Structural decomposition of variations of carbon dioxide emissions for the United States, the European Union and BRIC

Sesso, Patrícia Pompermayer; Vieira, Saulo Fabiano Amâncio; Zapparoli, Irene Domenes; Filho, Umberto Antônio Sesso

doi:10.1016/j.jclepro.2019.119761

Cited by 21 publications

(10 citation statements)

References 13 publications

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“…Zheng et al (2019) found that China's CO 2 emissions presented a plateauing trend after the beginning of the 'new normal' economy, and this trend was driven by the decline in energy intensity due to China's technology investment, energy pricing and restructuring. Pompermayer Sesso et al (2020) conducted an SDA analysis and found that both the USA and the EU realized emissions reductions in 2000-2009; the emissions reductions in the USA were driven by the intensity effect, and those in the EU were driven by the technology effect. Henriques and Borowiecki (2017) applied an LMDI decomposition to study the drivers of CO 2 emissions changes in Europe, North America and Japan during 1800-2010; they found that the growth of GDP per capita and population was the main driver of emissions growth, while energy intensity improvement through technological progress was the main offsetting driver.…”

Section: Introductionmentioning

confidence: 99%

Drivers of global and national CO₂ emissions changes 2000–2017

et al. 2020

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Understanding the drivers of CO 2 emissions changes is useful in supporting future mitigation. This study applies a log-mean divisia index decomposition to assess four drivers of CO 2 emissions changespopulation, income, energy intensity and carbon intensityin 138 countries worldwide over the period 2000-2017. At the global level, income and population are the main drivers of increased emissions over time, with contributions of 116% and 60% to global CO 2 emissions changes, respectively. Energy intensity is the key mitigation driver, with a contribution of −80%. Although carbon intensity increased CO 2 emissions overall over the period 2000-2017 with a contribution of 4%, it has started to reduce emissions in recent years. China, the United States of America, the European Union, India and Russia are the five regions responsible for most changes in global emissions. The five regions together contribute −73% of the energy intensity effect, and China's income contribution is 83% in relation to the total of 116%. At the national level, in 2017, CO 2 emissions returned to below 2000 levels in 62% of Annex I (developed) countries but increased in 88% of non-Annex I (mostly developing) countries. Among the 35 countries realizing CO 2 emissions reductions, 24 were driven primarily by energy intensity, six by carbon intensity, three by economic recession, and one by population decrease. Among the 103 countries with increasing CO 2 emissions, 63 were driven primarily by income, 26 by population, nine by carbon intensity increase, and five by energy intensity increase. Our analysis emphasizes the necessity of considering differences in national development stages when formulating climate change mitigation policies. Key policy insights:. Over the period 2000-2017, at the global and national levels, CO 2 emissions increases were driven mainly by economic development and population growth, and mitigation was driven mainly by energy intensity improvement.. Improving energy intensity and carbon intensity is the key to mitigating CO 2 emissions. Carbon intensity is expected to play an increasing role in the future.. In over one-third of Annex I countries, CO 2 emissions increased from 2000 to 2017. To meet the Paris Agreement goals, Annex I countries will need to enhance mitigation ambition by further tapping the mitigation potentials of energy and carbon intensity.. In accordance with national circumstances, development needs and international support, non-Annex I countries should achieve low-carbon economic and energy transitions and peak CO 2 emissions as early as possible.

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Section: Introductionmentioning

confidence: 99%

Drivers of global and national CO₂ emissions changes 2000–2017

et al. 2020

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“…For example, Cheng et al utilized a dynamic spatial panel model to show spatial differences in the impact of industrial structure on China’s carbon intensity [ 25 ]. Other researchers have looked at the carbon reduction effect of industrial restructuring using the input–output table, STIRPAT, and other models [ 26 , 27 , 28 ]. (3) The impact of industrial restructuring on carbon emissions at different scales: Scholars have addressed this issue from the global, national, regional, and urban scales [ 29 , 30 , 31 , 32 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Study of the Impact of Industrial Restructuring on the Spatial and Temporal Evolution of Carbon Emission Intensity in Chinese Provinces—Analysis of Mediating Effects Based on Technological Innovation

Wang

et al. 2022

IJERPH

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Global warming caused by greenhouse gas emissions seriously threatens a region's sustainable environmental and socioeconomic development. Promoting industrial restructuring and strengthening technological innovation have become an important path to achieving pollution and carbon reduction as well as the green transformation of economic structure. This paper explored the mechanism of the mediating effect of technological innovation on industrial restructuring and carbon reduction while accounting for the direct effect of industrial restructuring on carbon emissions. Then, based on China's provincial panel data from 2001 to 2019, we estimated the carbon emission intensity using the Intergovernmental Panel on Climate Change (IPCC)'s methods and analyzed its spatiotemporal evolution characteristics. Finally, we constructed a fixed-effect model and a mediating effect model to empirically analyze how industrial restructuring and technological innovation affect carbon emission intensity. The results are as follows: (1) From 2001 to 2019, China's carbon emission intensity showed a continuous downward trend, with a pronounced convergence trend; there were obvious differences in carbon emission intensity between eastern, central, and western regions (western region > central region > eastern region) due to the unbalanced industrial structure. (2) In terms of direct effects, industrial restructuring can significantly reduce carbon emission intensity. The intensity of the effect is inversely proportional to the level of industrial restructuring, and the results of sub-regional tests are similar. Nevertheless, there is an obvious regional difference in the size of the carbon emission reduction effect of industrial restructuring in the east, central, and western regions. (3) In terms of indirect effects, industrial restructuring can reduce carbon emission intensity by enhancing technological innovation, and it acts as a mediating variable in the process of industrial restructuring to reduce carbon emission. Finally, we put forward recommendations for promoting industrial restructuring, strengthening green technological innovation, and properly formulating carbon reduction measures to provide a reference for countries and regions to achieve the goals of carbon neutrality, carbon peaking, and high-quality economic development.

