Cutting CO<sub>2</sub>emissions from the US energy sector: meeting a 50% target by 2030

Warnatzsch, Erika A.; Reay, Dave

doi:10.4155/cmt.10.36

Carbon Management

2011

DOI: 10.4155/cmt.10.36

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Cutting CO₂emissions from the US energy sector: meeting a 50% target by 2030

Erika A. Warnatzsch

Dave Reay

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2015

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CO₂emissions from Iran's power sector and analysis of the influencing factors using the stochastic impacts by regression on population, affluence and technology (STIRPAT) model

Noorpoor

Kudahi

2015

Carbon Management

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To cite this article: A.R. Noorpoor & S. Nazari Kudahi (2015): CO 2 emissions from Iran's power sector and analysis of the influencing factors using the stochastic impacts by regression on population, affluence and technology (STIRPAT) model, Carbon Management, ABSTRACTThe current status of CO 2 emissions from Iran's power sector and the socio-economic factors that influence these emissions are fully covered in this paper. To begin, the amount of CO 2 emissions is calculated based on the IPCC guidelines for national GHG inventories. The analysis of socio-economic influencing parameters is performed by the stochastic impacts by regression on population, affluence and technology (STIRPAT) model using population size, gross domestic product (GDP) per capita, electricity intensity and consumption of energy resources for electricity generation. Then CO 2 emissions related to the electricity consumption in six sectors (residential, industrial, public, agriculture, trade and lighting) as well as grid losses and internal electricity consumption of power plants are estimated. Finally, CO 2 emissions from Iran's power sector are compared with their alternatives in Turkey and China. The results indicate that CO 2 emissions increased from 78.778 Tg in 2003 to 149.691 Tg in 2013, and the average CO 2 specific emission factor is 571.29 g/kWh. The outputs of the STIRPAT model illustrate that population size, GDP per capita, electricity intensity and the consumption of fossil fuels for electricity generation positively influence CO 2 emissions, while electricity generation by hydropower, renewable energies and nuclear energy negatively do.

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CO₂emissions from Iran's power sector and analysis of the influencing factors using the stochastic impacts by regression on population, affluence and technology (STIRPAT) model

Noorpoor

Kudahi

2015

Carbon Management

View full text Add to dashboard Cite

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Cutting CO₂emissions from the US energy sector: meeting a 50% target by 2030

Cited by 1 publication

References 22 publications

CO₂emissions from Iran's power sector and analysis of the influencing factors using the stochastic impacts by regression on population, affluence and technology (STIRPAT) model

CO₂emissions from Iran's power sector and analysis of the influencing factors using the stochastic impacts by regression on population, affluence and technology (STIRPAT) model

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Cutting CO2emissions from the US energy sector: meeting a 50% target by 2030

Cited by 1 publication

References 22 publications

CO2emissions from Iran's power sector and analysis of the influencing factors using the stochastic impacts by regression on population, affluence and technology (STIRPAT) model

CO2emissions from Iran's power sector and analysis of the influencing factors using the stochastic impacts by regression on population, affluence and technology (STIRPAT) model

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Cutting CO₂emissions from the US energy sector: meeting a 50% target by 2030

CO₂emissions from Iran's power sector and analysis of the influencing factors using the stochastic impacts by regression on population, affluence and technology (STIRPAT) model

CO₂emissions from Iran's power sector and analysis of the influencing factors using the stochastic impacts by regression on population, affluence and technology (STIRPAT) model