The functioning of the China-Europe Railway Express (CRE) represents a significant results in achieving carbon emission decoupling within Chinese cities. With usage of panel data-set of 253 Chinese cities from 2005 to 2022, this analysis applies econometric models, including Tapio Decoupling model and Difference-in-Difference model to explore the connection between CRE and carbon emission decoupling. Findings revealed that while economic growth and emissions increased, especially after CRE was launched in 2011, periods of weak and strong decoupling have been prevailed. Moreover, the CRE opening has increased the decoupling level by 1.75 %.
Keywords: China-Europe Railway Express, carbon emission decoupling, transport efficiency
Introduction
The history of railway transport started in the XIX century, when the first railways appeared, making a revolution in the movement of goods. By the time being railway transportation becomes one of the most crucial parts of international business. Although the cost of this transport method is higher than maritime freight, railway freight is nevertheless cheaper than air transportation. That makes it an ideal mode of transportation for high-valued industrial commodities, like promotional or seasonal goods that require fast delivery: automobiles, electronics and computers. In such case, railways offer an ideal alternative for the companies and businesses engaged in global trade: faster than maritime transport and more affordable than air transport.
The China-Europe Railway Express (CRE) is an international railway transportation method between China, Europe and countries along the Belt and Road. It operates on a wide network of railways, from China to Western Europe through Central Asia, copying the way of ancient Silk Road. In 2011 the first train left from Chongqing city, located in Southwest part of China, to Duisburg, located in Western Germany, becoming a significant milestone in international logistic system. Moreover, demand for rail freight has increased significantly, especially after launching Belt and Road initiative in 2013 by Chinese government.
With the introduction of the CRE, advanced technologies such as automation, digitalization, and optimization of logistics are brought into use. This not only boosting transport efficiency but it is also contributing to technological innovations in the logistics and transportation sector resulting in high-quality development. China-Europe Railway Express represents as an important part of transportation network, with extensive implications on expanding trade and region-to-region connectivity. Understanding the implications of CRE operations is not only a logistic significance; it is the solution to the pressing environmental problems.
This article investigates the relationship between China-Europe Railway Express operation and carbon emissions decoupling in Chinese cities contributes to the theoretical understanding of sustainable transportation systems. Understanding the effects of China-Europe Railway Express operation on carbon emission decoupling can spread the knowledge of policymakers and industry stakeholders about the environmental impact of specific transportation choices.
However, despite the obvious economic benefits, the environmental impacts of CRE operation, especially in the context of carbon emission decoupling, are still poorly explored. Therefore, to address these issues, the present study is stating the following research question: What is the effect of China-Europe Railway Express operation on carbon emission decoupling?
To answer this question the following research methods are used in this study:
(1) Literature analysis method
By analyzing various research literature on carbon emission in China, opening of China-Europe Railway Express, carbon emission decoupling and the mechanism of operation of the CRE, in combination with the objectives of this study, the research problems and scientific significance of the article are determined. By analyzing the literature current research trends in related fields are identified, which helps to clarify the direction of work.
(2) Mathematical modeling method
The study uses Tapio decoupling model to analyze carbon emission decoupling indexes and economic growth rates in Chinese cities. The DID model is used to study the impact of CRE operating on decoupling levels in the economic of Chinese cities.
Literature review
According to EDGAR database, created by European Commission and Netherlands Environmental Assessment Agency, China is one of the largest sources of CO 2 emissions in the world, which makes the issue of reducing emissions particularly urgent [1] . China bears an immense burden in reducing carbon emissions, largely attributed to its fossil-fuel-driven economic expansion. In 2018, China contributed approximately 30 % of global CO 2 emissions,which is twice as much as the second largest emitter in the world, the United States, which only contributed 15 % [2] . And in 2023 this value reached up to 35 % [1] . The transportation sector, as emphasized by Liu et al. (2015), played a significant role in this context [3] . Their analysis of four transport sub-sectors highlighted that road and sea transport are the dominant contributors to CO 2 emissions in China. Furthermore, they found that economic growth was one of the most critical driving forces behind rising emissions.
Taken together, these findings underscore the critical role of transportation and economic activity in shaping China’s carbon footprint. Carbon emissions in China are heavily influenced by industrialization, urbanization, infrastructure expansion, and economic growth. Consequently, there is an urgent need for more sustainable practices and policy interventions aimed at decoupling carbon emissions.
