scholarly journals Using the LMDI Method to Analyze the Change in Greenhouse Gas Emissions in Turkish Sectors

2021 ◽  
Author(s):  
Abdulkadir BEKTAŞ
Keyword(s):  
Co2 Emissions ◽  
Heat Production ◽  
Economic Activity ◽  
Energy Intensity ◽  
Decomposition Analysis ◽  
Manufacturing Industries ◽  
Lmdi Method ◽  
Gaseous Fuels ◽  
Turkish Economy ◽  
Determining Factors

In this study, CO2 emissions of the Turkish economy are decomposed for the 1998–2017 period for four sectors; agriculture, forestry and fishery, manufacturing industries and construction, public electricity and heat production, transport, and residential. The analyses are conducted for five fuel types; liquid, solid, gaseous fuels, biomass, and other fuels. In decomposition analysis, Log Mean Divisia Index (LMDI) method is used. The analysis results point out that energy intensity is one of the determining factors behind the change in CO2 emissions, aside from economic activity. The fuel mix component, especially for the manufacturing industries and construction sector, lowers CO2 emissions during the crisis periods when the economic activity declines. Mainly, it is found that changes in total industrial activity and energy intensity are the primary factors determining the changes in CO2 emissions during the study period. Among GDP sectors, manufacturing industries and construction and public electricity and heat production are the two sectors that dominate the change in CO2 emissions. Additionally, the residential and transport sectors’ contributions have gained importance during recent years. Among the manufacturing industries and construction, the non-metallic minerals sector contributes to CO2 emissions, followed by the chemicals sector.

Decomposition analysis of the change of energy intensity of manufacturing industries in Thailand

Energy ◽  
2014 ◽  
Vol 77 ◽  
pp. 171-182 ◽  
Author(s):  
Jaruwan Chontanawat ◽  
Paitoon Wiboonchutikula ◽  
Atinat Buddhivanich
Keyword(s):  
Energy Intensity ◽  
Decomposition Analysis ◽  
Manufacturing Industries

scholarly journals Decomposition Analysis of CO2 Emissions for Turkey and Iran over 1990-2010

2014 ◽  
Author(s):  
Hasan Rüstemoğlu ◽  
Sevin Uğural
Keyword(s):  
Co2 Emissions ◽  
Scale Effect ◽  
Energy Intensity ◽  
Decomposition Analysis ◽  
Carbon Intensity ◽  
Composition Effect ◽  
Economic Sectors ◽  
Intensity Effect ◽  
The World ◽  
Laspeyres Index

There exists an important awareness for reduction of CO2 emissions to obtain a sustainable world. Together with this, there is a great deal of interest for decomposition analysis to see the accelerating and decelerating factors of CO2 emissions. The aim of this project is to decompose CO2 emissions in economic sectors for the two superpowers of Middle East, Iran and Turkey, over the time period between 1990 and 2010, for Turkey obtained a rapid growth performance in recent years and Iran which is the energy superpower of the world. Refined Laspeyres Index decomposition method and a consistent data gathered from the World Bank’s and UN’s databases have been used during the analysis. Five main sectors (agriculture, manufacturing, transportation, construction and other service sectors) and four main impacts (scale effect, composition effect, energy intensity effect and carbon intensity effect) have been considered to see the increasing and decreasing factors of CO2 emissions. Various interesting results are observed for both of the countries, for each of the economic sectors. Generally scale effect and energy intensity effect are the dominant impacts for all sectors of both countries. However composition effect and carbon intensity effect are also important contributors for economic activities of these two countries. Overall, our analysis showed that these two countries should pay attention for energy intensity and sustainable economic growth.

scholarly journals Decomposition of Carbon Dioxide (CO2) Emissions in ASEAN Based on Kaya Identity

