An empirical analysis on carbon emission and economic growth in liaoning

Summary Cities, contributing more than 75% of global carbon emissions, are at the heart of climate change mitigation. Given cities' heterogeneity, they need specific low-carbon roadmaps instead of one-size-fits-all approaches. Here, we present the most detailed and up-to-date accounts of CO2 emissions for 294 cities in China and examine the extent to which their economic growth was decoupled from emissions. Results show that from 2005 to 2015, only 11% of cities exhibited strong decoupling, whereas 65.6% showed weak decoupling, and 23.4% showed no decoupling. We attribute the economic-emission decoupling in cities to several socioeconomic factors (i.e., structure and size of the economy, emission intensity, and population size) and find that the decline in emission intensity via improvement in production and carbon efficiency (e.g., decarbonizing the energy mix via building a renewable energy system) is the most important one. The experience and status quo of carbon emissions and emission-GDP (gross domestic product) decoupling in Chinese cities may have implications for other developing economies to design low-carbon development pathways.

As the world’s largest producer, consumer, and exporter of textiles and apparel, China plays a pivotal role in the carbon emission reduction of the industry. This paper employs the “Tapio” decoupling model to analyze the decoupling relationship between carbon emissions and economic growth in China’s textile industry across 30 provinces from 2001 to 2020. The LMDI model is then used to decompose the influencing factors of carbon emissions, followed by a comparative study of four distinct periods and three regions. The findings reveal that: (1) From 2001 to 2020, both carbon emissions and GDP growth in China’s textile industry exhibited a “rise then decline” trend. Carbon emissions primarily stemmed from coal consumption, followed by gasoline and natural gas. The energy structure had been gradually optimized, with the shares of coal and gasoline in total consumption declining, while the share of natural gas has increased. (2) Carbon emissions in China’s textile industry had achieved strong decoupling from economic growth over the 20-year study period. The decoupling status at different periods was as follows: weak decoupling (2001–2005), weak decoupling (2006–2010), strong decoupling (2011–2015), and weak negative decoupling (2016–2020). Comparing different regions, Central China exhibited strong decoupling, while East China and West China both experienced weak decoupling. (3) Per capita output value was the main driving factor behind the growth of carbon emissions, while energy consumption intensity factor played the most significant role in inhibiting emissions. Additionally, employment scale factor promoted carbon emissions in the first two periods but significantly suppressed them in the last two periods. The energy structure factor gradually strengthened its suppressive effect on carbon emissions, although its overall impact remained limited. Finally, based on these findings, feasible and practical policy recommendations are proposed.

The construction of transportation infrastructure boosts economic growth while facing the challenge of carbon emissions pressure. Clarifying the relationship among transportation infrastructure, economic growth, and carbon emissions is important in order to promote the realization of the goal of "dual-carbon." Based on the panel data of 30 provinces in China from 2002 to 2021, the research period was divided into four stages （2002-2006, 2007-2011, 2012-2016, and 2017-2021）. The Tapio decoupling model was used to analyze the decoupling state between carbon emissions and transportation infrastructure, as well as between carbon emissions and economic growth, and the panel vector autoregression （PVAR） model was used to study the dynamic relationship and internal influence mechanism among the three in each region. The results showed that： ① The overall decoupling relationship between carbon emissions and transportation infrastructure in China showed the changing trend of "weak decoupling → strong negative decoupling → strong decoupling → weak decoupling." ② The decoupling relationship between carbon emissions and economic growth in 30 provinces only showed four states in the four stages： strong decoupling, weak decoupling, expansive coupling, and expansive negative decoupling. During the research period, the decoupling index between carbon emissions and economic growth decreased in most provinces of China, and the overall decoupling state improved, but the carbon emissions decoupling situation was unstable. ③ Transportation infrastructure had a positive impact on economic growth in each region, and both transportation infrastructure and economic growth had a positive impact on carbon emissions in each region, but the degree of impact varied by region. The results of the research can provide low-carbon development strategies for the construction of transportation infrastructure and help promote the stable, healthy, and sustainable development of China's economy.