The Belt and Road Initiative (BRI) has highlighted the strategic role of transport infrastructure in fostering economic development and it emphasizes the potential of large-scale infrastructure investments [4] . China-Europe Railway Express became an essential way of transportation for the BRI, characterized by advantages such as convenience, safety, stability, and promotion of green economy, resulting the increase in economic ant trade vitalities of cities [5] . Scientists are studying the impact of CRE on regional development, trade, logistical efficiency, and possible environmental impacts of its operation. Also, China-Europe Railway Express has become an important factor in the development of China's transport system contributed to a sharp increase in the number of shipments and cargo volumes, and acts as a complementary alternative to sea and air transport [6] . The opening of CRE has also been linked to reductions in urban carbon emissions. This effect operates through several key mechanisms, including transport mode substitution, industrial restructuring, economic agglomeration, and increased trade openness [7] . The launch of CRE contributed significantly to emission reductions by facilitating structural and economic transformation at the city level. At the same time, studies have noted that this growth in activity can exert pressure on the environment, especially in the form of rising pollution [8] . This studies show that CRE is not only a major logistical innovation but also a multidimensional catalyst for international trade, urban environmental outcomes, and economic transformation.
Carbon emission decoupling is a key goal of sustainable development. In economics, decoupling is a violation of the relationship between the growth of the volume or pace of the economy and the growth of the volume or pace of exploitation of resources or harmful impact on the environment and human health [9] . Han et al. (2022) analyzed the decoupling dynamics between CO 2 emissions and China’s economic growth, accounting for the country’s current stage of development and concluded that China must reinforce and optimize its energy structure in alignment with its industrial framework [10] . Based on the findings of these studies, China faces a major challenge: the need to simultaneously support economic growth and reduce carbon footprint. However, in the recent study by Sun et al. (2024) it is said that economic growth in most regions of China has outpaced the growth rate of carbon emissions, showing the characteristics of decoupling, which is caused by decrease in energy intensity [11] .
Theoretical framework
In order to analyze how China-Europe Railway Express affects the carbon emission decoupling in Chinese cities this research is using following models:
- Tapio decoupling model is used to analyze the connection between economic development and CO 2 emissions. In this study the author distinguish four categories of decoupling state:
— Expansive negative decoupling (e > 1.2) means that both the GDP of the city and CO 2 emissions increase, but the growth rate of CO 2 emissions exceeds that of GDP;
— Recessive coupling (0.8 ≤ e ≤ 1.2) indicates that emissions and GDP both increase, with the CO 2 emissions growth rate being greater or equal to the rate of GDP growth;
— Weak decoupling (0 ≤ e < 0.8) means that CO 2 emissions increase alongside GDP level, but GDP grows faster than CO 2 emissions;
— Strong decoupling (e < 0) occurs when the city's GDP increases while CO 2 emissions decrease.
The decoupling index model is expressed as follows:
|
(4.1) |
Where e notes the decoupling elasticity of city c in year t , % CO 2 represents the growth rate of total CO 2 emissions, and % GDP represents the gross output value of estimated city. ΔCO 2 represents the difference in the total CO 2 emissions from target year t to base year 0, and ΔGDP represents the difference in the gross output value of the estimated city from target year t to base year 0. CO 2 t represents total CO 2 emissions in target year t , and GDP t represents the gross output value of the estimated city in target year t . CO 2 0 represents total CO 2 emissions in base year 0, and GDP 0 represents the gross output value of the estimated city in base year 0.
- On the basis of Tapio decoupling model this research is using Difference-in-Difference (DID) model to test the direct effect of China-Europe Railway Express operation on carbon emission decoupling.
The regression model based on the DID method is set as follows:
|
(4.2) |
Where CED is the explained variable of the level of carbon emission decoupling in city c in year t . CRE c *Post t is the explanatory variable for whether city c opened CRE in year t : if city c opened CRE in year t it equals 1, otherwise, value is 0. η and μ were added to denote city and year fixed effects to control for some unobservant factors and year-to-year differences between the treatment and control groups after the opening of the CRE. α is a constant variable; ε is a random error term that affects the carbon emissions of the city c in year t . Z ct represents a series of control variable vectors and β is the corresponding coefficient vectors to be estimated. The coefficient θ will reveal the difference in the impact on carbon emissions between the opened and unopened cities after the opening of CRE. This study will focus on the results of the coefficient θ : if it is significantly negative, it will mean that cities that have opened CRE are effective in reducing emissions compared to the cities that have not launched CRE.
