Peaking carbon emissions under a coupled socioeconomic-energy system: Evidence from typical developed countries
Graphical abstract
Introduction
Economic activities of human society induce tremendous energy consumption, resulting in increasing carbon emissions and intensifying climate change (Soergel et al., 2021; Song et al., 2022). Carbon emissions in some developed countries have peaked and remained stable, which signifies a large share of the world's carbon emissions would be produced by the developing countries alongside rapid economic growth (Mi et al., 2021; World Bank, 2010). The developing countries such as China and India have pledged to peak carbon emissions by 2030, while still face multiple challenges to achieve the target (Fang et al., 2022; IME, 2015). Peaking carbon emissions entails to coordinate socioeconomic development and energy consumption which interact mutually (Deangelo et al., 2021). A large amount of fossil energy consumption promotes rapid socioeconomic development, while the highly advanced socioeconomic development is accompanied by a decline in energy demand, an improvement in energy efficiency and a transition in energy structure (Song et al., 2018; Zhong et al., 2020). Revealing the role of coupling socioeconomic system and energy system in peaking carbon emissions in the typical developed countries that have already peaked carbon emissions can provide insights for the countries that have not peaked carbon emissions with the least possible delay.
In recent years, studies on carbon emissions have been increasing drastically. The Logarithmic Mean Divisia Index (LMDI) decomposition method based on the Kaya identify has been widely adopted to study the influencing factors of carbon emissions and most studies have demonstrated that socioeconomic development and energy consumption are the main contributors to increasing emissions (Ma et al., 2018; Chontanawat et al., 2019; Dong et al., 2020). Aiming at the complexity among socioeconomic development, energy consumption and carbon emissions, scholars focused on the pairwise socioeconomic-environmental system (Darge et al., 1973) and energy-environmental system (Jones, 1979) tracing back to five decades ago. The influence of socioeconomic development on carbon emissions has been dissected employing some econometrics models, statistical models and Environmental Kuznets Curve (EKC) hypothesis, etc. The quantitative models primarily describe the influence direction and influence degree through the model fitting coefficients, including autoregressive distributed lag (ARDL) model (Martins et al., 2021; Cai et al., 2018), and Stochastic impacts by regression on population, affluence and technology (STIRPAT) model (Fang et al., 2019; Li et al., 2019) etc. The qualitative models such as vector error correction model (VECM) and Granger causality analysis mainly explain the influence by judging the causal relationship (Chen et al., 2016; Appiah, 2018). Distinguished from the above methods, the EKC is a hypothesis better reflecting how socioeconomic development dynamically makes a difference to carbon emissions at various phases of socioeconomic development (Grossman et al., 1995). Fang et al., (2022); Ugur (2018); Aslan et al., (2018) and Gyamfi et al., (2021) focused on seeking the key solutions to solving the problems of continuous economic growth promoting carbon emissions using the EKC hypothesis. Energy consumption is an important material basis for socioeconomic development and the major source of carbon emissions (Mi et al., 2020). Carbon emissions are directly affected by energy consumption, attributed to its quantity (Xu et al., 2020), structure (Du et al., 2018; Tian et al., 2019), intensity (Benjamin et al., 2019; Xia et al., 2020), and efficiency (Mi et al., 2017a; Wang and Feng, 2021). The implementation of total energy consumption control contributes to energy saving and emission reduction (Muhammad, 2019). Substantial energy structure adjustment along with alleviating the dependence of socioeconomic development on energy consumption through improving energy efficiency facilitates carbon mitigation (Zhang et al., 2018; Saidi et al., 2020; Zhu et al., 2018).
An optimal state for carbon emission reduction could originate from the coupled and coordinated development of socioeconomic system and energy system. The concept of coupling deriving from physics refers to the degree of interdependence and interaction between two or more subsystems within the whole system (Solymar et al., 1996; Liu et al., 2002). For the entire system, a stronger coupling effect between subsystems leads to stronger linkages between subsystems, causing the entire system to evolve from disorder to order and from low-quality to high-quality. For a subsystem, a stronger coupling effect symbolizes stronger interaction with other subsystems, as well as higher dependence on others (Wang et al., 2021). So far, the concept and framework of coupling have been applied to deal with social system and ecological system (Quintas-Soriano et al., 2021; Jurkenaite et al., 2022), urbanization and eco-environment (Cui et al., 2020; He et al., 2017), food production and environment protection (Gasparri et al., 2015), commodity trade and products (Fang et al., 2016), agriculture and land use (Meijaard et al., 2020) etc. Among studies on the coupling between socioeconomic system and energy system, typically, Fan et al., (2019) discussed that a high coupling and coordination degree presents harmonious relationship between advanced socioeconomic development and sound eco-environment. Sheng et al., (2020) found the significant evidence of the coupling between economic growth and carbon emission reduction in China, concluding that the coupling effects are different in regions undergoing different stages of economic development in the short-run. The above studies indicate the maturity and applicability of the widely adopted coupling and coordination model in evaluating the coupling between systems. So far, the coupling between socioeconomic system and energy system has never been linked to the carbon emission peak of regions.
