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 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.

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 Driving Forces of Energy-Related CO2 Emissions Based on Expanded IPAT Decomposition Analysis: Evidence from ASEAN and Four Selected Countries

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 764 ◽  
Author(s):  
Jaruwan Chontanawat
Keyword(s):  
Population Growth ◽  
Co2 Emissions ◽  
Energy Demand ◽  
Energy Use ◽  
Driving Forces ◽  
Global Climate ◽  
Decomposition Analysis ◽  
Driving Factors ◽  
Carbon Intensity ◽  
Rapid Urbanization

ASEAN is a dynamic and diverse region which has experienced rapid urbanization and population growth. Their energy demand grew by 60% in the last 15 years. In 2013, about 3.6% of global greenhouse-gas emissions was emitted from this region and the share is expected to rise substantially. Hence, a better understanding of driving forces of the changes in CO2 emissions is important to tackle global climate change and develop appropriate policies. Using IPAT combined with variance analysis, this study aims to identify the main driving factors of CO2 emissions for ASEAN and four selected countries (Indonesia, Malaysia, Philippines and Thailand) during 1971–2013. The results show that population growth and economic growth were the main driving factors for increasing CO2 emissions for most of the countries. Fossil fuels play an important role in increasing CO2 emissions, however the growth in emissions was compensated by improved energy efficiency and carbon intensity of fossil energy. The results imply that to decouple energy use from high levels of emissions is important. Proper energy management through fuel substitution and decreasing emission intensity through technological upgrades have considerable potential to cut emissions.

Decomposition analysis of energy-related CO2 emissions in South Africa

2015 ◽  
Vol 26 (1) ◽  
pp. 67-73 ◽  
Author(s):  
Ming Zhang ◽  
Shuang Dai ◽  
Yan Song
Keyword(s):  
South Africa ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Driving Forces ◽  
Dominant Role ◽  
Decomposition Analysis ◽  
Structure Effect ◽  
Energy Structure ◽  
Index Method ◽  
Intensity Effect

South Africa has become one of the most developing countries in the world, and its economic growth has occurred along with rising energy-related CO2 emission levels. A deeper understanding of the driving forces governing energy-related CO2 emissions is very important in formulating future policies. The LMDI (Log Mean Divisia Index) method is used to analyse the contribution of the factors which influence energy-related CO2 emissions in South Africa over the period 1993-2011. The main conclusions drawn from the present study may be summarized as follows: the energy intensity effect plays the dominant role in decreasing of CO2 emission, followed by fossil energy structure effect and renewable energy structure effect; the economic activity is a critical factor in the growth of energy-related CO2 emission in South Africa.

scholarly journals Drivers Analysis of CO2 Emissions from the Perspective of Carbon Density: The Case of Shandong Province, China

2018 ◽  
Vol 15 (8) ◽  
pp. 1762 ◽  
Author(s):  
Feng Dong ◽  
Jingyun Li ◽  
Yue-Jun Zhang ◽  
Ying Wang
Keyword(s):  
Co2 Emissions ◽  
Traffic Congestion ◽  
Energy Intensity ◽  
Economic Effect ◽  
Shandong Province ◽  
Driving Factors ◽  
Carbon Density ◽  
Urbanization Effect ◽  
Intensity Effect ◽  
Land Urbanization

Against the backgrounds of emission reduction targets promised by China, it is crucial to explore drivers of CO2 emissions comprehensively for policy making. In this study, Shandong Province in China is taken as an example to investigate drivers in carbon density by using an extended Kaya identity and a logarithmic mean Divisia index model (LMDI) with two layers. It is concluded that there are eight positive driving factors of carbon density during 2000–2015, including traffic congestion, land urbanization, etc., and seven negative driving factors comprising energy intensity, economic structure, etc. Among these factors, economic growth and energy intensity are the main positive and negative driving factor, respectively. The contribution rate of traffic congestion and land urbanization is gradually increasing. Meanwhile, 15 driving factors are divided into five categories. Economic effect and urbanization effect are the primary positive drivers. Contrarily, energy intensity effect, structural effect, and scale effect contribute negative effects to the changes in carbon density. In the four stages, the contribution of urbanization to carbon density is inverted U. Overall, the results and suggestions can give support to decision maker to draw up relevant government policy.

scholarly journals A Decomposition Analysis of the Korean Manufacturing Sector: Monetary vs. Physical Outputs