- Additionally, a placebo test will be provided to ensure that any observed effects are not due to natural variations or biases, thereby validating the causal interpretation of the results. A robustness test will also be conducted by altering model specifications and sample structures to verify the stability and reliability of the findings, helping to exclude the influence of potential confounding factors.
Data description
For this analysis 253 Chinese cities with the data time range from 2005 to 2022 were selected as a study objects. The data related to China-Europe Railway Express opening was obtained from the official China Railway Express Portal (www.crexpress.cn). All other data for this study was collected from China Statistical Yearbook, National Bureau of Statistics of China, China City Statistical Yearbook, Ministry of Ecology and Environment of China, the National Development and Reform Commission (NDRC) and other official resources. As control variables this study uses:
- Economic growth. Economic growth of cities can lead to increased industrial output, which may in turn result in higher carbon emissions. This paper uses the logarithm of GDP index as a measure of economic development, and this variable is expected to contribute to a rise in CO2 emissions.
- Population. Population density can theoretically impact carbon emission decoupling in two ways: it may increase emissions due to scale effects, while also improving environmental quality through agglomeration effects. To represent this, this study uses the logarithm of the total number of registered population. The overall direction of this influence remains uncertain.
- Trade opening. The opening of CRE stimulates the growth of urban exports and imports, exerting varying effects on carbon emission. In order to capture these different impacts, it will be measured by the logarithm of the total imports and exports of goods to represent the trade opening of the cities.
- FDI. FDI can contribute to increased carbon emission decoupling through the introduction of modern technologies and management practices that make it possible to use resources more efficiently and reduce energy costs. The logarithm of the total value of foreign investments directed to the cities is used to represent this data.
- Implemented policies. Recently, more and more countries have been implementing initiatives and regimes to reduce emissions, and China is no exception. Projects of advances cleaner technologies and practices in the manufacturing industry have already been introduced in many cities. To check their impact on emissions and carbon emission decoupling, a presence of different regulations directed to reduce the level of carbon emissions in Chinese cities were added. It is set as a dummy variable of whether or not cities implemented environmental policies in their practices.
- Average wages. As the income of the citizens’ rises, there is greater access to household appliances and technology that are more energy-efficient, which will most certainly result in lower carbon emissions. Also, an increase in the average wage correlates with the development of the service sector and an increase in demand for low-carbon products. However, higher incomes also result in higher energy consumption because the extent of personal journeys, use of cars, and general energy use can rise. Thus the overall influence on decoupling remains uncertain. It is represented as the logarithm of average wages value at designated cities.
Analysis and results
- Tapio decoupling model
For the period from 2005 to 2022, negative decoupling is observed in most regions before 2011, where the growth of CO 2 emissions exceeds the growth rate of the economy. Although, starting from 2011 when the CRE was launched periods of weak and strong decoupling can be distinguished more often, which highlights the achievements in reducing emissions against the background of economic growth.
Table 1
Decoupling state trends (2006–2022)
Year |
%CO 2 |
%GDP |
e |
Decoupling state |
2006 |
0,1484 |
0,0613 |
2,4205 |
expansive negative decoupling |
2007 |
0,1397 |
0,0799 |
1,7490 |
expansive negative decoupling |
2008 |
0,0856 |
0,0862 |
0,9928 |
recessive coupling |
2009 |
0,0946 |
0,0558 |
1,6974 |
expansive negative decoupling |
2010 |
0,1051 |
0,1048 |
1,0029 |
recessive coupling |
2011 |
0,1412 |
0,1178 |
1,1985 |
recessive coupling |
2012 |
0,0366 |
0,0754 |
0,4852 |
weak decoupling |
2013 |
0,0447 |
0,0707 |
0,6313 |
weak decoupling |
2014 |
0,0073 |
0,0610 |
0,1190 |
weak decoupling |
2015 |
0,0069 |
0,0480 |
0,1431 |
weak decoupling |
2016 |
0,0338 |
0,0642 |
0,5261 |
weak decoupling |
2017 |
0,0516 |
0,0790 |
0,6530 |
weak decoupling |
2018 |
0,0290 |
0,0653 |
0,4446 |
weak decoupling |
2019 |
0,0480 |
0,0702 |
0,6846 |
weak decoupling |
2020 |
0,0044 |
0,0295 |
0,1482 |
weak decoupling |
2021 |
0,1008 |
0,1287 |
0,7831 |
weak decoupling |
2022 |
-0,0183 |
0,0720 |
-0,2542 |
strong decoupling |
- DID model
Table 2
