formula id="e6">
<mml:math id="m6">
<mml:mrow>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>E</mml:mi>
<mml:mi>U</mml:mi>
<mml:msub>
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</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:msub>
<mml:mi>Y</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
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<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>C</mml:mi>
<mml:msub>
<mml:mi>E</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>3</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>O</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>4</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>F</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b2;</mml:mi>
<mml:mn>5</mml:mn>
</mml:msub>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>ln</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:msub>
<mml:mi>T</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b5;</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>.</mml:mo>
</mml:mrow>
</mml:math>
<label>(6)</label>
</disp-formula>
</p>
<p>Model (4) shows that the GDP is affected by CO<sub>2</sub> emissions, renewable energy, labor, and capital (<xref ref-type="bibr" rid="B12">Danish et al., 2017</xref>). Model (5) indicates that the amount of CO<sub>2</sub> emissions is affected by the GDP per capita, renewable energy, energy use, squared GDP per capita, urbanization, and direct foreign investment (<xref ref-type="bibr" rid="B23">Lee and Brahmasrene, 2014</xref>). Model (6) indicates that energy use greenization is affected by the GDP, oil prices, CO<sub>2</sub> emissions, and external trade (<xref ref-type="bibr" rid="B21">Ishaque, 2017</xref>).</p>
<p>Models <xref ref-type="disp-formula" rid="e4">(4</xref>&#x2013;<xref ref-type="disp-formula" rid="e6">6)</xref> 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 <xref ref-type="disp-formula" rid="e4">(4</xref>&#x2013;<xref ref-type="disp-formula" rid="e6">6)</xref>; namely, Hansen&#x2019;s test for excessive identification limits and Durbin&#x2013;Wu&#x2013;Hausman&#x2019;s (DWH) test for examining the issue of endogeneity (<xref ref-type="bibr" rid="B13">Engle and Granger, 1987</xref>). 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.</p>
</sec>
<sec id="s3-2">
<title>Data and Descriptive Statistics</title>
<p>To evaluate models <xref ref-type="disp-formula" rid="e4">(4</xref>&#x2013;<xref ref-type="disp-formula" rid="e6">6)</xref>, 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 <xref ref-type="fig" rid="F1">Figure 1</xref>. <xref ref-type="fig" rid="F1">Figure 1</xref> 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&#x2013;2008) to a rapid increase (2009&#x2013;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&#x2019;s CO<sub>2</sub> 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&#x2019;s per capita GDP also showed a steady growth trend during the sample period, but the growth rate has declined in recent years.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Time series of lnEUG, lnCE, and lnY.</p>
</caption>
<graphic xlink:href="fenvs-10-871001-g001.tif"/>
</fig>
<p>
<xref ref-type="table" rid="T1">Table 1</xref> shows that during the sample period, the GDP per capita ranged from 5,305.8 to 11,817.6 Yuan; the per capita CO<sub>2</sub> emissions ranged from 0.57 to 29.5 tons; and energy use greenization accounted for 0.007&#x2013;0.054% of the total ultimate energy consumption.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Descriptive statistics.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Variable</th>
<th align="center">Mean</th>
<th align="center">SD</th>
<th align="center">Min</th>
<th align="center">Max</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">CE<sub>t</sub>
</td>
<td align="char" char=".">13.160</td>
<td align="char" char=".">12.201</td>
<td align="char" char=".">0.572</td>
<td align="char" char=".">29.51</td>
</tr>
<tr>
<td align="left">Y<sub>t</sub>
</td>
<td align="char" char=".">3651</td>
<td align="char" char=".">2026</td>
<td align="char" char=".">5305.8</td>
<td align="char" char=".">11,817.6</td>
</tr>
<tr>
<td align="left">EUG<sub>t</sub>
</td>
<td align="char" char=".">0.020</td>
<td align="char" char=".">0.011</td>
<td align="char" char=".">0.007</td>
<td align="char" char=".">0.052</td>
</tr>
<tr>
<td align="left">FD<sub>t</sub>
</td>
<td align="char" char=".">0.412</td>
<td align="char" char=".">0.132</td>
<td align="char" char=".">0.189</td>
<td align="char" char=".">0.603</td>
</tr>
<tr>
<td align="left">F<sub>t</sub>
</td>
<td align="char" char=".">1.756</td>
<td align="char" char=".">2.632</td>
<td align="char" char=".">-1.321</td>
<td align="char" char=".">8.511</td>
</tr>
<tr>
<td align="left">T<sub>t</sub>
</td>
<td align="char" char=".">75.111</td>
<td align="char" char=".">12.123</td>
<td align="char" char=".">56.122</td>
<td align="char" char=".">97.010</td>
</tr>
<tr>
<td align="left">L<sub>t</sub>
</td>
<td align="char" char=".">0.455</td>
<td align="char" char=".">0.275</td>
<td align="char" char=".">0.055</td>
<td align="char" char=".">1.742</td>
</tr>
<tr>
<td align="left">K<sub>t</sub>
</td>
<td align="char" char=".">21.154</td>
<td align="char" char=".">3.218</td>
<td align="char" char=".">18.556</td>
<td align="char" char=".">32.852</td>
</tr>
<tr>
<td align="left">OP<sub>t</sub>
</td>
<td align="char" char=".">47.701</td>
<td align="char" char=".">30.102</td>
<td align="char" char=".">15.521</td>
<td align="char" char=".">100.514</td>
</tr>
<tr>
<td align="left">U<sub>t</sub>
</td>
<td align="char" char=".">0.445</td>
<td align="char" char=".">0.273</td>
<td align="char" char=".">0.054</td>
<td align="char" char=".">1.746</td>
</tr>
<tr>
<td align="left">EU<sub>t</sub>
</td>
<td align="char" char=".">115.43</td>
<td align="char" char=".">16.820</td>
<td align="char" char=".">83.714</td>
<td align="char" char=".">149.904</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>
<xref ref-type="table" rid="T2">Table 2</xref> shows that the GDP and CO<sub>2</sub> emissions per capita showed the largest correlation, whereas the urbanization variable showed the lowest. Moreover, there is a significant negative relationship between CO<sub>2</sub> 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 CO<sub>2</sub> emissions per capita and increase the GDP per capita.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Variable correlations.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Variable</th>
<th align="center">CE<sub>t</sub>
</th>
<th align="center">Y<sub>t</sub>
</th>
<th align="center">EUG<sub>t</sub>
</th>
<th align="center">FD<sub>t</sub>
</th>
<th align="center">F<sub>t</sub>
</th>
<th align="center">T<sub>t</sub>
</th>
