Volume 1, Issue 1 (10-2010)                   jemr 2010, 1(1): 135-154 | Back to browse issues page

XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Fotros M H, baraty J. Analysis of Effective Factors Affecting Changes in CO2 Emissions of Power Plants Sector of Iran, 1997-2008. jemr 2010; 1 (1) :135-154
URL: http://jemr.khu.ac.ir/article-1-196-en.html
Abstract:   (19832 Views)

  The power sector in Iran accounts for a share of 28.2 percent of the total CO2 emissions, so it is the biggest emitter of greenhouse gases. This study uses Logarithmic Mean Divisia Index (LMDI) technique to examine the role of five factors (economic growth, fuel intensity, electricity intensity, structure and quality of fuel) influencing CO2 emissions of the Power Plant sector in the period 1997-2008. Thermal efficiency and the fuel mix effects have been analyzed to determine the factors affecting changes in CO2 emissions index. The results show that the economic growth has the highest effect on the increase of CO2 emissions in the power sector during the whole period of study. Then, fuel quality effect, fuel intensity effect and the structure of production effect respectively, have influenced the growth of CO2 emissions. Changes in fuel mix have had the greatest effect on the increase of CO2 emission index, especially for the period 1387-83. Emission index displays that combined cycle power plant has the least emission index among all types of thermal power plants and hence it is the most suitable thermal power plant for the environment amongst thermal power plants .

Full-Text [PDF 757 kb]   (5719 Downloads)    
Type of Study: بنیادی | Subject: انرژی، منابع و محیط زیست
Received: 2011/04/10 | Accepted: 2013/03/6 | Published: 2013/03/6

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Journal of Economic Modeling Research

Designed & Developed by : Yektaweb