2021 ◽  
Vol 4 (2) ◽  
pp. 101-114
Author(s):  
Vivid Amalia Khusna ◽  
Deni Kusumawardani
Keyword(s):  
Co2 Emissions ◽  
Economic Activity ◽  
Energy Intensity ◽  
Carbon Intensity ◽  
Middle Income ◽  
Middle Income Countries ◽  
Brunei Darussalam ◽  
Asean Countries ◽  
Carbon Dioxide Co2 ◽  
Kaya Identity

ASEAN is a region with high carbon dioxide (CO2) emissions, accompanied by an increase in population, gross domestic product (GDP) and energy consumption. Population, GDP, and energy consumption can be linked to CO2 emissions through an identity equation called the Rich Identity. This research is based on Kaya identity to describe CO2 emissions to calculate the impact of population, economic activity, energy intensity and carbon intensity on CO2 emissions in ASEAN and 8 ASEAN countries (i.e., Indonesia, Malaysia, Singapore, Thailand, Philippines, Vietnam, Myanmar and Brunei Darussalam) from 1990 to 2017. The method used is the Logarithmic Mean Division Index (LMDI). The data used are from the International Energy Agency (IEA) and the World Bank. Four effects measured and main findings showed that population, economic activity and carbon intensity factor increased by 293.02 MtCO2, 790.0 MtCO2, and 195.51 MtCO2, respectively. Meanwhile, energy intensity effect made ASEAN's CO2 emissions decrease by 283.13 MtCO2. Regarding contributions to the increase in CO2 emissions in all ASEAN countries, the population effect increases CO2 emissions in all countries in ASEAN and the economic activity effect is also the same, except in Brunei Darussalam which makes CO2 emissions in this country decreased by 1.07 MtCO2. Meanwhile, the effects of energy and carbon intensity are different. The effect of energy intensity causes CO2 emissions in lower-middle income countries to decrease, while in upper-middle and high-income countries, it increases carbon emissions. In contrast to the effect of carbon intensity, that actually makes CO2 emissions increase in lower-middle income countries and reduces carbon emissions in upper-middle and high-income countries.

scholarly journals Long-Term Increases and Recent Slowdowns of CO2 Emissions in Korea

2020 ◽  
Vol 12 (17) ◽  
pp. 6924
Author(s):  
Wankeun Oh ◽  
Jonghyun Yoo
Keyword(s):  
Co2 Emissions ◽  
Energy Intensity ◽  
Decomposition Analysis ◽  
Carbon Intensity ◽  
Analysis Model ◽  
Economic Sectors ◽  
Support Strategies ◽  
Index Decomposition ◽  
End Use

Korea is one of the fastest-growing CO2-emitting countries but has recently experienced a dramatic slowdown in emissions. The objective of the study is to examine the driving factors of long-term increases (1990–2015) and their slowdown (2012–2015) in emissions of Korea. This study uses an extended index decomposition analysis model that better fits Korea’s emission trends of the last 25 years by encompassing 19 energy end-use sectors (18 economic sectors and a household sector) and three energy types. The results show that emission increases in the long term (1990–2015) come from economic growth and population growth. However, improvements in energy intensity, carbon intensity, and economic structure offset large portions of CO2 emissions. The recent slowdown (2012–2015) mainly resulted from a decline in energy intensity and carbon intensity in the economic sectors. Among the different energy types, electricity has played a significant role in decreasing emissions because industries have reduced the consumption of electricity per output and the source of electricity generation has shifted to cleaner energies. These results imply that the Korean government should support strategies that reduce energy intensity and carbon intensity in the future to reduce CO2 emissions and maintain sustainable development.

scholarly journals Determinants of Energy-Based CO2 Emissions in Ethiopia: A Decomposition Analysis from 1990 to 2017

2020 ◽  
Vol 12 (10) ◽  
pp. 4175 ◽  
Author(s):  
Gideon Nkam Taka ◽  
Ta Thi Huong ◽  
Izhar Hussain Shah ◽  
Hung-Suck Park
Keyword(s):  
Co2 Emissions ◽  
Emission Intensity ◽  
Energy Intensity ◽  
Fossil Fuel ◽  
Driving Forces ◽  
Economic Effect ◽  
Decomposition Analysis ◽  
Rapid Urbanization ◽  
Intensity Effect ◽  
Decomposition Approach

