Factors Affecting CO2 Emissions Research Articles

The effect of higher fuel price on pollutants emission in Iran

A key aspect of sustainable development in a country is how energy, environment and economic sectors interact. Greenhouse gas emissions and their impacts are among important environmental issues that have been in focus. The increase in the concentration of these gases in atmosphere to levels above the natural level results in global warming, depletion of the Earth’s protective layer against harmful solar radiation, and threatening whole natural life. The present study aimed at examining the factors affecting CO2 emission in Iran in 1981-2015. The studied variables included per capita CO2 emission, fuel price, per capita production, and per capita energy consumption. The relationship was examined by auto-regressive distributed lag (ARDL) model. It was found that CO2 emission is related to actual price of fuel indirectly and to per capita production and per capita energy consumption directly. According to the findings, 1% higher price of fuel would decrease CO2 emission by 0.14%, while 1% higher per capita production would increase it by 0.59%. Given the effectiveness of subsidy reform policy and the increased price of fuel on the alleviation of greenhouse gas emissions by road transport sector, it is advisable to gradually increase fuel price until it reaches FOB price in the Persian Gulf.

Using LMDI to Analyze the Decoupling of Carbon Dioxide Emissions from China’s Heavy Industry

China is facing huge pressure on CO2 emissions reduction. The heavy industry accounts for over 60% of China’s total energy consumption, and thus leads to a large number of energy-related carbon emissions. This paper adopts the Log Mean Divisia Index (LMDI) method based on the extended Kaya identity to explore the influencing factors of CO2 emissions from China’s heavy industry; we calculate the trend of decoupling by presenting a theoretical framework for decoupling. The results show that labor productivity, energy intensity, and industry scale are the main factors affecting CO2 emissions in the heavy industry. The improvement of labor productivity is the main cause of the increase in CO2 emissions, while the decline in energy intensity leads to CO2 emissions reduction, and the industry scale has different effects in different periods. Results from the decoupling analysis show that efforts made on carbon emission reduction, to a certain extent, achieved the desired outcome but still need to be strengthened.

Factors affecting CO2 emissions in China’s agriculture sector: Evidence from geographically weighted regression model

China is currently the world's largest emitter of carbon dioxide. Considered as a large agricultural country, carbon emission in China’s agriculture sector keeps on growing rapidly. It is, therefore, of great importance to investigate the driving forces of carbon dioxide emissions in this sector. The traditional regression estimation can only get “average” and “global” parameter estimates; it excludes the “local” parameter estimates which vary across space in some spatial systems. Geographically weighted regression embeds the latitude and longitude of the sample data into the regression parameters, and uses the local weighted least squares method to estimate the parameters point–by–point. To reveal the nonstationary spatial effects of driving forces, geographically weighted regression model is employed in this paper. The results show that economic growth is positively correlated with emissions, with the impact in the western region being less than that in the central and eastern regions. Urbanization is positively related to emissions but produces opposite effects pattern. Energy intensity is also correlated with emissions, with a decreasing trend from the eastern region to the central and western regions. Therefore, policymakers should take full account of the spatial nonstationarity of driving forces in designing emission reduction policies.

Impact of urbanization on energy related CO2 emission at different development levels: Regional difference in China based on panel estimation

We examined the influence of urbanization on CO2 emission at different development levels employing the stochastic impacts by regression on population, affluence and technology (STIRPAT) model on provincial panel data from 1995 to 2013 for China. To investigate regional differences based on development levels in the effects of urbanization on CO2 emission, we divided the 29 provinces of China into three regions according to their per capita real GDP at constant value (1990 = 100). The panel estimation for the whole dataset and the three regions showed an inverted U relationship between urbanization and CO2 emission in the major regions of China. Specifically, the effects of urbanization vary significantly across the regions. In region 2 and region 3, a threshold level was identified, beyond which the emission urbanization elasticity was negative, and further increases in the urbanization rate did not contribute to higher emissions. However, in region 1, only population and affluence, rather than urbanization, were significant factors affecting CO2 emissions. In addition, the results did not confirm the environmental Kuznets Curve relationship between income and CO2 emission, where CO2 emission increases monotonically with income. We propose a series of policy implications based on these outcomes to help realize emission reduction targets better.

