The Characteristics of Carbon Emissions Embodied in China’s International Economic Circulation Based on Global Value Chains

Abstract

Economic growth and environmental sustainability represent two critical components of sustainable development. This study analyzed the impacts of China’s international economic circulation (IC) on value added and carbon emissions, using a global value chain accounting framework, seeking to answer how to achieve the dual goals of economic growth and carbon emissions reductions through IC routes: traditional, simple, and complex international economic circulations (TIC, SIC, CIC). The major findings are as follows: (1) The contribution of China’s IC to the domestic economy has decreased since 2008, while its contribution to foreign economies continues to increase. Exports mainly promote domestic economic growth through TIC, while imports mainly promote foreign economic growth through SIC. (2) The carbon emissions embodied in China’s IC through exports are 2.1–4.5 times higher than those in imports. The impact of SIC on the embodied carbon emissions in exports is higher than that in imports, while the impact of CIC in exports is equivalent to that in imports. (3) Although China is a net exporter of carbon emissions, through certain routes, China’s bilateral trade with countries such as Korea, Australia, Malaysia, and Russia are conducive to China’s carbon emissions reductions. These findings provide scientific evidence for the design of trade and carbon emissions mitigation policies.

1. Introduction

The world today is undergoing the greatest changes in a century. Economic growth has slowed since the global financial crisis, international markets have contracted, and external demand has weakened. Additionally, unilateral actions, trade protectionism, ongoing geopolitical conflicts, and the COVID-19 pandemic have contributed to increasing global uncertainties [1]. In response, the Chinese government introduced a new development strategy in 2020, aiming to foster a dual circulation model where domestic and foreign markets support one another, emphasizing domestic economic circulation (DC) [2]. This dual circulation strategy represents a proactive shift to adapt to evolving domestic and international conditions. Emphasizing the DC is not intended to create a closed single circulation but rather an open domestic and international dual circulation [3]. Dual circulation emphasizes improving the quality and level of China’s international economic circulation (IC). Ni and Tian [4] proposed that participation in IC remains vital for China’s economic growth, as well as for enhancing the efficiency of DC, optimizing resource allocation, and increasing production quality. Exports and imports are crucial avenues for participating in IC, bridging domestic and international markets and linking production and consumption in a globally interdependent framework [5]. Through exports, by utilizing its cost-effective resources and labor force, China meets foreign demand and drives its own economic growth [6]. Imports have made up for China’s deficiencies in high-tech products and services, promoting foreign economic growth. As a result, China’s IC contributes significantly to both domestic economic expansion and global economic stability. Therefore, it is essential to study the economic impact of China’s IC from the perspectives of exports and imports.

IC enables countries to leverage their comparative advantages in production and services, generating economic benefits through exports and imports, while also potentially increasing carbon emissions embodied in trade [7,8]. As the world’s largest trading nation, China’s deep integration into IC has propelled sustained economic growth and raised per capita income. However, as China has evolved into a “world factory”, concentrating on energy-intensive sectors, this model has increased its carbon emissions [9]. Dong et al. [10] indicated that developed countries have often transferred high-polluting and energy-consuming processes to China, leveraging advanced technologies, industrial networks, and efficient management models to reduce their own emissions while raising those in China. According to data from the Organization for Economic Cooperation and Development (OECD), from 1995 to 2018, the total value of China’s exports greatly increased from USD 132.08 billion to USD 2135.75 billion, with the carbon emissions embodied in exports rising from 442.48 Mt to 1947.95 Mt—an increase in their share of total emissions in China from 15.1% to 20.7%. With the expansion of exports, carbon emissions embodied in China’s exports have consistently increased. However, China has avoided massive domestic carbon emissions by importing low-carbon-intensity intermediates from developed countries. Bai et al. [11] indicated that the expansion of imports has supported global carbon emissions reductions. Analyzing carbon emissions embodied in IC through exports and imports is, thus, essential to understanding IC’s implications for global carbon emissions reductions.

The development of global value chains (GVC) has provided a new perspective for measuring dual circulation and its carbon emissions. The GVC-based production decomposition covers factor inputs, production activities represented by intermediate products, and the consumption activities of final products, and these can better correspond to the four links mainly included in economic circulation, namely, production, distribution, circulation, and consumption [12]. Therefore, the GVC-based production decomposition is widely used to measure value added in IC, and it also provides a methodological foundation for measuring carbon emissions in IC. Moreover, with the development of GVC, intermediate trade increasingly dominates international trade [13]. The value added created by the production of specific final products is often generated across multiple countries, with carbon emissions embodied in intermediate trade crossing borders multiple times through distinct value chain routes. Therefore, understanding the complexity of different value chain routes is crucial for identifying the value added created by traditional, simple, and complex IC based on the cross-border times of intermediates and for assessing the carbon emissions embodied in China’s IC via these routes.

This study uses the GVC accounting framework to evaluate the value added and carbon emissions embodied in China’s IC through exports and imports, seeking to answer the question of how to achieve the dual goals of economic growth and carbon emissions reductions through IC routes: traditional, simple, and complex international economic circulations. The analysis addresses the following questions: How does China’s IC contribute to domestic and international economies? What are the characteristics of carbon emissions embodied in China’s IC through exports and imports? How do carbon emissions flow through the GVC? What are the differences in embodied carbon transfer via various value chain routes? Answering these questions offers valuable guidance for China’s strategic involvement in IC to balance “stable growth and emission reductions”. This study constructs a GVC-based accounting framework that refers to the production decomposition framework proposed by Wang (2017) [14], which is an analytical tool used to decompose and quantify the value added by various countries, regions, or enterprises at different stages of the global production process. The framework is built on the inter-country input–output (ICIO) model, which describes the interdependencies among various sectors of an economic system through the construction of input–output tables and serves as a core tool for analyzing complex economic linkages between regions and industries. By tracing the flow of products within the GVC, the framework decomposes the total value of the final product into the value created by participating countries or enterprises at different production stages. This study uses a GVC-based accounting framework to examine IC exports and imports and classifies IC into three types: traditional international economic circulation (TIC), simple international economic circulation (SIC), and complex international economic circulation (CIC). Using this framework, this study assesses IC’s contributions to domestic and international economies, identifying the routes, sources, and destinations of carbon emissions in IC.

The contributions of this study are presented as follows: (1) IC affects a country’s economic development through intermediate supply and demand markets for products. However, few studies analyze IC from the perspective of imports. Based on GVC, this study constructs a framework to measure international economic circulation from the perspective of imports and exports. This makes up for the deficiency that studying IC only from the perspective of exports cannot reflect the influence of other countries on China’s IC. (2) Based on the framework, this study constructs three IC routes and divides IC into TIC, SIC, and CIC; extends the framework to analyze the characteristics of embodied carbon emissions in IC at the total, bilateral, sectoral, and route levels; and maps the flow process of embodied carbon emissions along China’s IC. The findings of this study provide important insights for understanding the roles of different value chain routes, which may provide abundant route information to help guide countries’ policy design. (3) The findings reveal the sources, destinations, and transfer routes of carbon emissions in IC, providing rich data support for achieving China’s dual goals of stable economic growth and carbon emissions reductions.

2. Literature Review

This study builds on the literature in three main areas: the definition of dual circulation, the measurement of dual circulation, and the measurement of embodied carbon emissions.

Since the dual circulation concept was proposed in 2020, scholars have actively explored its definition and scope. However, interpretations of IC vary significantly, and no consensus has been reached. Some scholars define IC as “external demand” according to the final demand of national economic accounting, where IC encompasses the portion of gross domestic product (GDP) that fulfills foreign final demand [15,16,17,18]. Lu [19] views IC as the process of engaging in international value creation across one or more production stages of factor inputs and distribution, industrial input and output, and meeting final demand. In this view, imports are considered foreign production fulfilling domestic needs and are, thus, excluded from IC. However, imports are an important means for other countries to access the Chinese market [20]. Without taking imports into account, it is impossible to accurately measure IC. Some scholars consider imports and define IC based on the presence of foreign inputs in production, whereby any production involving foreign participation is classified as IC. Li [21] believes that IC is an economic system in which the domestic production process uses foreign factors, production, and markets. Chen [22] believes that as long as the production link involves foreign countries, it belongs to IC. Their definitions include both exports and imports as part of IC and have refined the analytical framework of international circulation.