Baseline regression analysis on carbon emission decoupling
CED |
1 |
2 |
3 |
Without FE |
With FE |
With FE | |
CRE*Post |
-.0060*** (0.000) |
.0153*** (0.000) |
.0175*** (0.001) |
Economic growth |
-0.0837*** (0.003) | ||
Trade opening |
-.0375*** (0.003) | ||
Population |
.0936* (0.007) | ||
FDI |
.0136*** (0.005) | ||
Implemented policies |
.0013*** (0.001) | ||
Average wages |
-.0703* (0.037) |
Notes: significance levels of 10 %, 5 %, and 1 % represent *, **, and ***, respectively
Column 1 contains results excluding time- and city-fixed effects, while Column 2–3 include time- and city- fixed effects. Comparing coefficients in Column 1 and Column 2 can be seen, that the coefficient CRE*Post in Column 1 is significantly negative (-.0060) and the coefficient in Column 2 is significantly positive (.0153). Thus, it is necessary to use two-way fixed effects for further empirical estimations. After including control variables in Column 3, the coefficient CRE*Post is significantly positive (.0175), which indicates that compared to other cities, the cities where CRE was opened can increase the level of carbon emission decoupling by 1.75 %.
Furthermore, it can be seen that FDI (.0136) and Implementation of enpolicies (.0013) can have a significantly positive effect on emission decoupling. The entry of foreign investors creates competition and encourages local companies to improve production efficiency by using environmentally friendly practices, as well as adopting advanced technologies and production methods that are more energy efficient and less carbon-intensive. Implemented policies can help to promote cleaner technology upgrading and have a significant effect on decoupling. In addition, foreign investment under the influence of stimulating emission reduction policies can accelerate the financing of environmental technologies and contributes to the improvement of infrastructure. At the same time, Economic growth (-0.0837) and Trade opening (-.0375) negatively affect the emission decoupling. The reason for this effect may be due to an increase in industrial activity stimulated by the CRE opening. This leads to an increase in absolute emissions, even with possible improvements in energy efficiency. Population and Average wages significant only on 10 % level.
- Placebo and robustness tests
To confirm the causal effect of China-Europe Railway Express opening on CO 2 emission decoupling, a placebo test was conducted, artificially setting the start of the «treatment» several years earlier than the actual one, in 2008. This allowed us to check for hidden time trends that could distort the results. The coefficients for the placebo_treatment*placebo_post interaction are not significant, which confirms the absence of effects related to decoupling before the introduction of CRE.
Table 3
Placebo test
Placebo_treatment*placebo_post |
Economic growth |
Trade opening |
Population |
FDI |
Implemented policies |
Average wages | |
Coef |
.0015 |
-.5547 |
-.0079 |
.0001 |
.0136 |
.1046 |
.0703 |
P-value |
(0.412) |
(0.330) |
(0.076) |
(0.546) |
(0.246) |
(0.198) |
(0.371) |
Notes: significance levels of 10 %, 5 %, and 1 % represent *, **, and ***, respectively
In order to confirm the sustainability of the results several robustness test were made: different model specifications, changing the time period, and divided cities into categories depending on the size of their population. These tests showed that the key coefficients remained stable and statistically significant, which indicates the stability and reliability of the analysis results.
Conclusion
Carbon emission decoupling in China refers to the process of separating economic growth from an increase in carbon dioxide emissions. In other words, it involves achieving economic development without a proportional rise in carbon emissions. This transition is crucial for combating climate change and advancing sustainable development. In order to find out what role the operation of the China-Europe Railway Express (CRE) plays in changing carbon emissions, systematic theoretical and empirical work was carried out in this study. The main results of the study are presented below:
First, Tapio decoupling model analysis showed that from 2005 to 2022, GDP value and emissions increased in all regions, especially since 2011, which highlights the success in emission reduction. Second, further tests showed that СRЕ has increased the decoupling level by 1.75 %. This result is supported by the result of the placebo test. Third, in addition, several types of robustness tests were conducted, such as changing of model specification with replacement and addition of new variables, changing of time period, comparison of different categories of variables, and a bootstrap test with 1000 repetitions. All tests showed positive and significant results, on the basis of which it can be concluded that the opening of China-Europe Railway Express can stimulate carbon emission decoupling.
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