Ethiopia, among the fastest growing economies worldwide, is witnessing rapid urbanization and industrialization that is fueled by greater energy consumption and high levels of CO2 emissions. Currently, Ethiopia is the third largest CO2 emitter in East Africa, yet no comprehensive study has characterized the major drivers of economy-wide CO2 emissions. This paper examines the energy-related CO2 emissions in Ethiopia, and their driving forces between 1990 and 2017 using Kaya identity combined with Logarithmic Mean Divisia Index (LMDI) decomposition approach. Main findings reveal that energy-based CO2 emissions have been strongly driven by the economic effect (52%), population effect (43%), and fossil fuel mix effect (40%) while the role of emission intensity effect (14%) was less pronounced during the study period. At the same time, energy intensity improvements have slowed down the growth of CO2 emissions by 49% indicating significant progress towards reduced energy per unit of gross domestic product (GDP) during 1990-2017. Nonetheless, for Ethiopia to achieve its 2030 targets of low-carbon economy, further improvements through reduced emission intensity (in the industrial sector) and fossil fuel share (in the national energy mix) are recommended. Energy intensity could be further improved by technological innovation and promotion of energy-frugal industries.

scholarly journals Energy Related CO2 Emissions before and after the Financial Crisis

2020 ◽  
Vol 12 (9) ◽  
pp. 3867 ◽  
Author(s):  
Perry Sadorsky
Keyword(s):  
Financial Crisis ◽  
Co2 Emissions ◽  
Economic Activity ◽  
Energy Intensity ◽  
Carbon Intensity ◽  
Contributing Factors ◽  
Crisis Period ◽  
Country Level ◽  
Before And After ◽  
Carbon Dioxide Co2

The 2008–2009 financial crisis, often referred to as the Great Recession, presented one of the greatest challenges to economies since the Great Depression of the 1930s. Before the financial crisis, and in response to the Kyoto Protocol, many countries were making great strides in increasing energy efficiency, reducing carbon dioxide (CO2) emission intensity and reducing their emissions of CO2. During the financial crisis, CO2 emissions declined in response to a decrease in economic activity. The focus of this research is to study how energy related CO2 emissions and their driving factors after the financial crisis compare to the period before the financial crisis. The logarithmic mean Divisia index (LMDI) method is used to decompose changes in country level CO2 emissions into contributing factors representing carbon intensity, energy intensity, economic activity, and population. The analysis is conducted for a group of 19 major countries (G19) which form the core of the G20. For the G19, as a group, the increase in CO2 emissions post-financial crisis was less than the increase in CO2 emissions pre-financial crisis. China is the only BRICS (Brazil, Russia, India, China, South Africa) country to record changes in CO2 emissions, carbon intensity and energy intensity in the post-financial crisis period that were lower than their respective values in the pre-financial crisis period. Compared to the pre-financial crisis period, Germany, France, and Italy also recorded lower CO2 emissions, carbon intensity and energy intensity in the post-financial crisis period. Germany and Great Britain are the only two countries to record negative changes in CO2 emissions over both periods. Continued improvements in reducing CO2 emissions, carbon intensity and energy intensity are hard to come by, as only four out of nineteen countries were able to achieve this. Most countries are experiencing weak decoupling between CO2 emissions and GDP. Germany and France are the two countries that stand out as leaders among the G19.

scholarly journals An Analysis of Energy-related Greenhouse Gas Emissions in Turkish Energy-intensive Sectors

2020 ◽  
Author(s):  
Abdulkadir BEKTAŞ
Keyword(s):  
Greenhouse Gas ◽  
Co2 Emissions ◽  
Economic Activity ◽  
Energy Intensity ◽  
Driving Forces ◽  
Ghg Emissions ◽  
Low Carbon ◽  
Activity Effect ◽  
Reduction Of Co2 ◽  
The Impact