Following the establishment of these definitions, researchers attempted to quantify dual circulation. Jiang and Meng [23] and Li and Liu [24] used traditional gross trade statistics to estimate the value added created by China’s IC. Traditional gross trade statistics refer to a trade statistical method based on the total value of exports and imports of goods or services. Felice and Tajoli [25] indicated that traditional gross trade statistics are limited in distinguishing between the value creators of each production link in the sequential production process. Li and Pan [26] argued that gross trade statistics fall short in accurately representing value flows within dual circulation and emphasized the need for value added accounting. Koopman [27] constructed a unified framework for Trade in Value Added (TiVA) accounting to decompose total exports. TiVA accounts for the value added of one country that is directly and indirectly embodied in the final consumption of another country, focusing on measuring the value created in exports [28,29]. Lu [19] separated the value added in exports to measure IC based on TiVA accounting. TiVA accounting primarily focuses on international trade, while the study of dual circulation requires consideration of not only international trade but also purely domestic economic activities. Due to the limitations of TiVA accounting, it cannot integrate domestic economic circulation and international economic circulation into a single framework for measurement. In contrast, the GVC-based production decomposition framework, through a comprehensive breakdown of production activities, is capable of accounting for both domestic and international economic circulation, thereby providing a unified measurement framework for dual circulation research. Huang and Ni [15] leveraged the GVC-based production decomposition to break down GDP and analyze IC using the World Input-Output Database, while Chen [22] calculated foreign contributions to GDP, thereby measuring IC. To deeply analyze IC, Wang and Tian [8] categorized IC into simple and complex IC according to intermediates’ border crossings and measured them. However, as the GVC continues to develop, intermediate trade also develops continuously, making IC more complex. It is essential for further research to comprehend China’s IC routes and the implications of cross-border frequency for IC.

With China’s trade expansion, IC’s role in carbon emissions has garnered global attention. Early studies explored carbon emissions embodied in trade [30,31,32,33,34,35,36]. As GVC theory and measurement methodologies evolved, researchers began analyzing embodied emissions within GVC-based accounting frameworks. Meng [37] integrated value added and carbon emissions into the same accounting framework and tracked emissions along GVC routes. This provided the methodological basis for this study. Zhang conducted a review of embodied carbon emissions in international trade based on the GVC [38]. Yue et al. [39] similarly calculated GVC-based carbon emissions, while Huang et al. [40] examined GVC activities and traditional trade activities to understand value added flows and carbon transfers using the ICIO model. These studies established a foundation for precise carbon emissions measurement in IC along the GVC. Additionally, bilateral trade emissions have been explored, such as in China–United States [41,42], China–Korea [43], and China–Japan trade studies [44,45]. Yan and Huang [46] analyzed carbon emissions in China’s GVC at the national and sectoral levels. As GVC deepen, fragmented production and economic integration disperse emissions across production stages. Therefore, GVC decomposition is essential for identifying sources, destinations, and transfer routes of carbon emissions within IC.

However, although existing studies have taken imports into account in defining IC, most have ignored the import component when measuring IC and have only calculated the impact of exports on a country. Therefore, they have been unable to accurately measure the carbon emissions embodied in IC and have also been unable to analyze net carbon transfer. In addition, existing studies on the classification of IC have only considered whether intermediates cross borders, without considering the cross-border frequency of intermediates, which reflects the depth of China’s participation in the global division of labor. Therefore, studying the cross-border frequency of intermediates helps us understand in more detail the impacts of China’s IC on both China and the world. Furthermore, previous studies on IC have mainly focused on the economic aspect, with less attention paid to environmental impacts, especially embodied carbon emissions.

Using GVC decomposition, this study unifies exports and imports within a single research framework, differentiates between types of IC participation based on value chain routes, and analyzes the impacts of IC on domestic and foreign economies, as well as carbon emissions. This comprehensive approach allows for a deeper understanding of IC’s economic contributions and carbon transfer patterns, providing insights for developing policies aimed at achieving stable economic growth while promoting emission reductions.

3. Methods and Data

3.1. Basic Model Framework

The GVC-based accounting framework utilized in this study is constructed based on the ICIO model. The ICIO model is capable of depicting the complex input–output linkages between regions and industries and has become a mainstream tool for tracking product flows and trade-embedded factors along the GVC. The ICIO table serves as the foundation and core of the input–output model.

Table 1. Inter-country input–output table.

	Outputs	Intermediate Demand				Final Demand				Total
Inputs		1	2		G	1	2	…	G	Output
Intermediate Inputs	1	$H^{11}$	$H^{12}$		$H^{1g}$	$Y^{11}$	$Y^{12}$	…	$Y^{1g}$	$X^1$
	2	$H^{21}$	$H^{22}$		$H^{2g}$	$Y^{21}$	$Y^{22}$	…	$Y^{2g}$	$X^2$
	$⋮$	$⋮$	$⋮$	$\ddots$	$⋮$	$⋮$	$⋮$	$\ddots$	$⋮$	$⋮$
	G	$H^{g1}$	$H^{g2}$		$H^{gg}$	$Y^{g1}$	$Y^{g2}$	…	$Y^{gg}$	$X^g$
Value added		$V{a}^1$	$V{a}^2$		$V{a}^g$
Total input		${(X^1)}^{\prime }$	${(X^2)}^{\prime }$		${(X^g)}^{\prime }$

presents the basic framework of the ICIO table.

${\mathit{H}}^{\mathit{sr}}$ is the N × N matrix representing the intermediate input produced by a country, s, for a country, r (s, r = 1,2,$\cdots$, g); ${\mathit{Y}}^{\mathit{sr}}$ is an N × 1 vector representing the final product produced by a country, s, to satisfy a country, r; and ${\mathit{X}}^s$ is an N × 1 vector, representing country s’s total output. $\mathit{A}=\mathit{H}{\widehat{\mathit{X}}}^{-1}$ is the input coefficient matrix, and $\widehat{\mathit{X}}$ is a diagonalized matrix of X. $\mathit{V}{\mathit{a}}^{\mathit{s}}$ is a 1 × N vector representing country s′s direct value added. $\mathit{V}=\mathit{Va}{\widehat{\mathit{X}}}^{-1}$ is the value-added coefficient vector. The total output consists of both intermediate and final products based on the ICIO table.

