Driving forces of Iran's CO2 emissions from energy consumption: An LMDI decomposition approach

Mousavi, Babak; Lopez, Neil Stephen; Biona, Jose Bienvenido M.; Chiu, Anthony S.F.; Blesl, Markus

doi:10.1016/j.apenergy.2017.08.199

Cited by 242 publications

(80 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Overall results of energy and environmental indicators showed that the main drivers of Iran's CO 2 emission are economic growth and energy intensity. These findings are in line with the outcomes of Mousavi et al ., 29 who argued that economic activity is the main contributor to CO 2 emission in Iran. Moreover, Sumabat et al 48 .…”

Section: Resultssupporting

confidence: 92%

“…This increases concerns about the future impacts of environmental degradations on the country and global warming, human society threats, and long‐term droughts. Many studies have revealed that economic growth and low prices of fuel caused high fuel energy consumption and environmental problems in Iran 28,29 . While energy subsidies may lead to more energy consumption and CO 2 emissions, 30,31 empirical studies have emphasized the importance of the simultaneous impacts of the rise in GDP and energy consumption, particularly the magnitudes of the impacts of energy consumption, which are greater than the GDP effects 32–34 .…”

Section: Introductionmentioning

confidence: 99%

“…However, other studies revealed that the main contributor to Iran's CO 2 emissions is fossil fuel consumption and technology‐related improvements and use of natural gas in power plants and the transport sector was unable to offset CO 2 emission significantly 36,29 . Mousavi et al 29 . and Korsavi et al 30 .…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A CO₂ emissions assessment of the green economy in Iran

Solaymani

2020

Greenhouse Gases

View full text Add to dashboard Cite

This study aims to provide an assessment of total and sectoral CO2 emissions of Iran using a macroeconomic climate analysis. It uses two quantitative approaches (i.e., energy–economy–environment indicators and econometric analysis) that complement each other. According to the latest accessible data (1971–2016), evidence shows that, first, the change in Iran's total primary energy supply can significantly explain the variation of CO2 emissions in Iran, while energy intensity and CO2 intensity cannot significantly explain its variability. Second, CO2 emissions in Iran are increasing rapidly and the country is not moving toward the green economy situations. Third, the increase in energy intensity is mostly related to significant increases in energy consumption rather than increases in economic activity. This evidence shows that Iran's CO2 intensity highly depends on the consumption of fossil fuels. Fourth, the econometric estimates suggest that CO2 emissions, in comparison with other examined variables, change significantly in response to changes in per capita GDP, energy intensity, and carbon intensity. Fifth, the main contributors to industrial CO2 emissions are industrial per capita GDP and energy and carbon intensities, while in the transport sectors, the main contributors are the number of vehicles, transport energy intensity, and carbon intensity. Sixth, further decomposition analysis shows the positive impact of per capita GDP and the negative impacts of energy structure and energy efficiency on total CO2 emissions in Iran. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd.

show abstract

Section: Resultssupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A CO₂ emissions assessment of the green economy in Iran

Solaymani

2020

Greenhouse Gases

View full text Add to dashboard Cite

show abstract

“…Akbostanci et al applied LMDI to decompose the CO 2 emissions of the Turkish manufacturing industry into five influencing factors: overall activity, economy structure, sectoral energy intensity, sectoral energy structure, and CO 2 emission coefficient [45]. Babak Mousavi et al analyzed the influencing factors driving Iran's CO 2 emission changes [46]. Jeong et al decomposed the CO 2 emissions from South Korean industrial manufacturing into five influencing factors: economic activity, economic structure, energy intensity, energy-mix, and emission-factor [47].…”

Section: Literature Reviewmentioning

confidence: 99%

Investigation for the Decomposition of Carbon Emissions in the USA with C-D Function and LMDI Methods

Jiang

2019

Sustainability

View full text Add to dashboard Cite

Residual problems are one of the greatest challenges in developing new decomposition techniques, especially when combined with the Cobb-Douglas (C-D) production function and the Logarithmic Mean Divisia Index (LMDI) method. Although this combination technique can quantify more effects than LMDI alone, its decomposition result has residual value. We propose a new approach that can achieve non-residual decomposition by calculating the actual values of three key parameters. To test the proposed approach, we decomposed the carbon emissions in the United States to six driving factors: the labor input effect, the investment effect, the carbon coefficient effect, the energy structure effect, the energy intensity effect, and the technology state effect. The results illustrate that the sum of these factors is equivalent to the CO 2 emissions changes from t to t-1, thereby proving non-residual decomposition. Given that the proposed approach can achieve perfect decomposition, the proposed approach can be used more widely to investigate the effects of labor input, investment, and technology state on changes in energy and emission.