<th align="center">L<sub>t</sub>
</th>
<th align="center">K<sub>t</sub>
</th>
<th align="center">OP<sub>t</sub>
</th>
<th align="center">U<sub>t</sub>
</th>
<th align="center">EU<sub>t</sub>
</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">CE<sub>t</sub>
</td>
<td align="char" char=".">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Y<sub>t</sub>
</td>
<td align="char" char=".">0.701<sup>&#x2a;&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">EUG<sub>t</sub>
</td>
<td align="char" char=".">-0.615<sup>&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.150</td>
<td align="char" char=".">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">FD<sub>t</sub>
</td>
<td align="char" char=".">0.691<sup>&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.521<sup>&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.705<sup>&#x2a;</sup>
</td>
<td align="char" char=".">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">F<sub>t</sub>
</td>
<td align="char" char=".">0.284</td>
<td align="char" char=".">0.163</td>
<td align="char" char=".">0.322</td>
<td align="char" char=".">0.540<sup>&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">T<sub>t</sub>
</td>
<td align="char" char=".">0.558<sup>&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.411</td>
<td align="char" char=".">0.269</td>
<td align="char" char=".">0.628<sup>&#x2a;</sup>
</td>
<td align="char" char=".">0.728<sup>&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">L<sub>t</sub>
</td>
<td align="char" char=".">0.420</td>
<td align="char" char=".">0.499</td>
<td align="char" char=".">0.498</td>
<td align="char" char=".">0.702</td>
<td align="char" char=".">0.309</td>
<td align="char" char=".">0.436</td>
<td align="char" char=".">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">K<sub>t</sub>
</td>
<td align="char" char=".">0.579</td>
<td align="char" char=".">0.620<sup>&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.371</td>
<td align="char" char=".">0.624</td>
<td align="char" char=".">0.477</td>
<td align="char" char=".">0.415</td>
<td align="char" char=".">0.535</td>
<td align="char" char=".">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">OP<sub>t</sub>
</td>
<td align="char" char=".">0.561<sup>&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.563<sup>&#x2a;&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.620<sup>&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.597<sup>&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.581<sup>&#x2a;</sup>
</td>
<td align="char" char=".">0633<sup>&#x2a;&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.699<sup>&#x2a;</sup>
</td>
<td align="char" char=".">0.584<sup>&#x2a;&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">1</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">U<sub>t</sub>
</td>
<td align="char" char=".">0.401</td>
<td align="char" char=".">0.519</td>
<td align="char" char=".">0.310</td>
<td align="char" char=".">0.400</td>
<td align="char" char=".">0.381</td>
<td align="char" char=".">0.469</td>
<td align="char" char=".">0.601</td>
<td align="char" char=".">0.506</td>
<td align="char" char=".">0.604<sup>&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">1</td>
<td align="left"/>
</tr>
<tr>
<td align="left">EU<sub>t</sub>
</td>
<td align="char" char=".">0.661<sup>&#x2a;&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.401<sup>&#x2a;&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.450<sup>&#x2a;</sup>
</td>
<td align="char" char=".">0.489</td>
<td align="char" char=".">0.503<sup>&#x2a;&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.554<sup>&#x2a;&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.400<sup>&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.509<sup>&#x2a;</sup>
</td>
<td align="char" char=".">0.593<sup>&#x2a;&#x2a;&#x2a;</sup>
</td>
<td align="char" char=".">0.495<sup>&#x2a;</sup>
</td>
<td align="char" char=".">1</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Indicates significant paths: &#x2a;<italic>p</italic> &#x003C; 0.05, &#x2a;&#x2a;<italic>p</italic> &#x003C; 0.01, &#x2a;&#x2a;&#x2a;<italic>p</italic> &#x003C; 0.001</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec sec-type="results|discussion" id="s4">
<title>Empirical Results and Discussion</title>
<p>Through Hansen&#x2019;s test and the DWH test, the evaluation coefficients of models <xref ref-type="disp-formula" rid="e4">(4</xref>&#x2013;<xref ref-type="disp-formula" rid="e6">6)</xref> are presented in <xref ref-type="table" rid="T3">Table 3</xref>. The empirical findings of model <xref ref-type="disp-formula" rid="e4">(4)</xref> indicate that CO<sub>2</sub> emissions show a significant negative correlation with the GDP. If the per capita CO<sub>2</sub> emissions increase by 1%, the economic growth is expected to decrease by about 0.1%. This result was confirmed by the survey results of <xref ref-type="bibr" rid="B39">Pata (2018)</xref>, who showed that Turkey&#x2019;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 CO<sub>2</sub> emissions. However, China&#x2019;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 (<xref ref-type="bibr" rid="B49">Zheng et al., 2019a</xref>; <xref ref-type="bibr" rid="B18">Iqbal et al., 2019</xref>). In addition, the capital and labor force coefficients show significantly positive and negative correlations with the economic growth, respectively.</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Simultaneous equation generalized method of moment estimation for the models.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th colspan="7" align="left">Dependent variables</th>
</tr>
<tr>
<th rowspan="2" align="left">Independent variable</th>
<th colspan="2" align="center">Y (GDP per capita) model <xref ref-type="disp-formula" rid="e4">(4)</xref>
</th>
<th colspan="2" align="center">CO<sub>2</sub> (CO<sub>2</sub> emissions) model <xref ref-type="disp-formula" rid="e5">(5)</xref>
</th>
<th colspan="2" align="center">EUG (EU greenization) model <xref ref-type="disp-formula" rid="e6">(6)</xref>
</th>
</tr>
<tr>
<th align="center">Coef</th>
<th align="center">P</th>
<th align="center">Coef</th>
<th align="center">P</th>
<th align="center">Coef</th>
<th align="center">P</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Y (GDP per capita)</td>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">0.701</td>
<td align="char" char="(">(0.000)</td>
<td align="char" char=".">0.221</td>
<td align="char" char="(">(0.031)</td>
</tr>
<tr>
<td align="left">Y<sup>2</sup> (squared GDP)</td>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">-0.092</td>
<td align="char" char="(">(0.061)</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">CE (CO<sub>2</sub> emissions)</td>
<td align="char" char=".">-0.102</td>