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“…China's CO2 emissions increases were driven by economic development and population (Zheng et al 2020), but since 2012, the beginning of the new normal economy, emissions showed a plateauing trajectory which was driven by improvements in energy intensity (Zheng, Mi, Coffman, Shan, Guan and Wang 2019). As an HI country and ranked second in global emissions, USA's emissions decrease by energy intensity and carbon intensity improvements, while income and population continued to increase emissions (Sesso, Amancio-Vieira, Zapparoli and Sesso Filho, 2020;Henriques and Borowiecki, 2017;Xia et al, 2020). EU which mostly comprises of HI countries realizes emissions reductions since the 2000s by improvements in energy intensity, but income and population factors have still increasing effect on its emissions (Sesso et al, 2020;Henriques and Borowiecki, 2017;Perrier, Guivarch, Boucher, 2019;Xia et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

“…As an HI country and ranked second in global emissions, USA's emissions decrease by energy intensity and carbon intensity improvements, while income and population continued to increase emissions (Sesso, Amancio-Vieira, Zapparoli and Sesso Filho, 2020;Henriques and Borowiecki, 2017;Xia et al, 2020). EU which mostly comprises of HI countries realizes emissions reductions since the 2000s by improvements in energy intensity, but income and population factors have still increasing effect on its emissions (Sesso et al, 2020;Henriques and Borowiecki, 2017;Perrier, Guivarch, Boucher, 2019;Xia et al, 2020). In India and Russia, the other two most contributing countries, energy intensity was the primary mitigating factor, and while income acted to increase emissions in Russia, income and population together were resulting increase in India's emissions (Xia et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Üreti̇m Mi̇, Tüketi̇m Mi Beli̇rleyi̇ci̇? 1990-2015 Yillarinda Türkiye Co2 Emisyonlarinin Kaynaklari Ve Poli̇ti̇ka Etki̇leri̇

Alkan

Binatlı

2021

Hacettepe Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi

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Turkey's CO2 emissions have been steadily increasing since the 1990s. Determining influences of socioeconomic factors behind this increase can help identify which sectors and what types of policies should be prioritized to go into action. This paper identifies the main contributors to CO2 emissions change within five-year intervals during 1990-2015 by adopting the Structural Decomposition Analysis (SDA) method. The results show that CO2 emissions increase was driven by per capita expenditure and population factors, while emission coefficient factor had a reducing effect on emissions. As the production side factors fell pretty behind the consumption side factors, net emissions were positive and the actual determiner in CO2 emissions was found as consumption. The most contributing sectors were Electricity, Land Transportation and Mineral. Speeding up renewable energy investments and continuing energy efficiency measures, placing a carbon tax on electricity and oil consumption, promoting public transport and use of clean fuels and vehicles, slowing down construction and raising consumer awareness to change their consumption behavior, particularly to reduce demand for high emitting products and services should be the top priority policies.

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Structural decomposition of variations of carbon dioxide emissions for the United States, the European Union and BRIC

Cited by 21 publications

References 13 publications

Drivers of global and national CO₂ emissions changes 2000–2017

Drivers of global and national CO₂ emissions changes 2000–2017

Study of the Impact of Industrial Restructuring on the Spatial and Temporal Evolution of Carbon Emission Intensity in Chinese Provinces—Analysis of Mediating Effects Based on Technological Innovation

Üreti̇m Mi̇, Tüketi̇m Mi Beli̇rleyi̇ci̇? 1990-2015 Yillarinda Türkiye Co2 Emisyonlarinin Kaynaklari Ve Poli̇ti̇ka Etki̇leri̇

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Structural decomposition of variations of carbon dioxide emissions for the United States, the European Union and BRIC

Cited by 21 publications

References 13 publications

Drivers of global and national CO2 emissions changes 2000–2017

Drivers of global and national CO2 emissions changes 2000–2017

Study of the Impact of Industrial Restructuring on the Spatial and Temporal Evolution of Carbon Emission Intensity in Chinese Provinces—Analysis of Mediating Effects Based on Technological Innovation

Üreti̇m Mi̇, Tüketi̇m Mi Beli̇rleyi̇ci̇? 1990-2015 Yillarinda Türkiye Co2 Emisyonlarinin Kaynaklari Ve Poli̇ti̇ka Etki̇leri̇

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Drivers of global and national CO₂ emissions changes 2000–2017

Drivers of global and national CO₂ emissions changes 2000–2017