In the context of global countries’ pursuit of sustainable development and “dual carbon” goals of China, this paper combines the Tapio decoupling model, Kaya’s equation and LMDI decomposition method to analyze the relationship between carbon emissions and economic growth and the driving factors of carbon emissions in the Yellow River Basin (YRB) of China from 2001 to 2019. It is found that the decoupling state of CO2 and economic growth in the Yellow River Basin shows a trend of expansion negative decoupling - expansion connection - weak decoupling - strong decoupling, but different regions shows some heterogeneity. The economic intensity effect and population size effect generally play a positive role in driving carbon emissions, while carbon emission intensity, industrial structure and energy structure effect play a negative role in driving carbon emissions in most years. From the regional perspective, the energy consumption structure in the middle reaches is the most important factor to promote carbon emissions. In terms of time period, the industrial structure effect is the driving factor of carbon emissions in the decoupling state overall as expansionary linkage, while it is the inhibitor of carbon emissions in the decoupling state overall as weak decoupling. This study also puts forward countermeasures such as optimize the energy structure and upgrade the industrial structure to achieve green and high-quality economic development in the YRB.

Knowledge of decoupling indicators and its determinants is useful for formulating targeted policy recommendations. To this end, the Log-Mean Divisia Index and Tapio models were applied in this paper to study the decoupling relationship among economic growth and GHG emissions in Cameroon over the period 1971-2014. The analyzes were conducted according to the three major periods that marked Cameroon after independence and the decoupling indicators were broken down into seven factors while considering the three main GHGs emitted in this country (i.e. CO2, CH4, and N2O). The results showed that weak decoupling, strong decoupling, and strong negative decoupling occurred in Cameroon during the periods 1971-1984 and 1994-2014 which represent the periods before and after the economic crisis, respectively. In addition to these three decoupling statuses, recessive decoupling only appeared during the economic crisis period (1984-1994). From 1971 to 1984 and between 1994 and 2014, carbon intensity, economic activity, population, and emission factor not only contributed to the increase of Cameroon’s GHG (particularly CO2) emissions but also prevented decoupling. Unlike the period 1984-1994, energy intensity contributed to reducing environmental pollution while promoting decoupling during the periods 1971-1984 and 1994-2014. Although all played an important role in decoupling, we found that after the introduction of natural gas into the country’s energy mix from 2007, the effect of renewable energies on the mitigation of Cameroon’s CO2 emissions remained higher than the substitution of fossil fuels. However, to develop a cleaner economy, Cameroon should maintain modest economic growth and continuously transform economic development pathways, while encouraging the use of renewable energy to further reduce energy intensity per unit of GDP per capita.

Is energy transition promoting the decoupling economic growth from emission growth? Evidence from the 186 countries

The decoupling of carbon emissions has also become the dependence of countries’ development. Finance plays an important role in decoupling economic development from carbon emissions. This paper explores the impact of financial development in different regions on the decoupling of carbon emissions from economic growth, using the Tapio decoupling elastic model and the method of fully modified least squares (FMOLS) to study the impact of financial development on carbon emissions in six regional panels from 1995 to 2020: and Foreign direct investment (FDI), urbanization, population, and infrastructure as control variables. The results turn out that financial development will promote the decoupling of carbon emissions from economic growth in the ECA region. For EAP, SSA, AC, SA, and MENA regions, financial development will promote the growth of carbon emissions, and due to the different economic development dynamics of different countries, the positive effects of financial development on carbon emissions are heterogeneous. The impact of FDI, urbanization, and infrastructure on carbon emissions varies from region to region. The population will promote the growth of carbon emissions, regardless of the region. In addition, the ECA region is the most countries that has achieved the strong decoupling and is the first to realize the transition from weak decoupling to strong decoupling. Therefore,the ECA, EAP and AC region should accelerate the construction of a green financial system to promote the decoupling of economic growth and carbon emissions. The SSA, SA and MENA region should speed up the transformation of economic development mode and move towards weak decoupling or even strong decoupling.