<td align="char" char="(">(0.019)</td>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">0.245</td>
<td align="char" char="(">(0.000)</td>
</tr>
<tr>
<td align="left">EUG (EU greenization)</td>
<td align="char" char=".">0.063</td>
<td align="char" char="(">(0.000)</td>
<td align="char" char=".">-0.050</td>
<td align="char" char="(">(0.000)</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">K (capital)</td>
<td align="char" char=".">0.412</td>
<td align="char" char="(">(0.000)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">L (labor)</td>
<td align="char" char=".">-0.192</td>
<td align="char" char="(">(0.059)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">EU (energy use)</td>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">0.411</td>
<td align="char" char="(">(0.000)</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">U (urbanization)</td>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">0.152</td>
<td align="char" char="(">(0.022)</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">F (foreign direct investment)</td>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">0.111</td>
<td align="char" char="(">(0.043)</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">OP (oil prices)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">0.109</td>
<td align="char" char="(">(0.125)</td>
</tr>
<tr>
<td align="left">FD (financial development)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">0.210</td>
<td align="char" char="(">(0.029)</td>
</tr>
<tr>
<td align="left">T (trade openness)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">0.112</td>
<td align="char" char="(">(0.098)</td>
</tr>
<tr>
<td align="left">Constant</td>
<td align="char" char=".">7.211</td>
<td align="char" char="(">(0.000)</td>
<td align="char" char=".">4.521</td>
<td align="char" char="(">(0.009)</td>
<td align="char" char=".">11.001</td>
<td align="char" char="(">(0.000)</td>
</tr>
<tr>
<td align="left">Hansen&#x2019;s test (p)</td>
<td align="char" char=".">13.216</td>
<td align="char" char="(">(0.674)</td>
<td align="char" char=".">20.514</td>
<td align="char" char="(">(0.301)</td>
<td align="char" char=".">18.011</td>
<td align="char" char="(">(0.430)</td>
</tr>
<tr>
<td align="left">DWH test (p)</td>
<td align="char" char=".">5.001</td>
<td align="char" char="(">(0.032)</td>
<td align="char" char=".">10.401</td>
<td align="char" char="(">(0.003)</td>
<td align="char" char=".">6.331</td>
<td align="char" char="(">(0.033)</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>The empirical results of model <xref ref-type="disp-formula" rid="e5">(5)</xref> show that the per capita GDP influences CO<sub>2</sub> emissions per capita. The research shows that there is a positive relationship between the per capita GDP and per capita CO<sub>2</sub> emissions. If the GDP per capita increases by 0.1%, the CO<sub>2</sub> 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 <xref ref-type="bibr" rid="B17">H&#xf6;hne et al. (2011)</xref> for 15 European countries. We found a negative correlation between energy use greenization and CO<sub>2</sub> emissions. If energy use greenization increases by 1%, CO<sub>2</sub> emissions per capita are expected to decrease by about 0.05%. This result is the same as that in the references (<xref ref-type="bibr" rid="B44">Shahzad et al., 2017</xref>). However, our result contradicts the findings of one of the references (<xref ref-type="bibr" rid="B42">Shabani and Shahnazi, 2019</xref>). Energy use shows a significant positive correlation with CO<sub>2</sub> emissions per capita. If energy use increases by 1%, the CO<sub>2</sub> emissions per capita are expected to rise by about 0.41%. Similarly, urbanization and trade openness have positive correlations with CO<sub>2</sub> emissions per capita.</p>
<p>Finally, the empirical findings of model <xref ref-type="disp-formula" rid="e6">(6)</xref> 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 CO<sub>2</sub> emissions per capita and the demand for renewable energy. If CO<sub>2</sub> emissions per capita increase by 1%, energy use greenization is expected to increase by about 0.24%. These results show that CO<sub>2</sub> emissions per capita increase environmental degradation and promote the production and consumption of carbon-free sustainable energy, while lower CO<sub>2</sub> 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.</p>
<p>The aforementioned results indicated that (i) energy use greenization promotes per capita GDP growth; (ii) increased economic growth leads to higher CO<sub>2</sub> emissions, and continued increases in CO<sub>2</sub> emissions may reduce economic growth; and (iii) increased CO<sub>2</sub> emissions can boost the demand for renewable energy, thereby reducing CO<sub>2</sub> emissions.</p>
</sec>
<sec id="s5">
<title>Discussion and Conclusion</title>
<p>The main objective of this study was to investigate the relationship between CO<sub>2</sub> emissions, energy use greenization, and economic growth. Our findings show that energy use greenization may have narrowed the gap between China&#x2019;s economic growth and CO<sub>2</sub> 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, CO<sub>2</sub> emissions, and GDP. Our empirical results show that energy use greenization can promote economic growth. We also found that economic growth leads to increased CO<sub>2</sub> emissions, which promotes energy use greenization. Our findings also emphasize that energy use greenization can narrow the gap between China&#x2019;s economic growth and CO<sub>2</sub> emissions.</p>
<p>The key policy implications emerging from the aforementioned results are as follows. First, we found a significant relationship between the GDP and CO<sub>2</sub> emissions. The results indicate that economic growth leads to an increase in CO<sub>2</sub> emissions, and the continuous increase of CO<sub>2</sub> 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&#x2019;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 CO<sub>2</sub> emission mechanism. Increased CO<sub>2</sub> emissions can increase the demand for energy use greenization, thereby continuously reducing CO<sub>2</sub> emissions. Second, there is a significant relationship between energy use greenization and CO<sub>2</sub> emissions. An increase in CO<sub>2</sub> emissions can increase the demand for energy use greenization and continuously reduce CO<sub>2</sub> emissions. High fossil fuel consumption and the sharp increase in CO<sub>2</sub> emissions have brought severe challenges to the sustainable development of China&#x2019;s economy. Energy structure transformation and CO<sub>2</sub> 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&#x2019;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.</p>