Where ${\mathit{A}}^{\mathrm{D}}=\mathit{diag}({\mathit{A}}^{11},{\mathit{A}}^{22},\text{⋯},{\mathit{A}}^{\mathrm{gg}})$ is the GN × GN diagonalized matrix of the domestic input coefficient, representing the value of the domestic intermediate products required to produce a unit of output. ${\mathit{A}}^{\mathrm{F}}=\mathit{A}-{\mathit{A}}^{\mathrm{D}}$, ${\mathit{A}}^{\mathrm{F}}$ is a GN × GN matrix of direct input coefficients between countries, representing the value of intermediate products from abroad required to produce a unit of output. Y$=\left[{\sum }_{\mathit{r}}^{\mathit{g}}{\mathit{Y}}^{1\mathit{r}},{\sum }_{\mathit{r}}^{\mathit{g}}{\mathit{Y}}^{2\mathit{r}},\text{⋯},{\sum }_{\mathit{r}}^{\mathit{g}}{\mathit{Y}}^{\mathit{gr}}\right]\text{’}$ is a GN × 1 vector of the final and service products. ${\mathit{Y}}^{\mathrm{D}}=[{\mathit{Y}}^{11},{\mathit{Y}}^{22}\text{⋯},{\mathit{Y}}^{\mathrm{gg}}]\text{’}$ is a GN × 1 vector representing the final product and service consumed in the country. ${\mathit{Y}}^{\mathrm{F}}=\mathit{Y}-{\mathit{Y}}^{\mathrm{D}}$ represents the final production and service production consumed at home. E $=\left[{\sum }_{\mathit{r}\text{≠}1}^{\mathit{g}}{\mathit{E}}^{1\mathit{r}},{\sum }_{\mathit{r}\text{≠}2}^{\mathit{g}}{\mathit{E}}^{2\mathit{r}},\text{⋯},{\sum }_{\mathit{r}\text{≠}\mathit{g}}^{\mathit{g}}{\mathit{E}}^{\mathit{gr}}\right]\text{’}$ is a GN × 1 vector whose elements represent a country’s total exports. After sorting $\mathit{X}=\mathit{AX}+\mathit{Y}$, we obtain $\mathit{X}=\mathit{BY}$. $\mathit{B}={\left(\mathit{I}-\mathit{A}\right)}^{-1}$ is a Leontief inverse matrix that represents the direct and indirect total outputs to produce a unit of the final product. Equation (1) was converted to the following equation:

$$X={(I-A^{\mathrm{D}})}^{-1}{Y}^{\mathrm{D}}+{(I-A^{\mathrm{D}})}^{-1}E=L{Y}^{\mathrm{D}}+LE=L{Y}^{\mathrm{D}}+L{Y}^{\mathrm{F}}+L{A}^{\mathrm{F}}X$$

(1)

where $\mathit{L}=(\mathit{I}-{\mathit{A}}^{\mathrm{D}}{)}^{-1}$ is the local Leontief inverse matrix.

The GVC-based accounting framework is shown in Figure 1. According to the final demand, the total value added of a country can be divided into two parts: that which meets domestic final demand and that which meets foreign final demand. The portion that meets foreign final demand can be further classified based on product form into final exports and intermediate exports. Among these, intermediate exports can be further divided into simple GVC (crossing borders only once) and complex GVC (crossing borders multiple times) based on the number of times they cross borders.

On this basis, this study utilizes the GVC-based production decomposition framework to decompose global production activities according to different stages and analyzes the flow routes of value on a global scale. The decomposition methods are as follows:

By replacing X in Equation (1) with BY and diagonalizing ${\mathit{Y}}^{\mathrm{D}},{\mathit{Y}}^{\mathrm{F}},\mathit{Y}$ in Equation (1) to ${\widehat{\mathit{Y}}}^{\mathrm{D}},{\widehat{\mathit{Y}}}^{\mathrm{F}},\widehat{\mathit{Y}}$, and then multiplying the GN × GN diagonal matrix $\widehat{\mathit{V}}$, we obtained the following equation:

$$\begin{array}{l}\widehat{\mathit{V}}\mathit{B}\widehat{\mathit{Y}}=\widehat{\mathit{V}}\mathit{L}{\widehat{\mathit{Y}}}^{\mathrm{D}}+\widehat{\mathit{V}}\mathit{L}{\widehat{\mathit{Y}}}^{\mathrm{F}}+\widehat{\mathit{V}}\mathit{L}{\mathit{A}}^{\mathrm{F}}\mathit{B}\widehat{\mathit{Y}}\\ \hspace{1em}\hspace{1em}=\widehat{\mathit{V}}\mathit{L}{\widehat{\mathit{Y}}}^{\mathrm{D}}+\widehat{\mathit{V}}\mathit{L}{\widehat{\mathit{Y}}}^{\mathrm{F}}+\widehat{\mathit{V}}\mathit{L}{\mathit{A}}^{\mathrm{F}}\mathit{L}{\widehat{\mathit{Y}}}^{\mathrm{D}}+\widehat{\mathit{V}}\mathit{L}{\mathit{A}}^{\mathrm{F}}(\mathit{B}\widehat{\mathit{Y}}-\mathit{L}{\widehat{\mathit{Y}}}^{\mathrm{D}})\end{array}$$

(2)

where each element in $\widehat{\mathit{V}}\mathit{B}\widehat{\mathit{Y}}$ represents the value added from a source country/sector, directly or indirectly used in the production of final products and services in a particular country/sector. Equation (3) identifies the following four types of production activities:

(1)

$\widehat{\mathit{V}}\mathit{L}{\widehat{\mathit{Y}}}^{\mathrm{D}}$: Value added of domestic production and consumption; the production process occurs at home.

(2)

$\widehat{\mathit{V}}\mathit{L}{\widehat{\mathit{Y}}}^{\mathrm{F}}$: Value added of final exports and imports involving cross-border trade.

(3)

$\widehat{\mathit{V}}\mathit{L}{\mathit{A}}^{\mathrm{F}}\mathit{L}{\widehat{\mathit{Y}}}^{\mathrm{D}}$: Value added of intermediate exports and imports involving the cross-border trade of intermediate products.

(4)

$\widehat{\mathit{V}}\mathit{L}{\mathit{A}}^{\mathrm{F}}\left(\mathit{B}\widehat{\mathit{Y}}-\mathit{L}{\widehat{\mathit{Y}}}^{\mathrm{D}}\right)$: Value added of intermediate exports and imports involving the multiple cross-border trade of intermediate products.

3.2. Calculation Model of Value Added and Carbon Emissions of International Circulation

Based on the basic model framework above, this study constructed a dual circulation calculation model that differs from existing frameworks by distinguishing between production activities and the final use locations of production factors. Specifically, domestic circulation, in this model, is defined as the production activities and final use that occur entirely within the home country. This includes products and services that are produced, consumed, or utilized domestically without engaging in cross-border trade. In contrast, the IC calculation model measures production activities and final use involving cross-border trade, where products, services, or production factors move across borders to fulfill foreign demand or utilize foreign inputs. This classification enables this study to analyze both domestic and international economic flows and assess their respective impacts on economic growth and carbon emissions. In this sense, the model constructed in this study represents novel calculations and applications of dual circulation, considering both imports and exports, which is the first methodological contribution of this study.

To understand Equation (3) more intuitively, we assumed the two-country model as follows:

$$\begin{array}{l}\widehat{V}B\widehat{Y}=\left(\begin{array}{cc}{\widehat{V}}^s{L}^{ss}{\widehat{Y}}^{ss}& 0\\ 0& {\widehat{V}}^r{L}^{rr}{\widehat{Y}}^{rr}\end{array}\right)+\left(\begin{array}{cc}{\widehat{V}}^s{L}^{ss}{\widehat{Y}}^{sr}& 0\\ 0& {\widehat{V}}^r{L}^{rr}{\widehat{Y}}^{rs}\end{array}\right)\\ \hspace{1em}\hspace{1em}+\left(\begin{array}{cc}0& {\widehat{V}}^s{L}^{ss}{A}^{sr}{L}^{rr}{\widehat{Y}}^{rr}\\ {\widehat{V}}^r{L}^{rr}{A}^{rs}{L}^{ss}{\widehat{Y}}^{ss}& 0\end{array}\right)\\ \hspace{1em}\hspace{1em}+\left(\begin{array}{cc}{\widehat{V}}^s{L}^{ss}{A}^{sr}(B^{rs}{\widehat{Y}}^{ss}+B^{rr}{\widehat{Y}}^{rs})& {\widehat{V}}^s{L}^{ss}{A}^{sr}(B^{rr}{\widehat{Y}}^{rr}+B^{rs}{\widehat{Y}}^{sr})\\ {\widehat{V}}^r{L}^{rr}{A}^{rs}\left[(B^{ss}-L^{ss})Y^{ss}+B^{sr}{\widehat{Y}}^{rs}\right]& {\widehat{V}}^r{L}^{rr}{A}^{rs}(B^{rs}{\widehat{Y}}^{ss}+B^{ss}{\widehat{Y}}^{sr})\end{array}\right)\end{array}$$

