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Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China
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TLDR
In this article, the authors examined the impact factors of population, economic level, technology level, urbanization level, GDP per capita, industrialization level and service level on the energy-related CO2 emissions in Guangdong Province, China from 1980 to 2010 using an extended STIRPAT model.Citations
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Impacts of urbanization and industrialization on energy consumption/CO2 emissions: Does the level of development matter?
Ke Li,Ke Li,Boqiang Lin +2 more
TL;DR: In this article, the authors adopted the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework as a starting point and re-estimated the relationship using different panel date models.
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The relationship between economic growth, energy consumption, and CO2 emissions: Empirical evidence from China.
TL;DR: The results of cointegration tests suggest the existence of long-run cointegrating relationship among the variables, albeit with short dynamic adjustment mechanisms, indicating that the proportion of disequilibrium errors that can be adjusted in the next period will account for only a fraction of the changes.
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Factors that influence carbon emissions due to energy consumption in China: Decomposition analysis using LMDI
TL;DR: In this article, the authors analyzed factors that influence carbon emissions due to fossil energy consumption in China to identify key factors for policies promoting carbon emission reductions and highlighted the policy implications in terms of industrial structure and energy consumption.
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CO2 emissions, economic and population growth, and renewable energy: Empirical evidence across regions
TL;DR: In this paper, the authors investigated the nexus among carbon dioxide emissions, economic and population growth, and renewable energy across regions using an unbalanced panel dataset of 128 countries over the period 1990-2014.
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Dynamic relationship among environmental regulation, innovation, CO2 emissions, population, and economic growth in OECD countries: a panel investigation
Rubayyat Hashmi,Khorshed Alam +1 more
TL;DR: In this article, the authors examined the effects of environmental regulation and innovation on the carbon emission reduction of OECD countries during the period 1999-2014 and developed a new model called "stochastic impacts by regression on population, affluence, regulation and technology" (STIRPART) to extend the analysis on the evaluation of factors influencing carbon emissions.
References
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CO2 emissions of Turkish manufacturing industry: A decomposition analysis
TL;DR: In this article, the authors used the Log Mean Divisia Index (LMDI) method to decompose the changes in the CO2 emissions of manufacturing industry into five components; changes in activity, activity structure, sectoral energy intensity, sectorual energy mix and emission factors.
Journal ArticleDOI
Analysis of the environmental impact of China based on STIRPAT model
TL;DR: In this paper, the authors analyzed the effect of population, urbanisation level, GDP per capita, industrialization level and energy intensity on the country's environmental impact using the STIRPAT model with data for 1978-2006.
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Analysis of regional difference on impact factors of China’s energy – Related CO2 emissions
TL;DR: Wang et al. as mentioned in this paper divided China's 30 provincial-level administrative units into five emission regions according to the annual average value of provincial CO2 emissions per capita during 1990 and 2010.
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Analysis on influence factors of China's CO2 emissions based on Path–STIRPAT model
TL;DR: Wang et al. as mentioned in this paper discussed the driving forces influencing China's CO 2 emissions based on Path-STIRPAT model, a method combining Path analysis with STIRP PAT (stochastic impacts by regression on population, affluence and technology) model.
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Examining the driving forces for improving China’s CO2 emission intensity using the decomposing method
TL;DR: In this article, the authors examined the driving forces for reducing China's CO2 emission intensity between 1998 and 2008, utilizing the logarithmic mean divisia index (LMDI) technique.
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