</sec>
<sec id="s6">
<title>Suggestions and Policy Implementations</title>
<p>We need to acknowledge the positive role of energy use greenization in reducing CO<sub>2</sub> 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.</p>
<p>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&#x2019;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.</p>
<p>This study discusses the relationship between energy use greenization, CO<sub>2</sub> 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.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s7">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s8">
<title>Author Contributions</title>
<p>WX: writing an initial draft. KI coordinated the work and writing&#x2014;analysis. YW: proofreading.</p>
</sec>
<sec sec-type="COI-statement" id="s9">
<title>Conflict of Interest</title>
<p>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.</p>
</sec>
<sec sec-type="disclaimer" id="s10">
<title>Publisher&#x2019;s Note</title>
<p>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.</p>
</sec>
<ref-list>
<title>References</title>
<ref id="B1">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ahukaemere</surname>
<given-names>C. M.</given-names>
</name>
<name>
<surname>Okolo</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Aririguzo</surname>
<given-names>B. N.</given-names>
</name>
<name>
<surname>Uchenna</surname>
<given-names>O. S.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Tropical Soil Carbon Stocks in Relation to Fallow Age and Soil Depth</article-title>. <source>Malays. J. Sustain. Agric.</source> <volume>4</volume>, <fpage>05</fpage>&#x2013;<lpage>09</lpage>. <pub-id pub-id-type="doi">10.26480/mjsa.01.2020.05.09</pub-id> </citation>
</ref>
<ref id="B2">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Anwar</surname>
<given-names>J.</given-names>
</name>
</person-group> (<year>2016</year>). <article-title>Analysis of Energy Security, Environmental Emission and Fuel Import Costs under Energy Import Reduction Targets: A Case of Pakistan</article-title>. <source>Renew. Sustain. Energy Rev.</source> <volume>65</volume>, <fpage>1065</fpage>&#x2013;<lpage>1078</lpage>. <pub-id pub-id-type="doi">10.1016/j.rser.2016.07.037</pub-id> </citation>
</ref>
<ref id="B3">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Asongu</surname>
<given-names>S. A.</given-names>
</name>
<name>
<surname>Le Roux</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Biekpe</surname>
<given-names>N.</given-names>
</name>
</person-group> (<year>2018</year>). <article-title>Enhancing ICT for Environmental Sustainability in Sub-Saharan Africa</article-title>. <source>Technol. Forecast. Soc. Change</source> <volume>127</volume>, <fpage>209</fpage>&#x2013;<lpage>216</lpage>. <pub-id pub-id-type="doi">10.1016/j.techfore.2017.09.022</pub-id> </citation>
</ref>
<ref id="B4">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Baydoun</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Aga</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>The Effect of Energy Consumption and Economic Growth on Environmental Sustainability in the Gcc Countries: Does Financial Development Matter?</article-title> <source>Energies</source> <volume>14</volume>, <fpage>5897</fpage>. <pub-id pub-id-type="doi">10.3390/en14185897</pub-id> </citation>
</ref>
<ref id="B5">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bekun</surname>
<given-names>F. V.</given-names>
</name>
<name>
<surname>Alola</surname>
<given-names>A. A.</given-names>
</name>
<name>
<surname>Gyamfi</surname>
<given-names>B. A.</given-names>
</name>
<name>
<surname>Ampomah</surname>
<given-names>A. B.</given-names>
</name>
</person-group> (<year>2021a</year>). <article-title>The Environmental Aspects of Conventional and Clean Energy Policy in Sub-Saharan Africa: Is N-Shaped Hypothesis Valid?</article-title> <source>Environ. Sci. Pollut. Res.</source> <volume>28</volume>, <fpage>66695</fpage>&#x2013;<lpage>66708</lpage>. <pub-id pub-id-type="doi">10.1007/s11356-021-14758-w</pub-id> </citation>
</ref>
<ref id="B6">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bekun</surname>
<given-names>F. V.</given-names>
</name>
<name>
<surname>Alola</surname>
<given-names>A. A.</given-names>
</name>
<name>
<surname>Gyamfi</surname>
<given-names>B. A.</given-names>
</name>
<name>
<surname>Yaw</surname>
<given-names>S. S.</given-names>
</name>
</person-group> (<year>2021b</year>). <article-title>The Relevance of EKC Hypothesis in Energy Intensity Real-Output Trade-Off for Sustainable Environment in EU-27</article-title>. <source>Environ. Sci. Pollut. Res.</source> <volume>28</volume>, <fpage>51137</fpage>&#x2013;<lpage>51148</lpage>. <pub-id pub-id-type="doi">10.1007/s11356-021-14251-4</pub-id> </citation>
</ref>
<ref id="B7">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bekun</surname>
<given-names>F. V.</given-names>
</name>
<name>
<surname>Emir</surname>
<given-names>F.</given-names>
</name>
<name>
<surname>Sarkodie</surname>
<given-names>S. A.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Another Look at the Relationship between Energy Consumption, Carbon Dioxide Emissions, and Economic Growth in South Africa</article-title>. <source>Sci. Total Environ.</source> <volume>655</volume>, <fpage>759</fpage>&#x2013;<lpage>765</lpage>. <pub-id pub-id-type="doi">10.1016/j.scitotenv.2018.11.271</pub-id> </citation>
</ref>
<ref id="B8">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bekun</surname>
<given-names>F. V.</given-names>
</name>
<name>
<surname>Gyamfi</surname>
<given-names>B. A.</given-names>
</name>
<name>
<surname>Onifade</surname>
<given-names>S. T.</given-names>
</name>
<name>
<surname>Agboola</surname>
<given-names>M. O.</given-names>
</name>
</person-group> (<year>2021c</year>). <article-title>Beyond the Environmental Kuznets Curve in E7 Economies: Accounting for the Combined Impacts of Institutional Quality and Renewables</article-title>. <source>J. Clean. Prod.</source> <volume>314</volume>, <fpage>127924</fpage>. <pub-id pub-id-type="doi">10.1016/j.jclepro.2021.127924</pub-id> </citation>
</ref>
<ref id="B9">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bekun</surname>
<given-names>F. V.</given-names>
</name>
</person-group> (<year>2022</year>). <article-title>Mitigating Emissions in India: Accounting for the Role of Real Income, Renewable Energy Consumption and Investment in Energy</article-title>. <source>Ijeep</source> <volume>12</volume>, <fpage>188</fpage>&#x2013;<lpage>192</lpage>. <pub-id pub-id-type="doi">10.32479/ijeep.12652</pub-id> </citation>
</ref>
<ref id="B10">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Chen</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Ma</surname>