(3)

$$E^{sr}=V^s{L}^{ss}{Y}^{sr}+V^s{L}^{ss}{A}^{sr}[L^{rr}{Y}^{rr}+(B^{rs}{Y}^{ss}+B^{rr}{Y}^{rs})+(B^{rr}-L^{rr})Y^{rr}+B^{rs}{Y}^{sr})]$$

(4)

$$E^{rs}=V^r{L}^{rr}{Y}^{rs}+V^r{L}^{rr}{A}^{rs}[L^{ss}{Y}^{ss}+(B^{sr}{Y}^{rr}+B^{ss}{Y}^{sr})+(B^{ss}-L^{ss})Y^{ss}+B^{sr}{Y}^{rs})]$$

(5)

where ${\mathit{E}}^{\mathit{sr}}$ is the value added of country s’s exports to country r, ${\mathit{E}}^{\mathit{rs}}$ is the value added of country s’s imports from country r, and ${\widehat{\mathit{Y}}}^{\mathit{s}}$, ${\widehat{\mathit{Y}}}^{\mathit{r}}$, ${\widehat{\mathit{Y}}}^{\mathit{t}}$ represent the final use of s, r and t, respectively, and t ≠ s, r. We then expand the equation to a multi-country model as follows:

$$E^{sr}=\underset{\mathrm{Route}1}{\underbrace{{\widehat{V}}^s{L}^{ss}{\widehat{Y}}^{sr}}}+\underset{\mathrm{Route}2}{\underbrace{{\widehat{V}}^s{L}^{ss}{A}^{sr}{L}^{rr}{\widehat{Y}}^{rr}}}+\underset{\mathrm{Route}3}{\underbrace{{\widehat{V}}^s{L}^{ss}{A}^{sr}(B^{rs}{\widehat{Y}}^s+B^{rt}{\widehat{Y}}^t-L^{rr}{\widehat{Y}}^{rr})}}$$

(6)

$$E^{rs}=\underset{\mathrm{Route}1}{\underbrace{{\widehat{V}}^r{L}^{rr}{\widehat{Y}}^{rs}}}+\underset{\mathrm{Route}2}{\underbrace{{\widehat{V}}^r{L}^{rr}{A}^{rs}{L}^{ss}{\widehat{Y}}^{ss}}}+\underset{\mathrm{Route}3}{\underbrace{{\widehat{V}}^r{L}^{rr}{A}^{rs}(B^{sr}{\widehat{Y}}^r+B^{st}{\widehat{Y}}^t-L^{ss}{\widehat{Y}}^{ss})}}$$

(7)

In Equations (6) and (7), different value chain routes represent different types of IC. Production activities were divided into non-GVC (single value chain) activities and GVC activities based on whether intermediate products cross international borders. Based on the frequency of the cross-border transactions of intermediate products, GVC activities were further classified into simple and complex GVC activities. The three value chain routes used correspond to traditional international circulation (TIC), simple international circulation (SIC), and complex international circulation (CIC). Differentiating from existing frameworks, the IC routes newly defined by this study considered the frequency of cross-border transactions of intermediate products, which was this study’s second methodological contribution.

Table 2. International economic circulation of import and export and corresponding value chain routes.

International Economic Circulation		Value Chain Routes	Trade Pattern	Cross-Border Times
Export	TIC (Route 1)	single value chain	Final exports	once
	SIC (Route 2)	simple GVC	Intermediate exports	once
	CIC (Route 3)	complex GVC	Intermediate exports	twice or more
Import	TIC (Route 1)	single value chain	Final imports	once
	SIC (Route 2)	simple GVC	Intermediate imports	once
	CIC (Route 3)	complex GVC	Intermediate imports	twice or more

Note: TIC represents traditional international circulation, SIC represents simple international circulation, and CIC represents complex international circulation. Intermediate import is only assumed to be the last country from which the goods were imported into China.

shows the relationship between the IC of imports and exports and the value chain routes.

TIC refers to traditional final trade, where a country independently completes the entire process from raw material procurement, production, and processing to the manufacturing of final products within its own borders, after which the final products are exported across borders. SIC is an economic model in international economic activities that involves a one-time cross-border flow of intermediates, where an enterprise in one country produces intermediates and exports them to another country. The importing country’s enterprises then carry out further processing and assembly of these intermediates to transform them into final products. CIC is a highly globalized and fragmented economic model in which the production process of a product is decomposed into multiple stages, and intermediates flow across borders multiple times between several countries.

Country s’s direct carbon emissions coefficient is defined as ${\mathit{F}}^{\mathit{s}}$, ${\mathit{F}}^{\mathit{s}}={\mathit{C}}^{\mathit{s}}/{\mathit{X}}^{\mathit{s}}$, where ${\mathit{C}}^{\mathit{s}}$ is the vector of country s’s carbon emissions. In Equations (8) and (9), after replacing the value added coefficient with the direct carbon emissions coefficient, carbon emissions embodied in IC through exports and imports are represented as $\mathit{E}{\mathit{C}}^{\mathit{sr}}$ and $\mathit{E}{\mathit{C}}^{\mathit{rs}}$, respectively.

$$E{C}^{sr}=\underset{\mathrm{Route}1}{\underbrace{{\widehat{F}}^s{L}^{ss}{\widehat{Y}}^{sr}}}+\underset{\mathrm{Route}2}{\underbrace{{\widehat{F}}^s{L}^{ss}{A}^{sr}{L}^{rr}{\widehat{Y}}^{rr}}}+\underset{\mathrm{Route}3}{\underbrace{{\widehat{F}}^s{L}^{ss}{A}^{sr}(B^{rs}{\widehat{Y}}^s+B^{rt}{\widehat{Y}}^t-L^{rr}{\widehat{Y}}^{rr})}}$$

(8)

$$E{C}^{rs}=\underset{\mathrm{Route}1}{\underbrace{{\widehat{F}}^r{L}^{rr}{\widehat{Y}}^{rs}}}+\underset{\mathrm{Route}2}{\underbrace{{\widehat{F}}^r{L}^{rr}{A}^{rs}{L}^{ss}{\widehat{Y}}^{ss}}}+\underset{\mathrm{Route}3}{\underbrace{{\widehat{F}}^r{L}^{rr}{A}^{rs}(B^{sr}{\widehat{Y}}^r+B^{st}{\widehat{Y}}^t-L^{ss}{\widehat{Y}}^{ss})}}$$

(9)

The carbon transfer of China’s IC is then ${\sum }_{\mathit{r}\text{≠}\mathit{s}}^{\mathit{g}}\left(\mathit{E}{\mathit{C}}^{\mathit{sr}}-\mathit{E}{\mathit{C}}^{\mathit{rs}}\right)$.

Detailed construction of the methodology is provided in Supplementary Methodology S1.

3.3. Data

The data used in this study include input–output tables and sector-level carbon emissions corresponding to the input–output tables. The input–output tables are from the latest inter-country input–output tables of the OECD database in 2024 [47], which provide input–output tables covering 76 countries and one “Rest of the World” (ROW) region from 2000 to 2020 across 45 sectors. The OECD data come from a wide range of reliable sources and are widely used by most researchers. The database also includes carbon emissions data for the period 2000 to 2018 [48], which helps avoid conflicts and contradictions caused by different data sources, thereby reducing data errors and uncertainties.

In this study, the top ten countries in terms of trade volume with China are selected as the research subjects. The specific countries are listed in Supplementary Table S1. For analytical purposes, the 45 sectors were consolidated into eight major sectors based on the OECD sector classification. The sector names and their corresponding International Standard Industrial Classification, Revision 4 (ISIC Rev.4) codes are listed in

Table 3. Sector classification.