2021 ◽  
Vol 13 (11) ◽  
pp. 6192
Author(s):  
Junghwan Lee ◽  
Jinsoo Kim
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Driving Forces ◽  
Manufacturing Sector ◽  
Decomposition Analysis ◽  
Primary Energy ◽  
Intensity Effect ◽  
Activity Effect ◽  
Index Decomposition ◽  
Output Indicator

This study analyzes the changes in energy consumption of the Korean manufacturing sector using the index decomposition analysis (IDA) method. To capture the production effect based on actual physical activities, we applied the activity revaluation (AR) approach in the analysis. We also developed energy consumption data in terms of primary energy supply to consider conversion loss in the energy sector to avoid any distortions in the intensity effect. The analysis covers every manufacturing subsector in Korea over the period between 2006 and 2018. Combining two distinctive approaches from the previous literature, the AR approach and primary energy-based analysis gives us helpful findings for a climate policy. First, the overall activity effect estimated from the physical output indicator is lower than that from the monetary output indicator. The monetary indicator shows that the share of energy-intensive industries decreases, whereas the physical indicator shows the opposite. Second, in terms of energy efficiency, the intensity effect is estimated as an increasing factor of energy use, whereas inversed results are shown when we use the monetary indicator. Lastly, unlike the previous studies, the AR approach results indicate that Korean manufacturing sectors have been shifting toward an energy-intensive, so it is hard to anticipate positive intensity effects, which means decreasing energy consumption factor, for a while. These results support why analyzing the driving forces of energy consumption through the AR approach and primary energy base is highly recommended.

scholarly journals Key Factors Influencing the Achievement of Climate Neutrality Targets in the Manufacturing Industry: LMDI Decomposition Analysis

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8006
Author(s):  
Kristiāna Dolge ◽  
Dagnija Blumberga
Keyword(s):  
Energy Efficiency ◽  
Co2 Emissions ◽  
Manufacturing Industry ◽  
Decomposition Analysis ◽  
Clean Energy ◽  
Industrial Activity ◽  
Intensity Effect ◽  
Wood Processing ◽  
Activity Effect ◽  
The Impact

The manufacturing industry is often caught in the sustainability dilemma between economic growth targets and climate action plans. In this study, a Log-Mean Divisia Index (LMDI) decomposition analysis is applied to investigate how the amount of industrial energy-related CO2 emissions in Latvia has changed in the period from 1995 to 2019. The change in aggregate energy-related CO2 emissions in manufacturing industries is measured by five different factors: the industrial activity effect, structural change effect, energy intensity effect, fuel mix effect, and emission intensity effect. The decomposition analysis results showed that while there has been significant improvement in energy efficiency and decarbonization measures in industry, in recent years, the impact of the improvements has been largely offset by increased industrial activity in energy-intensive sectors such as wood processing and non-metallic mineral production. The results show that energy efficiency measures in industry contribute most to reducing carbon emissions. In the future, additional policies are needed to accelerate the deployment of clean energy and energy efficiency technologies.

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.

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.

Driving Forces of Water Intensity in China’s Industrial Sector: A Global Meta-Frontier Production–Theoretical Decomposition Analysis

2021 ◽  
pp. 2150010
Author(s):  
Tao Ding ◽  
Jiangyuan Li ◽  
Xing Shi ◽  
Huaqing Wu
Keyword(s):  
Driving Forces ◽  
National Level ◽  
Decomposition Analysis ◽  
Cost Effective ◽  
Industrial Sector ◽  
Sustainable Growth ◽  
Industrial Water ◽  
Water Usage ◽  
Decomposition Approach ◽  
Water Intensity

The shortage of water resources has prohibited the sustainable growth of China. Identifying the driving forces of water intensity is critical to initiating cost-effective policies and regulations to reduce water consumption across China. We develop a global meta-frontier production decomposition approach, which could simultaneously address the spatial and temporal heterogeneities, to decompose the water intensity of the industrial sector in China at various levels from 2011 to 2015. Results show that the industrial water intensity in all provinces except Shanxi has been declining over the sample period, with little potential for a further reduction. Second, at the national level, the potential water usage factor and the temporal catch-up effect of water usage technology are two significant contributors in reducing the industrial water intensity. Third, we find that some factors have mixed results at the regional and provincial levels, calling for customized policies in these aspects. Our approach provides a more precise decomposition and reveals more details in China’s variations of industrial water intensity, which has manifold implications for regional water management.

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