<given-names>Y.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Does Green Investment Improve Energy Firm Performance?</article-title> <source>Energy Policy</source> <volume>153</volume>, <fpage>112252</fpage>. <pub-id pub-id-type="doi">10.1016/j.enpol.2021.112252</pub-id> </citation>
</ref>
<ref id="B11">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Chi</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Bai</surname>
<given-names>G.</given-names>
</name>
<name>
<surname>Li</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Chen</surname>
<given-names>B.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Research on the Coordination of Energy in China&#x27;s Economic Growth</article-title>. <source>PLoS One</source> <volume>16</volume>, <fpage>e0251824</fpage>&#x2013;<lpage>20</lpage>. <pub-id pub-id-type="doi">10.1371/journal.pone.0251824</pub-id> </citation>
</ref>
<ref id="B12">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Danish</surname>
</name>
<etal/>
</person-group> (<year>2017</year>). <article-title>&#x2018;Role of renewable energy and non-renewable energy consumption on EKC: Evidence from Pakistan&#x2019;</article-title>. <source>Journal of Cleaner Production</source> <volume>156</volume>, pp. <fpage>855</fpage>&#x2013;<lpage>864</lpage>. <pub-id pub-id-type="doi">10.1016/j.jclepro.2017.03.203</pub-id> </citation>
</ref>
<ref id="B13">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Engle</surname>
<given-names>R. F.</given-names>
</name>
<name>
<surname>Granger</surname>
<given-names>C. W. J.</given-names>
</name>
</person-group> (<year>1987</year>). <article-title>Co-Integration and Error Correction: Representation, Estimation, and Testing</article-title>. <source>Econometrica</source> <volume>55</volume>, <fpage>251</fpage>. <pub-id pub-id-type="doi">10.2307/1913236</pub-id> </citation>
</ref>
<ref id="B14">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Fang</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Razzaq</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Mohsin</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Irfan</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2022</year>). <article-title>Spatial Spillovers and Threshold Effects of Internet Development and Entrepreneurship on Green Innovation Efficiency in China</article-title>. <source>Technol. Soc.</source> <volume>68</volume>, <fpage>101844</fpage>. <pub-id pub-id-type="doi">10.1016/j.techsoc.2021.101844</pub-id> </citation>
</ref>
<ref id="B15">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Hassan</surname>
<given-names>S. T.</given-names>
</name>
<name>
<surname>Xia</surname>
<given-names>E.</given-names>
</name>
<name>
<surname>Huang</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Khan</surname>
<given-names>N. H.</given-names>
</name>
<name>
<surname>Iqbal</surname>
<given-names>K.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Natural Resources , Globalization , and Economic Growth : Evidence from Pakistan</article-title>. <source>Environ. Sci. Pollut. Res.</source> <volume>26</volume>, <fpage>15527</fpage>&#x2013;<lpage>15534</lpage>. <pub-id pub-id-type="doi">10.1007/s11356-019-04890-z</pub-id> </citation>
</ref>
<ref id="B16">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>He</surname>
<given-names>G.</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>X.</given-names>
</name>
<name>
<surname>Cui</surname>
<given-names>Z.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Achieving Global Food Security by Focusing on Nitrogen Efficiency Potentials and Local Production</article-title>. <source>Glob. Food Secur.</source> <volume>29</volume>, <fpage>100536</fpage>. <pub-id pub-id-type="doi">10.1016/j.gfs.2021.100536</pub-id> </citation>
</ref>
<ref id="B17">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>H&#xf6;hne</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Blum</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Fuglestvedt</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Skeie</surname>
<given-names>R. B.</given-names>
</name>
<name>
<surname>Kurosawa</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Hu</surname>
<given-names>G.</given-names>
</name>
<etal/>
</person-group> (<year>2011</year>). <article-title>Contributions of Individual Countries&#x27; Emissions to Climate Change and Their Uncertainty</article-title>. <source>Clim. Change</source> <volume>106</volume>, <fpage>359</fpage>&#x2013;<lpage>391</lpage>. <pub-id pub-id-type="doi">10.1007/s10584-010-9930-6</pub-id> </citation>
</ref>
<ref id="B18">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Iqbal</surname>
<given-names>K.</given-names>
</name>
<name>
<surname>Hassan</surname>
<given-names>S. T.</given-names>
</name>
<name>
<surname>Peng</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Khurshaid</surname>
</name>
</person-group> (<year>2019</year>). <article-title>Analyzing the Role of Information and Telecommunication Technology in Human Development: Panel Data Analysis</article-title>. <source>Environ. Sci. Pollut. Res.</source> <volume>26</volume>, <fpage>15153</fpage>&#x2013;<lpage>15161</lpage>. <pub-id pub-id-type="doi">10.1007/s11356-019-04918-4</pub-id> </citation>
</ref>
<ref id="B19">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Iqbal</surname>
<given-names>K.</given-names>
</name>
<name>
<surname>Hassan</surname>
<given-names>S. T.</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Shah</surname>
<given-names>M. H.</given-names>
</name>
<name>
<surname>Syed</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Khurshaid</surname>
<given-names>K.</given-names>
</name>
</person-group> (<year>2022</year>). <article-title>To Achieve Carbon Neutrality Targets in Pakistan: New Insights of Information and Communication Technology and Economic Globalization</article-title>. <source>Front. Environ. Sci.</source> <volume>9</volume>, <fpage>1</fpage>&#x2013;<lpage>10</lpage>. <pub-id pub-id-type="doi">10.3389/fenvs.2021.805360</pub-id> </citation>
</ref>
<ref id="B20">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Irfan</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Elavarasan</surname>
<given-names>R. M.</given-names>
</name>
<name>
<surname>Ahmad</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Mohsin</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Dagar</surname>
<given-names>V.</given-names>
</name>
<name>
<surname>Hao</surname>
<given-names>Y.</given-names>
</name>
</person-group> (<year>2022</year>). <article-title>Prioritizing and Overcoming Biomass Energy Barriers: Application of AHP and G-TOPSIS Approaches</article-title>. <source>Technol. Forecast. Soc. Change</source> <volume>177</volume>, <fpage>121524</fpage>. <pub-id pub-id-type="doi">10.1016/j.techfore.2022.121524</pub-id> </citation>