Sector	Sector Description	Code in Input–Output Table
AGR	Agriculture, forestry, and fishing	A
MIN	Mining and quarrying	B
LTI	Low technology-intensive manufacturing	C10-19, C31-33
MTI	Medium technology-intensive manufacturing	C22-25
HTI	High technology-intensive manufacturing	C20-21, C26-30
TTC	Trade and Transportation	G, H, I, J58-60
FBS	Postal, Telecommunication, Financial, and Business Services	J61-63, K, M, N
OSE	Real estate, public administration, construction, and other services	D, E, F, L, O, P, Q, R, S, T

. The names and codes have also been retrieved from the OECD database [48]. Since this study categorizes manufacturing industries based on different technological levels,

Table 4. Corresponding sector codes for manufacturing industries.

Sector	Code	Specific Sectors
LTI	C10-12	Food products, beverages, and tobacco
	C13-15	Textiles, textile products, leather, and footwear
	C16	Wood and products of wood and cork
	C17-18	Paper products and printing
	C19	Coke and refined petroleum products
	C31-33	Manufacturing nec; repair and installation of machinery and equipment
MTI	C22	Rubber and plastics products
	C23	Other non-metallic mineral products
	C24	Basic metals
	C25	Fabricated metal products
HTI	C20	Chemical and chemical products
	C21	Pharmaceuticals and medicinal, chemical, and botanical products
	C26	Computer, electronic, and optical equipment
	C27	Electrical equipment
	C28	Machinery and equipment, nec
	C29	Motor vehicles, trailers, and semi-trailers
	C30	Other transport equipment

lists the specific sectors under each category, enabling a clearer analysis of their economic and embodied carbon emissions characteristics.

4. Results

4.1. The Economic Impact of China’s International Economic Circulation

China’s GDP is generated through two components: domestic economic circulation (DC) and international economic circulation (IC). To gain an in-depth understanding of the impact of China’s IC on the economic system, this study conducted a measurement and analysis of the value added generated by international economic circulation based on three dimensions: scale, development trend, and structure. Figure 2 shows the contribution of dual circulation to China’s GDP from 2000 to 2020. The contribution of China’s DC to the economy has consistently been much higher than that of IC, indicating that DC is the dominant driver of China’s GDP. From 2000 to 2020, China pursued a DC-oriented economic development model, with the annual average contribution of DC exceeding 80.0%. However, from 2001 to 2007, the contribution of DC decreased from 81.7% to 73.3%. This shift can be attributed to the expansion of globalization and China’s accession to the World Trade Organization (WTO), and the long-term export-oriented economic development model of ”both heads outward, massive imports and massive exports” has made China’s economy develop rapidly. Consequently, the contribution of IC increased from 18.3% in 2000 to 27.7% in 2007. Following 2008, the global economy faced weak demand resulting from the global financial crisis and a rising tide of anti-globalization sentiment. As a result, the external impetus for economic growth diminished, leading to a slight decline in the contribution of IC. After a period of small fluctuations, the contribution of IC continued to decrease gradually, reaching 14.8% by 2020. Furthermore, based on value chain routes, IC is categorized into traditional international economic circulation (TIC), simple international economic circulation (SIC), and complex international economic circulation (CIC). TIC participates in international trade primarily through final exports, and the domestic economy driven by TIC consistently outperformed those driven by SIC and CIC, which operate through intermediate exports, throughout the entire study period. Nevertheless, the contribution of intermediate exports to economic growth was greater than that of final exports, highlighting the significant role that intermediate exports play in enhancing economic performance.

China’s IC affects domestic economies while simultaneously promoting foreign economies. Figure 3 displays the contributions of IC to both domestic and foreign economies from 2000 to 2020 at the route level. Figure 3a shows the contribution of IC to the domestic economy through exports. The trends for TIC, SIC, and CIC show similarities, with each route initially increasing before declining. This pattern may be attributed to China’s gradual emergence as the “world’s factory” following its accession to the WTO, during which it fully engaged in GVC division of labor. However, the global financial crisis in 2008 resulted in a significant drop in international demand, which adversely affected the domestic economy. Final exports through TIC initially encouraged China’s economic growth, with its contribution rising from 9.3% in 2000 to 11.8% in 2008. Subsequently, it plummeted to 9.6% in 2009, before gradually decreasing to 7.0% by 2020. The contributions of intermediate exports (SIC and CIC) were lower than those of final exports (TIC). Notably, the contributions of SIC gradually approached TIC, and by 2015, the combined contributions of SIC and CIC surpassed that of TIC. Because both SIC and CIC refer to intermediate trade, this trend suggests a notable shift due to the fact that the roles of intermediate and final exports have become equally significant. Furthermore, the contribution of SIC was always higher than that of CIC, with contributions of 5.7–6.4% and 1.8–2.1%, respectively. The more complex the GVC of an export route, the more subsequent production processes there are, and the closer exporters are to the upstream of the production chains [49]. Therefore, the production chains of China’s intermediate exports are mainly located in the downstream area of the GVC.

Figure 3b examines the impact of China’s IC on foreign economies through imports. The contribution of the three types of IC to other economies globally has generally increased, rising from 0.2%, 0.3%, and 0.1% in 2000 to 0.6%, 1.5%, and 0.4% in 2020, respectively. TIC consistently remained lower than SIC, with the gap between the two widening over time. Interestingly, CIC surpassed TIC during 2007 to 2008, indicating a contrasting trend to exports. These findings suggest that China’s IC primarily stimulates the economic growth of other economies through intermediate imports. Although the contribution of China’s IC to its domestic economy has decreased, its contribution to foreign economies has continued to increase, indicating a gradual increase in China’s dependence on the international market.

Figure 4 illustrates the impact of China’s IC on both domestic and foreign economies. The representative countries were chosen based on the top ten highest trade scales. In Figure 4a, the impact of IC through exports on the domestic economy in 2020 is depicted. The data indicate that the value added generated by China’s exports to the United States is the highest, totaling USD 41.55 trillion, significantly surpassing that of other countries. Japan follows as the second largest recipient, with exports valued at USD 16.59 trillion, which is only 40.0% of the amount for the United States. Among the top five countries contributing to China’s economic growth via IC, four are developed nations—namely Japan, the United States, Germany, and Australia—mainly influencing China’s economy through TIC. In contrast, the bottom five countries, which include Russia, Indonesia, Vietnam, and Malaysia, primarily enhance China’s economic growth through SIC.

Figure 4b examines the impact of IC on foreign economies through imports in 2020. It shows that the value added created by China’s imports from the United States is the highest among all trading partners. When viewed from the perspective of circulation routes, it becomes evident that China predominantly promotes the economic growth of major countries globally through SIC. Specifically, the value added percentages for Brazil and Russia attributable to China’s SIC constitute 75.5% and 72.5%, respectively, of the total value added created by SIC.

Figure 4a,b reveal distinct dynamics in China’s IC. The pulling effect of the United States, Japan, Australia, Brazil, Russia, and Indonesia on China’s economy is greater than the corresponding effect of China on these countries’ economies. Conversely, for Korea, Germany, Vietnam, and Malaysia, the influence of China on their economies exceeds their impact on China’s economy. Notably, major countries generally exert a greater driving effect on the Chinese economy through TIC than vice versa; only the United States, Indonesia, and Vietnam promote China’s economy more than their own economies are driven by China through SIC. Additionally, only Russia and India drive the Chinese economy more than their own economies are influenced by China through CIC. Economic development is the root cause of carbon emissions. These results provide an important economic background for understanding the carbon emissions issue. Only with a clear understanding of the scale, structure, and development trends of economic activities can the carbon emissions issues triggered by these activities be further explored.

