Showing 4 results for Emission
Dr Mohammad Hassan Fotros, Javad Baraty,
Volume 1, Issue 1 (10-2010)
Abstract
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 .
Dr Majid Maddah, Forough Noe Iran,
Volume 3, Issue 10 (12-2012)
Abstract
Informal economy i.e. unrecorded economy, is one of the important problems in developing countries which affects the efficiency of economic activities in formal sector. Informal economy is also an important source of air pollution.
This paper aims at estimating informal economy in Iran over the period 1980-2009 based on the mount of CO2 emissions and the country forest areas and using Kalman Filter approach. The results indicate that: 1) there is a significant and long run relationship between CO2 emissions, the size of forest areas and firm’s industrial activities and total national product, 2) Total national product is more than recorded data in the study period so the existence of informal economy can’t be rejected during this period. 3) The average share of informal economy in total GDP is about 35.6 %.
Samira Motaghi,
Volume 8, Issue 30 (12-2017)
Abstract
The present paper reviews the impact of the development situation of 3 groups of selected developing countries on environment over the period of 1990 – 2014 using by Environment Kuznets Curve (EKC) hypothesis. For this, it uses economic, social, human and political development factors with the variables that are as follows: GDP, GDP2 and energy consumption as economic development indicators, Urbanization as social and life expectancy at birth and fertility rates as human development indicators and good governance used as political indicator. The results show an inverted U-shaped relationship real GDP per capita and CO2 emission in oil-exporting and whole sample and a U-shaped in non-oil – exporting countries. In addition, the estimated results show a meaningful relationship between the CO2 emission and real GDP, energy use fertility rate, expectancy at birth and urbanization (development situation) in all three groups of the country.
Somayeh Azami, Latif Poor-Karimi, Sahar Sadri,
Volume 9, Issue 31 (3-2018)
Abstract
The purpose of this study is to evaluate environmental productivity changes in Iranian manufacturing industries, with two-digit ISIC codes, during 2003-2014. For this purpose, Meta-frontier Non-radial Malmquist CO_2 emission Performance Index (MNMCPI) is used. This index considers technological heterogeneities of industries. Empirical results indicate that, during 2003-2014, MNMCPI has grown, on average; the highest growth rate belongs to industries with medium technology. Also, all three indices of EC, BPC and TGC, as MNMCPI components, experienced growth, on average. TGC has the greatest impact in industries with medium technology while BPC has the greatest impact in industries with high and low technology. In general, BPC had the greatest effect on MNMCPI growth.The highest growth rate in EC index is observed in industries with low technology and the highest growth rates in BPC index, which shows the effect of innovation, and in TGC index are observed in industries with medium technology. Therefore, based on TGC index, industries with medium technology level are leading technological industries. Rregression analysis shows that energy intensity has a negative and significant effect and R&D has a positive significant effect on MNMCPI.