Presently, studies on carbon emission peak have mainly focused on the prediction of energy consumption and carbon emissions (Xu et al., 2020; Feng, 2019; Liu et al., 2019), the peaking time, and the pathways to peak emissions in advance (Mi et al., 2017b; Tao et al., 2019; Yang and Song, 2021). These studies aimed at providing the guidance to establish a low-carbon development roadmap for various industries or regions (Fang et al., 2022). Diverse socioeconomic development conditions across countries lead to the differences in the peaking time. Specifically, the per capita carbon emissions and total carbon emissions would peak simultaneously in the case of a country with a zero-population growth (He, 2013). Chai et al. (2015) divided the countries having peaked carbon emissions into three groups in line with per capita carbon emissions, peaking time and stability of emissions. Dong et al., (2019) divided the emission peaking process in the developed countries into three stages and adopted a threshold regression model to analyze the influence of urbanization and industrialization on emissions to provide some reference for the developing countries. Jiang et al., (2019) considers that accurate projections of carbon emissions in the developing countries such as China and India, which are big carbon emitters, and the knowledge of possible time and pathways to achieve the emission peak are meaningful to cope with global climate change.
The literature review confirms that socioeconomic system and energy system jointly drive carbon emissions. Most studies have focused on how the social, economic and energy indicators affect carbon emissions. The impacts on the emission peaking process need to be explored from the perspective of system evolution, namely the socioeconomic system and energy system. For the countries having peaked carbon emissions, the influences of socioeconomic system and energy system on emissions present periodical features. Although the relationship between socioeconomic development and energy consumption or carbon emissions has been extensively studied, few studies have tracked the carbon emissions accompanying the coupling between socioeconomic system and energy system, as well as uncovered the role of the coupling between two systems in peaking emissions. In light of the above, relinking the coupling between socioeconomic system and energy system to the emission peaking process in the developed countries having peaked carbon emissions is of both theoretical and practical significance.
Targeting 10 typical developed countries having peaked carbon emissions, this study develops a comprehensive evaluation framework consisting of 13 indices for the socioeconomic system and energy system. The coupling between two systems in the empirical countries during the 10 years before and after the emission peak is measured to explore its influencing mechanism on the emission peaking process. The cases for five typical developing countries having not peaked carbon emissions are used to validate the findings. The main contributions of this study can be summarized as: (1) analyzing the carbon emission peaking process under both the impacts of the socioeconomic system and energy system, and under the coupling in between in the developed countries; (2) providing the experiences that the developing countries can attain from the developed countries in pertinently strategizing on how to achieve the emission peak considering the interactions between socioeconomic system and energy system.
The rest of this paper is organized as follows. Section 2 elaborates the coupling and coordination model for measuring the coupling level and coordination level between socioeconomic system and energy system, and introduces the empirical countries and data sources. Section 3 illustrates the results of the coupling and coordination between two systems and the development level of two systems for the empirical countries. Section 4 presents discussion and policy implications excavated. The conclusions are finally drawn in Section 5.
Section snippets
Research framework
The research procedures and the structure of the coupled socioeconomic-energy system are presented in Figs. 1 and 2 respectively. Firstly, 13 socioeconomic and energy indices are ultimately determined with reference to reviewed studies according to the frequency and regularity of the indices. A comprehensive evaluation framework of the socioeconomic system and energy system is constructed. Secondly, the weights of 13 indices are calculated by the entropy weight method. Then, the coupling
Coupling between socioeconomic system and energy system for the developed countries
By using the time series data on 13 indices ranging within 10 years before and after the emission peak, the coupling level and coordination level between socioeconomic system and energy system are quantified. The coupling level and coordination level are both greater than 0.85 (Fig. 3), which indicates that both the interaction and quality for two systems keep a high level, while the performance on interaction is better than on quality. The coupling level is highly close to 1 within the whole
Discussion
Under the theoretical framework for sustainable development and the targets for the emission peak and carbon neutrality, promoting high-quality socioeconomic development and highly efficient energy utilization for "carbon control" is imperative. The socioeconomic system and energy system are interactively affected, mainly reflected as two types of "inseparability", namely, high quality socioeconomic development relies on the support of highly efficient energy utilization which in turn is a
Conclusion
With 10 typical developed countries having peaked carbon emissions as the empirical targets, a framework consisting of 13 indices is constructed to evaluate the coupling between socioeconomic system and energy system during the 10 years before and after the emission peak. Through tracking the carbon emissions accompanying the coupling between two systems, the influencing mechanism of the coupling between two systems in peaking emissions is explored, which is consolidated by the cases in five
CRediT authorship contribution statement
Haiyan Duan: Conceptualization, Methodology, Formal analysis, Writing – original draft. Xiaohang Sun: Data curation, Methodology, Software, Visualization, Writing – original draft. Junnian Song: Conceptualization, Methodology, Formal analysis, Writing – review & editing, Supervision. Jiahao Xing: Formal analysis, Visualization, Writing – original draft. Wei Yang: Formal analysis, Writing – review & editing, Supervision.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This work is supported by National Natural Science Foundation of China (NO. 41801199, NO. 71773034).
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2023, Journal of Cleaner ProductionCitation Excerpt :In addition to the macroscopic perspective as sustainability, system coordination has also been connected to some more specific socioeconomic indicators. Targeting typical developed countries having peaked carbon emissions covering 10 years before and after the emission peak, Duan et al. (2022) measured the coupling between two systems and probed its influencing mechanism on peaking carbon emissions. Wang et al. (2021) employed a coupling coordination degree model to assess the coupling level between total factor energy efficiency and industrial structure with the Yangtze River Delta urban agglomeration as the empirical target.