</ref>
<ref id="B21">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ishaque</surname>
<given-names>H.</given-names>
</name>
</person-group> (<year>2017</year>). <article-title>Quantifying the Potential Impact of Pakistan&#x27;s GHG Mitigation Policies for Coal-Fired Power Plants</article-title>. <source>Energy Procedia</source> <volume>142</volume>, <fpage>2809</fpage>&#x2013;<lpage>2815</lpage>. <pub-id pub-id-type="doi">10.1016/j.egypro.2017.12.426</pub-id> </citation>
</ref>
<ref id="B22">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Lan</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Zhao</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Jiao</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Khan</surname>
<given-names>M. N.</given-names>
</name>
<name>
<surname>Sial</surname>
<given-names>T. A.</given-names>
</name>
<etal/>
</person-group> (<year>2021</year>). <article-title>Long-term Vegetation Restoration Increases Deep Soil Carbon Storage in the Northern Loess Plateau</article-title>. <source>Sci. Rep.</source> <volume>11</volume>, <fpage>1</fpage>&#x2013;<lpage>11</lpage>. <pub-id pub-id-type="doi">10.1038/s41598-021-93157-0</pub-id> </citation>
</ref>
<ref id="B23">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Lee</surname>
<given-names>J. W.</given-names>
</name>
<name>
<surname>Brahmasrene</surname>
<given-names>T.</given-names>
</name>
</person-group> (<year>2014</year>). <article-title>ICT, CO<sub>2</sub> Emissions and Economic Growth: Evidence from a Panel of ASEAN</article-title>. <source>Glob. Econ. Rev.</source> <volume>43</volume>, <fpage>93</fpage>&#x2013;<lpage>109</lpage>. <pub-id pub-id-type="doi">10.1080/1226508X.2014.917803</pub-id> </citation>
</ref>
<ref id="B24">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Li</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Che</surname>
<given-names>S.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Synergistic Effect of Carbon Trading Scheme on Carbon Dioxide and Atmospheric Pollutants</article-title>. <source>Sustainability</source> <volume>13</volume>, <fpage>5403</fpage>. <pub-id pub-id-type="doi">10.3390/su13105403</pub-id> </citation>
</ref>
<ref id="B25">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Liang</surname>
<given-names>X.</given-names>
</name>
<name>
<surname>Lu</surname>
<given-names>T.</given-names>
</name>
<name>
<surname>Yishake</surname>
<given-names>G.</given-names>
</name>
</person-group> (<year>2022</year>). <article-title>How to Promote Residents&#x27; Use of Green Space: An Empirically Grounded Agent-Based Modeling Approach</article-title>. <source>Urban For. Urban Green.</source> <volume>67</volume>, <fpage>127435</fpage>. <pub-id pub-id-type="doi">10.1016/j.ufug.2021.127435</pub-id> </citation>
</ref>
<ref id="B26">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Liu</surname>
<given-names>J.-L.</given-names>
</name>
<name>
<surname>Ma</surname>
<given-names>C.-Q.</given-names>
</name>
<name>
<surname>Ren</surname>
<given-names>Y.-S.</given-names>
</name>
<name>
<surname>Zhao</surname>
<given-names>X.-W.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Do Real Output and Renewable Energy Consumption BRICS Countries</article-title>. <source>Energies</source>, <fpage>1</fpage> </citation>
</ref>
<ref id="B27">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Liu</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Yang</surname>
<given-names>Q.</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Sun</surname>
<given-names>W.</given-names>
</name>
<name>
<surname>Xu</surname>
<given-names>Y.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Analysis of CO<sub>2</sub> Emissions in China&#x27;s Manufacturing Industry Based on Extended Logarithmic Mean Division Index Decomposition</article-title>. <source>Sustainability</source> <volume>11</volume>, <fpage>226</fpage>. <pub-id pub-id-type="doi">10.3390/su11010226</pub-id> </citation>
</ref>
<ref id="B28">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Liu</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Jiao</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Zhao</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>K.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Impact of Greenization on the Marginal Utility of Intensity of Carbon Emissions and Factors Affecting it in China</article-title>. <source>Energy Eng. J. Assoc. Energy Eng.</source> <volume>118</volume>, <fpage>363</fpage>&#x2013;<lpage>378</lpage>. <pub-id pub-id-type="doi">10.32604/EE.2021.013472</pub-id> </citation>
</ref>
<ref id="B29">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Liu</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Cai</surname>
<given-names>B.</given-names>
</name>
</person-group> (<year>2018</year>). <article-title>High-resolution Carbon Emissions Data for Chinese Cities</article-title>. <source>Belfer Cent. Sci. Int. Aff.</source> <comment>Cambridge, Mass Harvard Univ</comment>. <fpage>1</fpage>&#x2013;<lpage>29</lpage>. </citation>
</ref>
<ref id="B30">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Manta</surname>
<given-names>A. G.</given-names>
</name>
<name>
<surname>Florea</surname>
<given-names>N. M.</given-names>
</name>
<name>
<surname>B&#x103;d&#xee;rcea</surname>
<given-names>R. M.</given-names>
</name>
<name>
<surname>Popescu</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>C&#xee;rciumaru</surname>
<given-names>D.</given-names>
</name>
<name>
<surname>Doran</surname>
<given-names>M. D.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>The Nexus between Carbon Emissions, Energy Use, Economic Growth and Financial Development: Evidence from Central and Eastern European Countries</article-title>. <source>Sustainability</source> <volume>12</volume>, <fpage>7747</fpage>. <pub-id pub-id-type="doi">10.3390/SU12187747</pub-id> </citation>
</ref>
<ref id="B32">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Olivier</surname>
<given-names>J. G. J.</given-names>
</name>
<name>
<surname>Peters</surname>
<given-names>J. A. H. W.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Trends in Global CO<sub>2</sub> and Total Greenhouse Gas Emissions</article-title>. <source>PBL Neth. Environ. Assess. Agency</source> <volume>2020</volume>, <fpage>70</fpage>. </citation>
</ref>
<ref id="B33">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Osobajo</surname>
<given-names>O. A.</given-names>
</name>
<name>
<surname>Otitoju</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Otitoju</surname>
<given-names>M. A.</given-names>
</name>
<name>
<surname>Oke</surname>