Quantitative analysis on decoupling between economic output, carbon emission, and the driving factors behind decoupling states can serve to make the economy grow without increasing carbon emission in China’s transport sector. In this work, we investigate the decoupling states and driving factors of decoupling states in the transport sector of China’s four municipalities (Beijing, Shanghai, Tianjin, and Chongqing) through combining the Tapio decoupling approach with the decomposition technique. The results show that (i) the decoupling state of Beijing, Shanghai, and Tianjin improved; Beijing stabilized in weak decoupling; Shanghai and Tianjin appeared to have strong decoupling, but the decoupling state of Chongqing deteriorated from decoupling to negative decoupling. (ii) The energy-saving effect was the primary contributor to decoupling in these four municipalities, promoting transport’s economic growth strongly decouple from carbon emission. The economic scale effect was not optimized enough in Chongqing, facilitating expansive coupling, and expansive negative decoupling emerged. But it had a rather positive impact on decoupling process in Beijing, Shanghai and Tianjin, promoting economic growth to weakly decouple from carbon emission. (iii) The carbon-reduction effect promoted strong decoupling, which emerged in Shanghai’s transport sector, more so than in the other three municipalities, in which weak decoupling emerged. Finally, several relevant policy recommendations were offered to promote the decoupling of carbon emission from economic growth and low-carbon transport.

The chase for economic growth results in global environmental degradation, threatening the socioeconomic aspects of human lives. Singapore is a global economic player, transforming its rural setup into an urban structure to achieve higher economic growth (EG). However, the drive for EG drastically affected its environmental quality. In this respect, the present study analyzes the relationship between Singapore's economic activities and environmental quality. This study uses the Tapio decoupling indicator, Kaya Identity, and the Log Mean Divisia Index (LMDI) decomposition techniques to assess the relationships between these paramount factors from 1990 to 2016. The LMDI analysis reveals that EG and population are the main contributors to carbon emissions (CE), whereas carbon intensity reduces the environmental impact. However, energy intensity and energy structure have depicted mixed effects on CE. Further, Tapio analysis reveals that Singapore has experienced strong decoupling (SD) in most study years. Additionally, expensive negative decoupling (END), weak decoupling (WD), and strong negative decoupling (SND) were also observed during the study period. An expanded decomposition analysis reveals that population and EG deteriorate environmental quality in Singapore. While carbon intensity is the critical driver that strengthens the decoupling progress, energy intensity and structure depict a mixed effect on the decoupling process.

Understanding the spatiotemporal decoupling effects among economic development, energy consumption, and carbon dioxide emissions is paramount to achieving sustainable development. This relationship sheds light on how regions can grow economically while managing their energy resources efficiently and minimizing environmental impacts. This study examines the critical and globally relevant issue of spatiotemporal decoupling that includes economic development, energy consumption, and carbon dioxide emissions in Xinjiang Province from 2006 to 2020. The Tapio Elasticity Analysis Method is utilized to achieve this objective. We found that the early years showed expansive coupling, reflecting a phase where economic growth was closely tied to increases in energy consumption and emissions. However, over time, particularly post-2010, there is a noticeable shift towards weak decoupling and eventually to more substantial forms of decoupling. The primary sector displayed mostly weak and strong decoupling. The secondary sector, however, showed fluctuating decoupling states. In the tertiary sector, a generally weak decoupling was observed. A spatial analysis across Xinjiang’s prefectures and cities revealed pronounced regional variations. This investigation validates the effectiveness of regional ecological policies and illustrates the necessity of tailored strategies to foster sustainable development. Our findings provide valuable insights not only for regional policymakers but also for international stakeholders aiming to achieve sustainable development. The results underline the importance of tailored strategies in different regions, contributing to the broader understanding of sustainable development dynamics.

This study analyzes the decoupling relationship between carbon emissions and economic growth, along with the driving factors of this relationship, for the four municipalities in China from 2005 to 2021, using the Tapio decoupling model and the Logarithmic Mean Divisia Index method for quantitative analysis. The results of the Tapio analysis show that Beijing and Shanghai achieved decoupling in all of the years studied, with 62.5% of the years in Beijing being classified as having strong decoupling, while Shanghai predominantly exhibited weak decoupling, accounting for 62.5% of the years studied. Tianjin displayed more diverse characteristics, with 12.5% and 6.25% of years demonstrating expansive coupling and strong negative decoupling, respectively. In Chongqing, 50% of years were characterized by weak decoupling, while 18.75% were characterized by expansive coupling. The analysis indicates that the reduction in energy intensity plays a significantly greater role in promoting decoupling than other factors, suggesting that reducing energy intensity is a feasible and important path for carbon decoupling. Additionally, reducing carbon intensity and coal resource usage in the secondary industry is a key factor for promoting decoupling, while the expansion of economic and population scales hinders this process. By quantitatively analyzing the mechanisms behind decoupling, this study reveals the challenges posed by economic and population growth in achieving carbon reduction targets. The findings provide a scientific basis for policies promoting low-carbon economic development and offer valuable insights for global efforts to combat climate change.