show abstract

“…Compared with the SDA, the Logarithmic Mean Divisia Index (LMDI) does not produce residual terms, which is better for time series analysis. The current literature applying the LMDI to investigate the effects on carbon emissions found that the economic structure, energy structure, industrial structure, income, population size, and renewable energy production capacity had impacts on carbon emission changes [33][34][35][36][37][38]. In analyses of APEs, some studies decomposed SO 2 emissions using this method.…”

mentioning

confidence: 99%

Decomposition Analysis of Factors that Drive the Changes of Major Air Pollutant Emissions in China at a Multi-Regional Level

Yang

Miao

et al. 2019

Sustainability

View full text Add to dashboard Cite

The regional emission reduction determines the national emission reduction for one country, and the differences in regional economic characteristics may result in regional differences in air pollutant emissions (APEs). In this regard, this study constructs a regional contribution index of different factors through an extended LMDI (Logarithmic Mean Divisia Index) method and investigates regional differences in factors driving the changes of China's major APEs (SO 2 , NO x , and PM 2.5 ). It reveals that the regional emission efficiency effect was a key inhibitory factor on APEs, which was more obvious in the eastern and northern regions. The regional energy intensity had greater inhibitory effects on SO 2 and NO x than on PM 2.5 , and these inhibitory effects were more obvious in the eastern region. The regional population structure promoted APEs for northern, southern, northeastern, and eastern regions, and inhibited APEs for central, southwestern, and northwestern regions. The regional relative income had a slight effect, which curbed APEs for northern, eastern, southern, and northern regions. The national economic growth effect was the key factor in promoting APEs, which was obvious in eastern and northern regions, followed by southern, central, and southwestern regions. Policy implications are put forward based on empirical results.Sustainability 2019, 11, 7113 2 of 22 reduction target for the 13th Five-Year Plan (FYP) (2016-2020) that by 2020 the energy consumption per 10,000 RMB GDP would be cut by 15% in comparison to 2015, and SO 2 and NO x would be within 15.8 and 15.74 million tons, respectively, which are both 15% lower than the level of 2015. There are regional differences in APEs for China because of its serious imbalances in economic development. As for the air pollutant reduction, the national reduction target should be reasonably allocated to each province and municipality as a regional target, to smoothly realize the national emission reduction target. Therefore, it is urgent and important to study the regional differences in factors that affect APEs in China, which is conductive to offer references for designing policies according to regional differences and effectively reduce air pollutant emissions (APEs).Many previous studies touched on the issues related to air pollutant emission trends and characteristics [6][7][8][9], and the harm to the economy and human health [10][11][12][13][14][15][16][17][18][19]. Recently, more attention has been focused on analyses of factors influencing APEs. Some studies established econometric models to discuss the relationships between APEs and macroeconomic variables [20][21][22][23] and explore the effects of these macroeconomic variables on APEs [24][25][26][27]. Some scholars analyzed sources of APEs from the sectoral perspective and found that the power and transport sectors were the main sources [28][29][30], followed by the agriculture and household sectors [31,32]. The decomposition method has been widely used to decompose factors influencing energy u...

show abstract

Driving forces of Iran's CO2 emissions from energy consumption: An LMDI decomposition approach

Cited by 242 publications

References 33 publications

A CO₂ emissions assessment of the green economy in Iran

A CO₂ emissions assessment of the green economy in Iran

Investigation for the Decomposition of Carbon Emissions in the USA with C-D Function and LMDI Methods

Decomposition Analysis of Factors that Drive the Changes of Major Air Pollutant Emissions in China at a Multi-Regional Level

Contact Info

Product

Resources

About

Driving forces of Iran's CO2 emissions from energy consumption: An LMDI decomposition approach

Cited by 242 publications

References 33 publications

A CO2 emissions assessment of the green economy in Iran

A CO2 emissions assessment of the green economy in Iran

Investigation for the Decomposition of Carbon Emissions in the USA with C-D Function and LMDI Methods

Decomposition Analysis of Factors that Drive the Changes of Major Air Pollutant Emissions in China at a Multi-Regional Level

Contact Info

Product

Resources

About

A CO₂ emissions assessment of the green economy in Iran

A CO₂ emissions assessment of the green economy in Iran