<given-names>A.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>The Impact of Energy Consumption and Economic Growth on Carbon Dioxide Emissions</article-title>. <source>Sustainability</source> <volume>12</volume>, <fpage>7965</fpage>. <pub-id pub-id-type="doi">10.3390/SU12197965</pub-id> </citation>
</ref>
<ref id="B34">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Pata</surname>
<given-names>U. K.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Linking Renewable Energy, Globalization, Agriculture, CO<sub>2</sub> Emissions and Ecological Frootprint in BRIC Countries: a Sustainability Perspective</article-title>. <source>Renew. Energy</source> <volume>173</volume>, <fpage>197</fpage>&#x2013;<lpage>208</lpage>. <pub-id pub-id-type="doi">10.1016/j.renene.2021.03.125</pub-id> </citation>
</ref>
<ref id="B35">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Pata</surname>
<given-names>U. K.</given-names>
</name>
<name>
<surname>Aydin</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Testing the EKC Hypothesis for the Top Six Hydropower Energy-Consuming Countries: Evidence from Fourier Bootstrap ARDL Procedure</article-title>. <source>J. Clean. Prod.</source> <volume>264</volume>, <fpage>121699</fpage>. <pub-id pub-id-type="doi">10.1016/j.jclepro.2020.121699</pub-id> </citation>
</ref>
<ref id="B36">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Pata</surname>
<given-names>U. K.</given-names>
</name>
<name>
<surname>Caglar</surname>
<given-names>A. E.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Investigating the EKC Hypothesis with Renewable Energy Consumption, Human Capital, Globalization and Trade Openness for China: Evidence from Augmented ARDL Approach with a Structural Break</article-title>. <source>energy</source> <volume>216</volume>, <fpage>119220</fpage>. <pub-id pub-id-type="doi">10.1016/j.energy.2020.119220</pub-id> </citation>
</ref>
<ref id="B37">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Pata</surname>
<given-names>U. K.</given-names>
</name>
<name>
<surname>Isik</surname>
<given-names>C.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Determinants of the Load Capacity Factor in China: A Novel Dynamic ARDL Approach for Ecological Footprint Accounting</article-title>. <source>Resour. Policy</source> <volume>74</volume>, <fpage>102313</fpage>. <pub-id pub-id-type="doi">10.1016/j.resourpol.2021.102313</pub-id> </citation>
</ref>
<ref id="B38">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Pata</surname>
<given-names>U. K.</given-names>
</name>
<name>
<surname>Kumar</surname>
<given-names>A.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>The Influence of Hydropower and Coal Consumption on Greenhouse Gas Emissions: A Comparison between China and India</article-title>. <source>Water</source> <volume>13</volume> (<issue>10</issue>), <fpage>1387</fpage>. <pub-id pub-id-type="doi">10.3390/w13101387</pub-id> </citation>
</ref>
<ref id="B39">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Pata</surname>
<given-names>U. K.</given-names>
</name>
</person-group> (<year>2018</year>). <article-title>Renewable Energy Consumption, Urbanization, Financial Development, Income and CO<sub>2</sub> Emissions in Turkey: Testing EKC Hypothesis with Structural Breaks</article-title>. <source>J. Clean. Prod.</source> <volume>187</volume>, <fpage>770</fpage>&#x2013;<lpage>779</lpage>. <pub-id pub-id-type="doi">10.1016/j.jclepro.2018.03.236</pub-id> </citation>
</ref>
<ref id="B31">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Regulation of the European Parliament and of the Council</surname>
</name>
</person-group> (<year>2021</year>). <article-title>Regulation of the European Parliament and of the Council Amending</article-title>. <source>Eur. Comm.</source> <volume>0197</volume>. </citation>
</ref>
<ref id="B40">
<citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname>Rousseeuw</surname>
<given-names>P.</given-names>
</name>
<name>
<surname>Yohai</surname>
<given-names>V.</given-names>
</name>
</person-group>, <year>1984</year>, <source>Robust Regression by Means of S-Estimators</source>. <fpage>256</fpage>&#x2013;<lpage>272</lpage>. <pub-id pub-id-type="doi">10.1007/978-1-4615-7821-5_15</pub-id> </citation>
</ref>
<ref id="B41">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Sarfraz</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Ivascu</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Belu</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Artene</surname>
<given-names>A.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Accentuating the Interconnection between Business Sustainability and Organizational Performance in the Context of the Circular Economy: The Moderating Role of Organizational Competitiveness</article-title>. <source>Bus. Strat. Env.</source> <volume>30</volume>, <fpage>2108</fpage>&#x2013;<lpage>2118</lpage>. <pub-id pub-id-type="doi">10.1002/bse.2735</pub-id> </citation>
</ref>
<ref id="B42">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Shabani</surname>
<given-names>Z. D.</given-names>
</name>
<name>
<surname>Shahnazi</surname>
<given-names>R.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Energy Consumption, Carbon Dioxide Emissions, Information and Communications Technology, and Gross Domestic Product in Iranian Economic Sectors: A Panel Causality Analysis</article-title>. <source>Energy</source> <volume>169</volume>, <fpage>1064</fpage>&#x2013;<lpage>1078</lpage>. <pub-id pub-id-type="doi">10.1016/j.energy.2018.11.062</pub-id> </citation>
</ref>
<ref id="B43">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Shah</surname>
<given-names>S. G. M.</given-names>
</name>
<name>
<surname>Sarfraz</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Ivascu</surname>
<given-names>L.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Assessing the Interrelationship Corporate Environmental Responsibility, Innovative Strategies, Cognitive and Hierarchical CEO: A Stakeholder Theory Perspective</article-title>. <source>Corp. Soc. Responsib. Environ. Manag.</source> <volume>28</volume>, <fpage>457</fpage>&#x2013;<lpage>473</lpage>. <pub-id pub-id-type="doi">10.1002/csr.2061</pub-id> </citation>
</ref>
<ref id="B44">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Shahzad</surname>
<given-names>S. J. H.</given-names>
</name>
<name>
<surname>Kumar</surname>
<given-names>R. R.</given-names>
</name>
<name>
<surname>Zakaria</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Hurr</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2017</year>). <article-title>Carbon Emission, Energy Consumption, Trade Openness and Financial Development in Pakistan: A Revisit</article-title>. <source>Renew. Sustain. Energy Rev.</source> <volume>70</volume>, <fpage>185</fpage>&#x2013;<lpage>192</lpage>. <pub-id pub-id-type="doi">10.1016/j.rser.2016.11.042</pub-id> </citation>
</ref>