Amid global climate warming, it is necessary to explore the decoupling relationship between economic growth (EG) and industrial CO2 emissions (ICEs). This paper uses the Tapio decoupling model and the logarithmic mean Divisia index (LMDI) model synthetically to analyze the decoupling relationship between EG and ICEs and reveal the driving force of growth of CO2 emissions (CEs) based on ICE panel data from 13 prefecture-level cities in Jiangsu province from 2011 to 2015. From the research results, it can be seen that the decoupling status in southern Jiangsu, middle Jiangsu and northern Jiangsu presented weak decoupling (WD), weak negative decoupling (WND) and WD, respectively. In 2011–2013, seven prefecture-level cities exhibited states of WD, and strong decoupling (SD) occurred only in Zhenjiang, with a decoupling index value of −0.3359. In 2013–2015, five prefecture-level cities exhibited states of WD. The energy intensity and carbon emission intensity had negative inhibitory effects on ICEs, and economic development and the energy structure had positive promotion effects on ICEs. The research results have important theoretical and practical significance for future energy savings, carbon emissions reductions and the realization of a low-carbon economy in the economic development of Jiangsu.

Achieving decoupling between economic growth and carbon emissions is imperative for global sustainable development. This study provides a comparative analysis of this decoupling process in the European Union (EU) and BRICS countries from 1996 to 2023, employing the Tapio decoupling model and Logarithmic Mean Divisia Index (LMDI) decomposition analysis. Our findings reveal a stark contrast: the EU has achieved an average annual carbon emission growth rate of −1%, predominantly characterized by strong decoupling, whereas the BRICS nations exhibit an average growth rate of 6.26%, mainly in a state of weak decoupling. The LMDI results indicate that the intensity effect is the primary driver of carbon reduction in the EU, while the income effect is the most significant factor promoting emissions growth in the BRICS bloc. A novel finding is the identification of a near-symmetrical relationship between the energy transition effect and the fossil energy structure effect in the cumulative decomposition charts, offering a new perspective for evaluating energy system changes. The study concludes that while the EU demonstrates a more advanced decoupling pathway, significant internal disparities persist. For BRICS countries, mitigating the pressure from economic and population growth through industrial upgrading, differentiated energy policies, and enhanced renewable infrastructure is crucial. These insights provide valuable policy implications for both developed and developing economies in navigating their low-carbon transitions.

Decomposition and decoupling analysis of carbon emissions from economic growth: A comparative study of China and the United States

Taking Jiangxi’s agricultural sector as an example, we first computed the carbon emissions of Jiangxi’s agricultural sector during 2005-2018 in this paper, and then used the Tapio decoupling model to explore the decoupling status between the carbon emissions’ change and the economic growth. The results showed that: the carbon emissions of Jiangxi’s agriculture, first, increased from 236.98×104 t in 2005 to 274.00×104 t in 2015, and then decreased from 270.74×104 t in 2016 to 247.95×104 t in 2018. The decoupling relationship between the carbon emissions’ change and the economic growth mainly expressed as weak decoupling during 2005-2015 and strong decoupling during 2015-2018. The reason was that Jiangxi’s economy is no longer developing in an extensive way, but is shifting to a low-carbon development pattern. Namely, the carbon emissions from chemical fertilizer and pesticide were the most important part of agricultural carbon emissions. Moreover, this part’s emissions showed a significant downward trend along with the update of agriculture technology and the improvement of production efficiency. Thus, some particular suggestions to reduce the agricultural carbon emissions of Jiangxi were put forward.