4.2. The Carbon Emissions Embodied in China’s International Economic Circulation

After considering China’s economic background, this study calculates the embodied carbon emissions in IC at both the overall national and sectoral levels. Figure 5 depicts the carbon emissions characteristics of China’s IC from 2000 to 2018. In the upper section, the data reveal that carbon emissions embodied in exports grew significantly from 514.22 Mt in 2000 to 1534.91 Mt in 2018, reflecting a growth rate of 198.5%. Notably, there was a substantial increase in emissions between 2001 and 2008. However, this upward trend was interrupted by decreases in emissions during two periods: from 2008 to 2009 and again from 2014 to 2016. The first decline was due to the global financial crisis, and the second resulted from a decline in global investment. Following 2016, carbon emissions embodied in exports exhibited a gradual increase once more. The largest destination for these emissions from China’s exports is the United States, while Korea, Japan, and Germany also rank among the primary destinations for carbon emissions.

The lower section of Figure 5 illustrates the carbon emissions embodied in China’s imports, which are consistently lower than those of exports, ranging from 0.22 to 0.47 times the emissions of exports. This distinction primarily arises from the differences in factor endowments between China and each trade partner. China’s labor endowment has led the country to predominantly produce export products that are labor-intensive, low-value added, and high-carbon intensity. Conversely, the products that China imports are mainly high-tech and low-carbon-intensity [50]. Overall, the carbon emissions embodied in imports increased from 181.53 Mt to 762.4 Mt over the study period. There were minor fluctuations in emissions during 2005–2006 and 2015–2016, but an overall increase was observed throughout the remaining years. At the country level, excluding the ROW, Russia was the leading source of carbon emissions embodied in China’s imports before 2006, followed closely by Korea. However, since 2006, Korea has emerged as the largest source country. This shift can be attributed to geographical proximity and the strong complementarity between the two countries in terms of natural resources, labor, and export structures. Consequently, economic exchanges and cooperation between China and Korea gradually expanded, resulting in significant growth in carbon emissions embodied in imports from Korea [51].

Figure 6 shows the sectoral distribution of carbon emissions embodied in China’s IC through exports from 2000 to 2018. Most carbon emissions embodied in China’s IC through exports are concentrated in the manufacturing sector. This sector’s proportion of total carbon emissions grew from 43.1% in 2000 to 55.2% in 2010, before declining to 49.1% in 2018. These changes mainly occurred because of the continuous optimization of China’s export structure, with the proportion of manufacturing products in total exports increasing and its carbon emissions volume showing an upward trend [52]. In 2018, with a decline in the proportion of manufacturing exports, embodied carbon emissions also decreased significantly. The period from 2005 to 2016 was particularly notable, as carbon emissions from the manufacturing sector consistently accounted for over 50.0% of total emissions, likely due to China’s rapid industrialization and the accelerated growth of heavy industries during this time [53]. The manufacturing sector is further categorized into three types based on technological levels: low-tech manufacturing industry (LTI), medium-tech manufacturing industry (MTI), and high-tech manufacturing industry (HTI). The proportion of emissions from MTI steadily increased from 23.2% to 35.6% from 2000 to 2015, consistently surpassing the contributions of LTI and HTI. This is primarily because of the increase in exports of MTI products, such as steel, which is an energy-intensive industry, and the increase in exports of steel products leads to more carbon emissions. MTI experienced a remarkable growth rate of 48.3% over the study period, while LTI and HTI saw declines of −38.2% and −13.1%, respectively. Notably, after 2012, the proportion of carbon emissions from HTI began to exceed that of LTI, likely indicating a shift in the structure of manufacturing emissions toward more technologically advanced industries.

Table 5. Carbon emissions embodied in exports of China’s manufacturing industry to major countries through different international economic circulation in 2018 (Mt).

Country	LTI				MTI				HTI
	TIC	SIC	CIC	Gross	TIC	SIC	CIC	Gross	TIC	SIC	CIC	Gross
USA	15.85	6.75	2.57	25.17	40.63	45.15	21.29	107.07	12.71	10.34	5.17	28.22
JPN	3.54	2.89	0.67	7.10	13.74	15.06	5.69	34.49	4.05	3.86	1.32	9.23
KOR	1.01	1.89	0.34	3.24	4.30	13.99	2.64	20.93	1.39	3.12	0.65	5.16
VNM	0.57	1.27	0.11	1.95	1.60	7.67	1.07	10.34	0.36	1.26	0.24	1.86
DEU	2.32	0.86	0.75	3.93	6.75	6.02	6.46	19.23	2.00	1.52	1.54	5.06
AUS	1.53	0.9	0.24	2.67	4.61	6.46	2.24	13.31	1.56	1.38	0.50	3.44
MYS	0.30	0.33	0.10	0.73	1.36	3.37	0.96	5.69	0.36	0.66	0.23	1.25
RUS	1.34	0.57	0.25	2.16	4.65	6.16	2.14	12.95	1.37	1.38	0.52	3.27
BRA	0.69	0.46	0.16	1.31	4.55	4.20	1.37	10.12	1.41	1.40	0.37	3.18
IDN	0.72	0.63	0.19	1.54	4.21	8.25	1.77	14.23	1.35	1.70	0.42	3.47
ROW	23.80	17.12	6.52	47.44	102.13	139.71	54.11	295.94	26.72	30.80	13.42	70.94
Total	51.67	33.67	11.90	97.24	188.53	256.04	99.74	544.30	53.28	57.42	24.38	135.08

shows the carbon emissions embodied in different ICs through exports from manufacturing industries to major countries in 2018. Out of the top ten countries with the largest trade volumes with China, carbon emissions embodied in China’s manufacturing exports to the United States were the highest, at 25.15 Mt, 108.27 Mt, and 28.35 Mt for LTI, MTI, and HTI, respectively. For LTI and HTI, carbon emissions were primarily embodied in exports through TIC, apart from exports to Korea, Vietnam, and Malaysia. For MTI, carbon emissions were primarily embodied in SIC, and the proportions of carbon emissions embodied in exports to Korea, Vietnam, Malaysia, and Indonesia through SIC were all more than 50.0%, at 66.8%, 74.2%, 59.2%, and 58.0%, respectively, while those to Brazil and Germany were primarily embodied through TIC. The contributions of CIC to the embodied carbon emissions of MTI and HTI were 18.8% and 18.1%, respectively, which were higher than that of LTI. In summary, the carbon emissions of LTI and HTI were primarily embodied in final exports, whereas those of MTI were primarily embodied in intermediate exports. These findings are conducive to understanding the scale, trends, and sectoral structure of embodied carbon emissions from an overall perspective.

4.3. Carbon Transfer in China’s International Economic Circulation

Based on the analysis of embodied carbon emissions at the overall level, this study further measures the flow and transfer of embodied carbon emissions in China’s IC at the route level. Figure 7a maps the flow of carbon emissions embodied in China’s IC through exports for 2018. The total carbon emissions embodied in China’s exports were 1532.89 Mt, which included 941.71 Mt from intermediate exports and 629.43 Mt from final exports. This is because of the global production chain revolution, which has made intermediate trade the mainstream of international trade, and China is gradually integrating into the division of labor within the GVC [54]. Regarding the cross-border frequency of intermediate products, carbon emissions from intermediate exports can be categorized into two parts: SIC, contributing 689.89 Mt, and CIC, contributing 214.43 Mt. SIC is the primary contributor to carbon emissions embodied in China’s exports, accounting for 44.2% of total carbon emissions. This is because SIC concentrates on lower-tech industries with high energy consumption, and their intermediates cross an international border only once, which shortens the length of the production chain and reduces the technical difficulty of production, thereby facilitating participation by less-industrialized economies [55]. The carbon emissions embodied in China’s exports to the United States through these three routes were the highest, totaling 145.73 Mt for TIC, 120.52 Mt for SIC, and 57.54 Mt for CIC. This was followed by Japan, which accounted for emissions of 47.54 Mt, 44.36 Mt, and 15.19 Mt through the same routes.