In recent decades, greenhouse gas (GHG) emissions have been a critical priority of global environmental policy. The leading cause of the increase in GHG triggering global warming in the atmosphere is the continuously growing demand for universal energy due to population and economic growth. Energy efficiency and reduction of CO2 emissions in highly-energy consuming sectors of Turkey are critical in deciding a low-carbon transition. In this study, the change of energy-related CO2 emissions in Turkey’s energy-intensive four sectors from 1998 to 2017 is analyzed based on the Logarithmic Mean Divisia Index (LMDI) method. It is used to decompose CO2 equivalent emissions changes in these sectors into five driving forces; changes in economic activity, activity mix, energy intensity, energy mix, and emission factors. Analytical results indicate that economic activity is a vital decisive factor in determining the change in CO2 emissions as well as sectoral energy intensity. The activity effect has raised CO2 emissions, while energy intensity has decreased. This method indicates that the impact of the energy intensity could be the first key determinant of GHG emissions. Turkey's efforts to be taken in these sectors in adopting low carbon growth policies and reducing energy-related emissions to tackle climate change are clarified in detail.

A Decomposition Analysis of Developing Low-Carbon Economy in Dalian Industry Sector

2011 ◽  
Vol 361-363 ◽  
pp. 1954-1959
Author(s):  
Xiao Yu Liu ◽  
Hai Lin Mu ◽  
Hua Nan Li ◽  
Miao Li
Keyword(s):  
Economic Activity ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Decomposition Analysis ◽  
Low Carbon ◽  
Energy Mix ◽  
Low Carbon Economy ◽  
Industry Sector ◽  
Industrial Energy ◽  
Carbon Economy

In this paper, we utilize Logarithmic Mean Divisia Index (LMDI) techniques to decompose different components —CO2 emission factor, industrial energy mix, industrial energy intensity, industrial-scale structure, industrial structure, economic activity, family size and family households—which contribute to the changes in CO2 emissions in Dalian industry sector based on industry economy and CO2 emissions data in Dalian from 2000 to 2009. The results show that the economic activity was the main component for CO2 emissions increase, and energy intensity was the most favorable component in developing low-carbon economy in Dalian industry sector, and optimize energy mix could contribute to a significant reduction in CO2 emissions.

scholarly journals Decomposition Analysis of the Carbon Emissions of the Manufacturing and Industrial Sector in Thailand

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 798
Author(s):  
Jaruwan Chontanawat ◽  
Paitoon Wiboonchutikula ◽  
Atinat Buddhivanich
Keyword(s):  
Co2 Emissions ◽  
Emission Intensity ◽  
Co2 Emission ◽  
Energy Intensity ◽  
Manufacturing Sector ◽  
Decomposition Analysis ◽  
Intensity Change ◽  
Positive Contribution ◽  
Intensity Effect ◽  
Co2 Emission Intensity

Since the 1990s, CO2 emissions have increased steadily in line with the growth of production and the use of energy in the manufacturing sector in Thailand. The Logarithmic Mean Divisia Index Method is used for analysing the sources of changes in CO2 emissions as well as the CO2 emission intensity of the sector in 2000–2018. On average throughout the period, both the amount of CO2 emissions and the CO2 emission intensity increased each year relative to the baseline. The structural change effect (effect of changes of manufacturing production composition) reduced, but the intensity effect (effect of changes of CO2 emissions of individual industries) increased the amount of CO2 emissions and the CO2 emission intensity. The unfavourable CO2 emission intensity change came from the increased energy intensity of individual industries. The increased use of coal and electricity raised the CO2 emissions, whereas the insignificant change in emission factors showed little impact. Therefore, the study calls for policies that decrease the energy intensity of each industry by limiting the use of coal and reducing the electricity used by the manufacturing sector so that Thailand can make a positive contribution to the international community’s effort to achieve the goal of CO2 emissions reduction.

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