<ref id="B45">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Wu</surname>
<given-names>X.</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Yin</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Zheng</surname>
<given-names>W.</given-names>
</name>
<name>
<surname>Song</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Tian</surname>
<given-names>J.</given-names>
</name>
<etal/>
</person-group> (<year>2021</year>). <article-title>A Haze Prediction Model in Chengdu Based on Lstm</article-title>. <source>Atmosphere</source> <volume>12</volume>, <fpage>1479</fpage>. <pub-id pub-id-type="doi">10.3390/atmos12111479</pub-id> </citation>
</ref>
<ref id="B46">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Yam</surname>
<given-names>G.</given-names>
</name>
<name>
<surname>Tripathi</surname>
<given-names>O. P.</given-names>
</name>
<name>
<surname>Das</surname>
<given-names>D. N.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Modelling of Total Soil Carbon Using Readily Available Soil Variables in Temperate Forest of Eastern Himalaya, Northeast India</article-title>. <source>Geol. Ecol. Landscapes</source> <volume>5</volume>, <fpage>209</fpage>&#x2013;<lpage>216</lpage>. <pub-id pub-id-type="doi">10.1080/24749508.2019.1706295</pub-id> </citation>
</ref>
<ref id="B47">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Yin</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Huang</surname>
<given-names>W.</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Yang</surname>
<given-names>B.</given-names>
</name>
<name>
<surname>Zheng</surname>
<given-names>W.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Spatiotemporal Analysis of Haze in Beijing Based on the Multi-Convolution Model</article-title>. <source>Atmosphere</source> <volume>12</volume>, <fpage>1408</fpage>. <pub-id pub-id-type="doi">10.3390/atmos12111408</pub-id> </citation>
</ref>
<ref id="B48">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Yuelan</surname>
<given-names>P.</given-names>
</name>
<name>
<surname>Akbar</surname>
<given-names>M. W.</given-names>
</name>
<name>
<surname>Hafeez</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Ahmad</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Zia</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Ullah</surname>
<given-names>S.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>The Nexus of Fiscal Policy Instruments and Environmental Degradation in China</article-title>. <source>Environ. Sci. Pollut. Res.</source> <volume>26</volume>, <fpage>28919</fpage>&#x2013;<lpage>28932</lpage>. <pub-id pub-id-type="doi">10.1007/s11356-019-06071-4</pub-id> </citation>
</ref>
<ref id="B49">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zheng</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Mi</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Coffman</surname>
<given-names>D. M.</given-names>
</name>
<name>
<surname>Milcheva</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Shan</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Guan</surname>
<given-names>D.</given-names>
</name>
<etal/>
</person-group> (<year>2019a</year>). <article-title>Regional Development and Carbon Emissions in China</article-title>. <source>Energy Econ.</source> <volume>81</volume>, <fpage>25</fpage>&#x2013;<lpage>36</lpage>. <pub-id pub-id-type="doi">10.1016/j.eneco.2019.03.003</pub-id> </citation>
</ref>
<ref id="B50">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zheng</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Mi</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Coffman</surname>
<given-names>D. M.</given-names>
</name>
<name>
<surname>Shan</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Guan</surname>
<given-names>D.</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>S.</given-names>
</name>
</person-group> (<year>2019b</year>). <article-title>The Slowdown in China&#x27;s Carbon Emissions Growth in the New Phase of Economic Development</article-title>. <source>One Earth</source> <volume>1</volume>, <fpage>240</fpage>&#x2013;<lpage>253</lpage>. <pub-id pub-id-type="doi">10.1016/j.oneear.2019.10.007</pub-id> </citation>
</ref>
<ref id="B51">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zheng</surname>
<given-names>X.</given-names>
</name>
<name>
<surname>Lu</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Yuan</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Baninla</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Stenseth</surname>
<given-names>N. C.</given-names>
</name>
<etal/>
</person-group> (<year>2020</year>). <article-title>Drivers of Change in China&#x2019;s Energy-Related CO<sub>2</sub> Emissions</article-title>. <source>Proc. Natl. Acad. Sci. U.S.A.</source> <volume>117</volume>, <fpage>29</fpage>&#x2013;<lpage>36</lpage>. <pub-id pub-id-type="doi">10.1073/pnas.1908513117</pub-id> </citation>
</ref>
<ref id="B52">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zhou</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Hu</surname>
<given-names>S.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Regression Analysis and Driving Force Model Building of CO<sub>2</sub> Emissions in China</article-title>. <source>Sci. Rep.</source> <volume>11</volume>, <fpage>1</fpage>&#x2013;<lpage>14</lpage>. <pub-id pub-id-type="doi">10.1038/s41598-021-86183-5</pub-id> </citation>
</ref>
<ref id="B53">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Tiwari</surname>
<given-names>A.</given-names>
</name>
</person-group> (<year>2011</year>). <article-title>Tourism, Exports and FDI as a Means of Growth: Evidence from four Asian Countries</article-title>. <source>Rom. Econ. J.</source> <volume>14</volume> (<issue>40</issue>), <fpage>131</fpage>&#x2013;<lpage>151</lpage>. </citation>
</ref>
<ref id="B54">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Mahjabeen</surname>
<given-names>N.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Renewable Energy, Institutional Stability, Environment and Economic Growth Nexus of D-8 Countries</article-title>. <source>Mendeley Data</source> <volume>29</volume> (<issue>1</issue>), <fpage>1</fpage>&#x2013;<lpage>10</lpage>. <pub-id pub-id-type="doi">10.17632/y6tdzbn9cf.1</pub-id> </citation>
</ref>
<ref id="B55">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Venkatraja</surname>
<given-names>B.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Does Renewable Energy Affect Economic Growth? Evidence From Panel Data Estimation of BRIC Countries</article-title>. <source>Int. J. Sustain. Dev. World Ecol.</source> <volume>27</volume> (<issue>2</issue>), <fpage>107</fpage>&#x2013;<lpage>113</lpage>. <pub-id pub-id-type="doi">10.1080/13504509.2019.1679274</pub-id> </citation>
</ref>
</ref-list>
</back>
</article>