Figure 7b maps the flow of carbon emissions along China’s IC through imports in 2018. Excluding the ROW, the top three sources of carbon emissions embodied in imports are Korea, the United States, and Russia, with emissions of 61.95 Mt, 59.51 Mt, and 55.66 Mt, respectively. The carbon emissions embodied in imports through the three IC routes were 157.87 Mt for TIC, 488.59 Mt for SIC, and 115.94 Mt for CIC. Carbon emissions embodied in imports through SIC were higher than those of TIC and CIC. This is mainly because SIC, which corresponds to a simple GVC, imports intermediates for producing final products to meet domestic demand, which is the main means of China’s participation in the GVC through imports. This form of value chain occupies a relatively low position in the division of labor and generates the most carbon emissions. Examining the different value chain routes in imports reveals that imports from the United States primarily occur through TIC, contributing 18.08 Mt of carbon emissions. In contrast, imports from Korea mainly occur through SIC, resulting in 41.94 Mt of emissions, while imports from Russia primarily utilize CIC, accounting for 16.26 Mt of emissions.

This study further analyzes the carbon intensity of IC, calculated by dividing carbon emissions by value added.

Table 6. Embodied carbon intensity of China’s IC in 2018 (kg/USD).

Bilateral Trade	Export				Import
	TIC	SIC	CIC	Gross	TIC	SIC	CIC	Gross
CHN-USA	0.63	0.85	0.92	0.75	0.21	0.33	0.27	0.27
CHN-JPN	0.56	0.85	0.94	0.70	0.22	0.38	0.34	0.32
CHN-KOR	0.58	0.9	0.91	0.78	0.37	0.54	0.52	0.49
CHN-VNM	0.79	1.21	1.06	1.08	0.68	0.89	1.01	0.85
CHN-DEU	0.62	0.81	0.93	0.75	0.14	0.27	0.26	0.22
CHN-AUS	0.62	0.87	0.97	0.75	0.24	0.48	0.45	0.43
CHN-MYS	0.58	0.96	0.94	0.80	0.63	0.62	0.67	0.63
CHN-RUS	0.61	0.88	0.93	0.75	0.89	0.95	1.20	1.01
CHN-BRA	0.73	0.96	0.93	0.83	0.30	0.40	0.51	0.39
CHN-IDN	0.71	1.01	1.02	0.88	0.43	0.66	0.76	0.63
Gross	0.62	0.89	0.93	0.76	0.27	0.48	0.45	0.41

presents the embodied carbon intensity of China’s IC in 2018. The carbon intensity of exports is 0.76 kg/USD, while that of imports is 0.41 kg/USD. This indicates that China may reduce domestic carbon emissions by replacing domestic production with imports, suggesting that the indirect expansion of China’s imports is beneficial for China’s carbon reductions [55]. The carbon intensity of exports from China to developing countries is higher than that to developed countries. The carbon intensity of imports follows the same pattern. Regardless of whether Vietnam is an exporter to or importer from China, its carbon intensity remains the highest among the ten countries participating in China’s IC. For bilateral trade between China and Russia, the carbon intensity of China’s imports is higher than that of its exports. Regarding routes, the carbon intensity of TIC is lower than that of the other two routes, regardless of whether it is measured for imports or exports. This is attributed to intermediate trade accounting for more value added in energy-intensive sectors, while final trade accounts for more value added in non-energy-intensive sectors. The carbon intensity of SIC is lower than that of CIC in exports and higher than that of CIC in imports. Zhang et al. [49] suggest that the complexity of the value chain route for exports leads to greater involvement in multiple production processes, bringing exporting countries closer to the upstream of the production chain, while upstream intermediates of China’s exports tend to be higher-emission resource inputs rather than R&D products. Conversely, the lower carbon intensity of imports is due to China importing fewer high-emission resource input products through CIC.

Table 7. Carbon transfer in IC through bilateral trade in 2000 and 2018 (Mt).

Bilateral Trade	2000				2018
	TIC	SIC	CIC	Gross	TIC	SIC	CIC	Gross
CHN-USA	70.99	53.95	7.44	132.38	127.65	91.14	45.48	264.27
CHN-JPN	36.41	28.67	4.95	70.03	36.92	15.80	8.81	61.53
CHN-KOR	1.07	−8.19	3.20	−3.92	1.57	−6.44	0.80	−4.07
CHN-VNM	0.59	0.85	0.88	2.32	0.89	6.15	0.22	7.26
CHN-DEU	9.05	5.06	3.36	17.47	19.67	6.45	11.93	38.05
CHN-AUS	3.02	0.90	0.20	4.12	11.59	−16.69	2.71	−2.39
CHN-MYS	−0.31	−1.14	1.93	0.48	−0.11	−1.00	−0.15	−1.26
CHN-RUS	−1.11	−26.03	−6.52	−33.66	12.37	−20.19	−10.5	−18.32
CHN-BRA	0.80	0.78	0.15	1.73	10.41	−4.70	1.78	7.49
CHN-IDN	1.26	0.001	0.54	1.801	10.57	5.66	0.97	17.20

presents the carbon transfer in various IC routes through bilateral trade for 2000 and 2018. In this context, carbon transfer through TIC was dominant, followed by SIC and CIC. In both 2000 and 2018, China was a net importer of carbon emissions in its trade with Korea and Russia, indicating that their involvement in China’s IC contributed to reductions in China’s carbon emissions. For TIC, the carbon transfer values for China–Malaysia trade and China–Russia trade in 2000 were −0.31 Mt and −1.11 Mt, respectively, suggesting that these trades through TIC aided in reducing China’s carbon emissions. However, by 2018, the carbon transfer in China–Russia trade was 12.37 Mt. Regarding SIC, the carbon transfer values in China–Korea trade, China–Malaysia trade, and China–Russia trade in 2000 were −8.19 Mt, −1.14 Mt, and −26.03 Mt, respectively. By 2018, the carbon transfer in China–Australia and China–Brazil trade changed from positive in 2000 to negative, indicating that these trade routes were beneficial for reducing China’s carbon emissions. For CIC, in 2000, only China–Russia trade was beneficial for reducing China’s carbon emissions, while in 2018, Brazil also played a role in decreasing carbon emissions through its participation in China’s CIC. These findings suggest that it is possible to achieve carbon emissions reductions while promoting economic growth through specific IC routes, such as trade with Malaysia via TIC and trade with Russia via CIC. Moreover, China’s bilateral trade with most countries can facilitate carbon emissions reductions through SIC. The research results provide scientific evidence for achieving the dual goals of stabilizing the economy and reducing emissions.

5. Discussion

By analyzing the economic impact of international economic circulation, this study finds that domestic economic circulation is the main driver of China’s economic growth, which is consistent with previous research findings [56,57]. In addition, this study emphasizes the rising role of IC. After China’s accession to the WTO from 2001 to 2008, the effect of IC on domestic economic growth increased significantly, which echoed the assumption of accelerating growth in export-oriented economies worldwide. The continued decline in the contribution of IC after 2008 reflects weaker global demand and increased deglobalization. It also supports the argument that excessive reliance on external markets leads to increased economic vulnerability [58]. After 2015, China’s participation in IC shifted from final exports (TIC) to intermediate exports (SIC, CIC), aligning with the development of GVC. The structure of production networks has increasingly leaned toward multiple cross-border processes [59].

