Decomposition Of CO2 Emissions Research Articles

Effects of trade liberalization on the global decoupling and decomposition of CO2 emissions from economic growth

Evidence of climate change is widespread and severe across all parts of the world. This poses a threat to humanity, and the entire environment. Appropriate policies are therefore required to help reduce greenhouse gas emission levels, limit the rate of global warming and its impact on climate change while pursuing national growth targets. This study employs the Tapio decoupling method to analyse the decoupling relationship (DR) between economic growth and carbon dioxide (CO2) emissions from 1998 to 2018. We also apply the Logarithmic Mean Divisia Index (LMDI) decomposition method on an extended Kaya identity to analyse CO2 emissions drivers in 145 countries. Last, the study examined the relative impacts of trade intensity and trade efficiency on the DR between economic growth and CO2 emissions. The results revealed that regions with relatively many developing and emerging countries (i.e., SSA, EAP, LAC, MENA, and SA) generally performed Weak Decoupling (WD), Expansive Negative Decoupling (END) and Expansive Coupling (EC), and the decoupling process was largely unstable. The ECA and NA regions on the other hand, which are typically composed of developed economies performed stable WD and Strong Decoupling (SD) statuses throughout the study period. The evidence further revealed that while trade intensity, activity, population, output per carbon emission and Carbon Intensity (CI) effects promote CO2 emissions, trade efficiency and energy intensity (EI) hinder emissions. We recommend that developing countries should enforce laws and cooperate with the developed economies to gain access to green technology to promote environmental sustainability.

Decomposition of the Kaya identity in the European Mediterranean countries over the 1990-2020 period with respect to CO2 emissions

The Kaya identity, proposed by Yoichi Kaya in 1993, attempts to evaluate the impact of total emissions of carbon dioxide (greenhouse gas) as the impact of human activity on the environment. The purpose of this work is the decomposition of CO2 emissions in the European Mediterranean countries (Cyprus, France, Greece, Italy, Malta, Slovenia and Spain) for a time period spanning from 1990 to 2020, based upon the Kaya identity into scale, technological and structural effect. For this purpose, the Tapio decoupling analysis is adopted. According to results, technology improvements leading to declining rates of carbon per unit of energy used and structural changes indicating the use of less energy per unit of production could help in counterbalancing the positive scale effect of GDP production in CO2 emissions per capita. This, however, requires the implementation of proper strategies focusing in improvements in technological change and structural changes in order to mitigate CO2 emissions without hindering the economic growth process.

Spatio-temporal analysis of decoupling and spatial clustering decomposition of CO2 emissions in 335 Chinese cities

• Spatio-temporal analysis of the decoupling of urban development levels and CO 2 emissions. • Spatial decomposition of CO 2 emissions for 335 cities. • Chinese cities can be clustered into nine types according to their development status and resource endowment. • The critical intra-group decomposition factors differed for the nine types of cities. • Population intensity is the most critical factor contributing to the inter-group differences in urban CO 2 emissions. The decoupling of urban development levels (UDL) and CO 2 emissions is an essential representation of sustainable urban development. The spatial decomposition of urban CO 2 emissions is an essential reference for achieving differential CO 2 emission reduction. This study first evaluates the UDL of 335 cities from 2009 to 2019 using the entropy weight-TOPSIS method. The Tapio decoupling method is used to analyze the spatio-temporal evolution of the decoupling relationship between UDL and CO 2 emissions. Second, the Logarithmic Mean Divisia Index (LMDI) method is used to spatially decompose urban CO 2 emissions and explore their key influencing factors. Finally, cities with the same development status and resource endowment are spatially clustered by density peaks. Moreover, the proposed spatial LMDI method is used for intra-group and inter-group decomposition of CO 2 emissions. The results show that the decoupling status can be divided into three stages. CO 2 emission intensity and electricity consumption intensity show mainly north–south differences, while other factors show mainly east–west differences. Cities can be classified into nine types by clustering, and the critical intra-group decomposition factors are different. Population intensity is the most critical factor contributing to the inter-group differences in urban CO 2 emissions, followed by land size and output intensity.

Decoupling and decomposition analysis of environmental impact from economic growth: a comparative analysis of Pakistan, India, and China

The dispute between economic growth and greenhouse gas emissions is one of the major challenges of the twenty-first century. The central issue of the emerging economies revolves around the decoupling of economic growth and the rising carbon dioxide (CO2) emissions. This study examines the decoupling the CO2 emissions from the economic growth through the employment of the Tapio decoupling index and decomposition of CO2 emissions into its pre-determined factors through the Log Mean Divisia Index (LMDI) decomposition technique for Pakistan, India, and China (PIC) for a time span of 1990–2014. The findings of the Tapio elasticity analysis depict that in a few years, environmental impact has been seen to be decoupled from the economic growth in the respective PIC countries. However, relatively Pakistan experienced expensive negative decoupling; India mostly experienced weak decoupling and expensive coupling, while China exhibited weak decoupling in multiple years. In addition, the analysis of Tapio decoupling elasticity showed that energy intensity is the key factor supporting the decoupling in PIC countries, while population, affluence (GDP per capita) and energy structure have weakened the progress of decoupling. Furthermore, the analysis of the LMDI decomposition suggested that population, energy structure and affluence in PIC countries increase the CO2 emissions, while energy intensity reduces CO2 emissions, while mixed effects are reflected by carbon intensity.

Decomposition of CO2 Emissions over 1980-2003 in Turkey

There is a multi-dimensional need for studying the energy situation in Turkey and to obtain insight into the development of CO2 emissions. On the one hand, recent projections of the OECD show that Turkey has a yearly GDP growth potential of over 7%. On the other hand, recent projections of UNDP and World Bank indicate that the level of CO2 emission is going to rise six-fold by 2025 with respect to the level of emissions in 1990. It is a great challenge to both meet the growth target and keep the CO2 under control. Thereupon, this paper tries to unfold factors that explain CO2 emissions by undertaking a complete decomposition analysis for Turkey over the period 1980-2003. The analysis shows, as is common to relatively fast growing economies, that the biggest contributor to the rise in CO2 emissions is the expansion of the economy (scale effect). The carbon intensity and the change in composition of the economy, which nearly move in tandem, also contribute to the rise in CO2 emissions, albeit at a slower rate. The energy intensity of the economy, which is decreasing, is responsible for a modest reduction in CO2 emissions. Hence, in congruence with the scale effect, we do not find a decoupling of carbon emissions and economic growth in Turkey over the period 1980-2003.