Is India on the right pathway to reduce CO2 emissions? Decomposing an enlarged Kaya identity using the LMDI method for the period 1990–2016

Ortega-Ruiz, G.; Nieto, Ángel Isidro Mena; García‐Ramos, J. E.

doi:10.1016/j.scitotenv.2020.139638

Cited by 79 publications

(31 citation statements)

References 34 publications

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“…Kaya identity was proposed by (Kaya. 1989), and it reflected the factors that lead to the change of carbon emissions (Pui and Othman 2019;Ortega-Ruiz et al 2020).…”

Section: Comparison Of the Decomposition Methodsmentioning

confidence: 99%

Influencing factors and decoupling analysis of carbon emissions in China’s manufacturing industry

Jin

Han

2021

Environ Sci Pollut Res

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The manufacturing industry directly reflects national productivity, and it is also an industry with serious carbon emissions, which has attracted wide attention. This study decomposes the influential factors on carbon emissions in China's manufacturing industry from 1995 to 2018 into industry value added (IVA), energy consumption (E), fixed asset investment (FAI), carbon productivity (CP), energy structure (EC), energy intensity (EI), investment carbon intensity (ICI) and investment efficiency (IE) by Generalized Divisia Index Model (GDIM). The decoupling analysis is carried out to investigate the decoupling states of the manufacturing industry under the pressure of "low carbon" and "economy." Considering the technological heterogeneity, we study the influential factors and decoupling status of the light industry and the heavy industry. The results show that: (1) Carbon emissions of the manufacturing industry present an upward trend, and the heavy industry is the main contributor. (2) Fixed asset investment (FAI), industry value added (IVA) are the driving forces of carbon emissions. Investment carbon intensity (ICI), carbon productivity (CP), investment efficiency (IE), and energy intensity (EI) have inhibitory effects. The impact of the energy consumption (E) and energy structure (EC) are fluctuating. (3) The decoupling state of the manufacturing industry has improved. Fixed asset investment (FAI), industry value added (IVA) hinder the decoupling; carbon productivity (CP), investment carbon intensity (ICI), investment efficiency (IE), and energy intensity (EI) promote the decoupling.

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“…Kaya identity was proposed by (Kaya. 1989), and it reflected the factors that lead to the change of carbon emissions (Pui and Othman 2019;Ortega-Ruiz et al 2020).…”

Section: Comparison Of the Decomposition Methodsmentioning

confidence: 99%

Influencing factors and decoupling analysis of carbon emissions in China’s manufacturing industry

Jin

Han

2021

Environ Sci Pollut Res

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“…In addition to these, [164] studied India and China. India was also addressed in [165]. Still, on the Asian continent, Pakistan, Vietnam, Kazakhstan and Japan were studied by [166][167][168][169], respectively.…”

Section: Discussionmentioning

confidence: 99%

Renewable Energy, Economic Growth and Economic Development Nexus: A Bibliometric Analysis

Oliveira

Moutinho

2021

Energies

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The present research aims to conduct a systemic review on Renewable Energy, Economic Growth and Economic Development and look for links between the papers published between 2008 and May 2021. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, it was possible to reach a sample of 111 articles selected by Web of Science and a sample of 199 academic articles selected by Scopus in that specific period. The analysis of the group of Renewable and Non-renewable Energy Consumption, Economic Growth and Economic Development shows that most of the articles published in this subsample use the quantitative methodology in economic sciences. The results indicate that research on the subject has a growing trend and that most of the articles are post-2015 publications. In addition, China has been the leading nation in published works. The journal Renewable and Sustainable Energy Reviews is considered the most relevant in this category, and Sustainability has the most publications. Finally, a research gap was identified to be explored, lacking studies aimed at understanding the consumption of renewable energies and economic development and studies that focus on renewable energies and economic growth in less developed economies.

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“…After 2007, decreasing emissions were largely a result of economic recession with changes in fuel mix (for example, substitution of natural gas for coal) playing a comparatively minor role. Ortega-Ruiz et al [ 19 ] explored the main drivers of CO 2 emissions in India during 1990–2016. The results showed that India’s CO 2 emissions increased by 276% because of the rapid economic growth, while the energy intensity has been the main factor reducing CO 2 emissions by approximately −47%.…”

Section: Literature Reviewmentioning

confidence: 99%

Decomposition and Decoupling Analysis of CO2 Emissions Based on LMDI and Two-Dimensional Decoupling Model in Gansu Province, China

Xin

Jia

et al. 2021

IJERPH

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Currently, little attention has been paid to reducing carbon dioxide (CO2) emissions of Gansu, and the two-dimensional decoupling model has been rarely used to study the relationship between the economic development and CO2 emissions, especially in western China (e.g., Gansu). Thus, here, we first used the Logarithmic Mean Divisia Index (LMDI) to decompose the driving factors of Gansu’s CO2 emissions between 2000–2017 and then analyzed the decoupling relationship by using the two-dimensional model. Results showed: (1) Gansu’s CO2 emissions increased from 7805.70 × 104 t in 2000 to 19,896.05 × 104 t in 2017. The secondary industry accounted for the largest proportion in Gansu’s CO2 emissions, followed by the tertiary industry and the primary industry. (2) The economic output showed the dominant driving effect on Gansu’s CO2 emissions growth with the cumulative contribution rate of 201.94%, followed by the effects of industrial structure, population size, and energy structure, and their cumulative contribution rates were 9.68%, 7.81%, and 3.05%, respectively. In contrast, the energy intensity effect presented the most obvious mitigating effect with the cumulative contribution rate of −122.49%. (3) The Environmental Kuznets Curve (EKC) between CO2 emissions and economic growth was demonstrated the inverted U-shape in Gansu. The two-dimensional decoupling status was the low level-weak decoupling (WD-LE) during 2000–2017. Thus, dropping the proportion of the secondary industry, reducing the use of carbon-intensive fuel like coal, introducing advanced technologies, and increasing the investment of new energy might effectively restrain the growth of Gansu’s CO2 emissions.

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Is India on the right pathway to reduce CO2 emissions? Decomposing an enlarged Kaya identity using the LMDI method for the period 1990–2016

Cited by 79 publications

References 34 publications

Influencing factors and decoupling analysis of carbon emissions in China’s manufacturing industry

Influencing factors and decoupling analysis of carbon emissions in China’s manufacturing industry

Renewable Energy, Economic Growth and Economic Development Nexus: A Bibliometric Analysis

Decomposition and Decoupling Analysis of CO2 Emissions Based on LMDI and Two-Dimensional Decoupling Model in Gansu Province, China

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