Previous studies have primarily focused on the exports of IC. However, only a handful of scholars have studied imports and exports together. This research incorporates both imports and exports into a unified framework, examining not only the effects of international circulation on the domestic economy but also its impact on foreign economies. The survey results show that although the IC’s role in driving the domestic economy through exports is gradually weakening, its contribution to foreign economies through imports is increasingly prominent. This phenomenon has not received sufficient attention in existing research. China’s IC is not only an intrinsic demand for supporting domestic economic development but also an important engine for promoting global economic growth. Although China has proposed focusing domestic circulation as the main driver, it also attaches importance to the development of the world economy through international circulation. Especially through the import of intermediate products, China has significantly played the role of a “global demand engine”, injecting strong impetus into the stability and development of the global industrial chain. For example, China’s imports have stimulated economies like South Korea (through SIC) and Russia (through CIC), revealing a symbiotic relationship in which China’s demand supports upstream suppliers.

This study systematically measures the embodied carbon emissions in IC by employing a GVC-based production decomposition framework. The findings reveal a rapid increase in China’s export-related embodied carbon emissions between 2000 and 2008, primarily driven by its deep integration into the GVC division of labor system and its coal-dominated industrialization model [60,61]. The manufacturing sector accounts for the largest share of carbon emissions embodied in exports, with medium-technology manufacturing exhibiting higher embodied carbon emissions compared to low- and high-technology manufacturing. This reflects the energy-intensive production chains of medium-technology industries. Guo et al. [53] utilized the value added trade accounting framework to estimate embodied carbon emissions in exports, and the results obtained are consistent with the findings mentioned above.

Beyond focusing on embodied carbon emissions in exports, this study also utilizes the aforementioned framework to measure and compare embodied carbon emissions in imports. The results indicate that, at the aggregate level, embodied carbon emissions in imports are approximately 0.22 to 0.47 times those of exports, indicating China’s role as a net exporter of embodied carbon in IC. Additionally, the carbon intensity of exports is notably higher than that of imports. This finding corroborates the applicability of the “pollution haven hypothesis” in China, indicating a stark contrast between China’s labor-intensive and carbon-heavy exports and its cleaner, technology-intensive imports [62].

However, this study further reveals that China is not a net exporter of carbon emissions in all trade activities. By analyzing carbon transfers in IC at both bilateral and sectoral levels, the research identifies specific trade pathways that significantly reduce China’s net carbon emissions. For instance, trade with Malaysia and South Korea through SIC, as well as trade with Russia through CIC, effectively lowers China’s carbon emissions. These findings provide empirical evidence for achieving sustainable development, suggesting that by optimizing relationships with strategic partners and adjusting cooperation strategies based on the characteristics of different trade routes, China can effectively achieve synergy between economic growth and carbon emissions reduction goals in the GVC.

6. Conclusions and Implications

This study established an accounting framework for IC from the perspective of GVC, considering IC through exports and imports. We classified China’s IC into TIC, SIC, and CIC based on the geographical locations involved in the production process and the cross-border frequency of intermediates. This study first quantified the value added and carbon emissions embodied in China’s IC, followed by an analysis of the impact of China’s IC on domestic and foreign value added and carbon emissions based on the sources, destinations, and value chain routes. The major findings are presented as follows:

(1)

The driving effect of China’s IC on both domestic and foreign economies exhibited an increasing trend from 2000 to 2020. Exports primarily drive domestic economic growth through TIC and gradually shift from relying on TIC to SIC and CIC; however, SIC is much higher than CIC, indicating that China’s position in the GVC remains relatively low, and the proportion of its participation in IC through the complex GVC still needs to be increased. Meanwhile, imports primarily stimulate foreign economic growth through SIC, with their contribution to the foreign economy continuing to increase. Overall, IC has proven beneficial to both China’s economic growth and the world’s economic growth, and its contribution to the world economy is constantly increasing. Notably, the United States is the top contributor to China’s economic growth and benefits the most from China by participating in China’s IC.

(2)

Overall, the carbon emissions embodied in China’s IC through exports are 2.1–4.5 times those in imports. At the country level, the primary destination of carbon emissions embodied in China’s exports is the United States, while Korea is the main source of carbon emissions embodied in China’s imports. At the sectoral level, the manufacturing industry contributes the highest carbon emissions, accounting for over 50.0% of total emissions embodied in exports, with carbon emissions from medium- and high-tech manufacturing industries exceeding those from low-tech manufacturing industries. The promoting effect of CIC on the embodied carbon emissions of medium- and high-tech manufacturing industries is greater than that on low-tech manufacturing industries. At the route level, carbon emissions embodied in both imports and exports primarily flow through SIC, while the impact of SIC on embodied carbon emissions in exports is greater than that in imports.

(3)

China is a net importer of carbon emissions in its bilateral trade with certain countries, such as Russia, Korea, Malaysia, and Australia. China’s IC demonstrates potential for carbon emissions reductions through specific value chain routes; for example, China’s trade with Malaysia has reduced carbon emissions through TIC, while trade with Korea, Malaysia, Australia, Brazil, and Russia has contributed to reductions through SIC. Moreover, China’s trade with Malaysia and Russia has reduced its carbon emissions through CIC. The carbon intensity of exports through CIC is higher than that through SIC, while the situation is the opposite for imports. The findings regarding carbon emissions in China’s trade with various countries at the route level provide data support to help China achieve stable economic growth and carbon emissions reductions.

This study has some limitations. Firstly, this study is capable of analyzing the value added and embodied carbon emissions of exports at the sectoral level. However, due to reliance on the OECD database, the analysis of imports is subject to certain limitations, as we are unable to obtain sector-specific data for importers. Therefore, in this study, all the analyses on imports were conducted at the national level and cannot be carried out at the sectoral level. In future research, we will strive to integrate additional databases to obtain more granular data on imports, thereby enabling a sectoral-level analysis. Secondly, this study does not employ structural decomposition analysis, which introduces certain limitations in explaining the underlying mechanisms of factors affecting value added and embodied carbon emissions. In our subsequent research, we have conducted structural decomposition analysis on changes in value added and embodied carbon emissions in China’s IC. Thirdly, the data are outdated, as the carbon emissions data used in this study are current only up to 2018, and these lagging data cannot accurately reflect the latest actual situation of carbon emissions. We will actively carry out multi-channel data collection, update carbon emissions data, and explore the laws and trends behind the data in depth to provide solid support for China’s emission reductions.

The following policy implications are provided based on the results: The dual circulation policy should not only focus on domestic economic circulation as its mainstay but also place great importance on the high-quality development of international economic circulation. To improve the quality of international economic circulation, attention should be paid to intermediate trade, particularly in complex GVC. Efforts should be made to promote technological innovation and increase research and development inputs, as well as to promote the upgrading of traditional industries and the development of high-tech manufacturing industries, thereby enhancing China’s position in the GVC. More specifically, policymakers should simplify customs clearance procedures for intermediate products to reduce trade costs; provide financial support and policy incentives for enterprises to engage in R&D and innovation in intermediate product production, such as tax breaks for high-tech intermediate product manufacturing enterprises; provide technical support and financial assistance for traditional industries to carry out technological transformation; and increase government investment in basic research and key technology research.

While improving the quality of international economic circulation and expanding intermediate trade, more attention should be paid to the impacts of carbon emissions. Specific value chain routes can promote the economic development of China and the world while reducing China’s embodied carbon emissions. Formulating corresponding carbon reduction policies according to the impacts of different value chain routes is conducive to achieving sustainable economic growth and carbon reductions. Improving domestic production technologies is an effective measure for reducing China’s carbon emissions. Adjusting the trade structure, reducing exports of products from low-value added and high-carbon industries, increasing exports of products from high-tech manufacturing industries, actively participating in the international division of labor, and becoming deeply embedded in the GVC are also beneficial for decreasing China’s carbon emissions. Specifically, for value chain routes with high carbon emissions but relatively low economic value, policymakers could impose stricter carbon emissions restrictions and tax policies. For those value chain routes that can achieve both economic development and carbon emissions reductions, policymakers could provide more preferential policies and incentives, such as subsidies for green production technologies and tax breaks for low-carbon products.