Assessing CO2 emissions of electric vehicles in Germany in 2030

Electric vehicles are often said to reduce carbon dioxide (CO2) emissions. However, the results of current comparisons with conventional vehicles are not always in favor of electric vehicles. We outline that this is not only due to the different assumptions in the time of charging and the country-specific electricity generation mix, but also due to the applied assessment method. We, therefore, discuss four assessment methods (average annual electricity mix, average time-dependent electricity mix, marginal electricity mix, and balancing zero emissions) and analyze the corresponding CO2 emissions for Germany in 2030 using an optimizing energy system model (PERSEUS-NET-TS). Furthermore, we distinguish between an uncontrolled (i.e. direct) charging and an optimized controlled charging strategy. For Germany, the different assessment methods lead to substantial discrepancies in CO2 emissions for 2030 ranging from no emissions to about 0.55kg/kWhel (110g/km). These emissions partly exceed the emissions from internal combustion engine vehicles. Furthermore, depending on the underlying power plant portfolio and the controlling objective, controlled charging might help to reduce CO2 emissions and relieve the electricity grid. We therefore recommend to support controlled charging, to develop consistent methodologies to address key factors affecting CO2 emissions by electric vehicles, and to implement efficient policy instruments which guarantee emission free mobility with electric vehicles agreed upon by researchers and policy makers.

Factors Affecting CO2 Emissions in the BRICS Countries: A Panel Data Analysis

Abstract The effects of climate change are being felt on all continents of the world and these impacts are predicted to intensify in the coming decades. Unmitigated climate change poses great risks to human health, global food security, and economic development and to the natural world on which much of our prosperity depends. Society therefore needs to take measures to adapt to these unavoidable impacts while taking action to cut the greenhouse gas emissions that are contributing to climate change. This study analyzes the interactions that may exist between the total energy consumption, FDI, economic growth, and the emission of CO2 in the BRICS countries, using the co-integration tests and panel Granger causality in panel. The results show significantly that there is a co-integration relationship between CO2 emissions and economic variables. The results also indicate the existence of a unidirectional causality from CO2 to the independent variables. These results can help decision makers in these countries to understand and grasp the complexity of this phenomenon; a better understanding of this phenomenon will probably better guide future decisions to deal with this threat that weighs more heavily on the scene world politics.

Factors affecting CO2 emission in the Middle East: A panel data analysis

This study investigated the major factors that influence the CO2 emission in 12 Middle Eastern countries, namely, Bahrain, Egypt, Iran, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, the UAE, and Yemen. A panel model was used in this study and the period 1990–2009 was considered. The results showed that the total primary energy consumption, foreign direct investment net inflows, GDP, and total trade were important factors in increasing CO2 emission in the investigated countries. Thus, it is important for these counties to examine the requirements for foreign investment to promote environmental protection and increase the technological transfer through foreign companies to reduce the environmental damage. It is also important for them to adopt trade-related measures and policies to increase environmental protection since total trade increases CO2 emission. It is also crucial for these countries to increase energy productivity to achieve their GDP growth.

CO 2 Emission Trends in the Cement Industry: An International Comparison

We present an in-depth decompositionanalysis using physical indicators oftrends in Carbon dioxide (CO2) emissions in the cementindustry in Brazil, China, South Korea andthe United States. Physical indicatorsallow a detailed analysis of intra-sectoraltrends, in contrast to the often usedmonetary indicators. We assess thecontribution of different factors affectingCO2 emissions in the cement industry,including change in product mix, efficiencyof power generation, changes in fuel mixand changes in energy efficiency. Thedecomposition results show that in allexamined countries, increased productionwas the main contributor to the increase intotal CO2 emissions. Energy-efficiencyimprovement is the most important factorthat led to the reduction of emissionintensities for all countries except Korea.For Korea, structural change in the productmix is the most important factorcontributing to the emission intensityreduction.