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 Analysing South Africa’s automotive energy consumption : application of index decomposition analysis

2021 ◽  
Author(s):  
◽  
Rofhiwa Tevin Machivha
Keyword(s):  
Energy Consumption ◽  
Decomposition Analysis ◽  
Structural Effect ◽  
Intensity Effect ◽  
Sectoral Shifts ◽  
Activity Effect ◽  
Index Decomposition Analysis ◽  
Index Decomposition ◽  
Industrial Energy ◽  
The Impact

This research focuses on applying the Index Decomposition Analysis (IDA) to South Africa’s automotive industry to decompose energy consumption and further make use of regression analysis to understand how it relates to the economy. South Africa has been going through an energy crisis, which has resulted in ongoing load shedding as a way to manage this crisis. Looking at South Africa’s energy generation, it can be noted that the entire country depends on Eskom as the main supplier and of electricity, but it is unable to keep pace with the demand. The results of the research show that there exists a nexus across all segments between energy consumption and GDP; furthermore, the decomposition results show that energy consumption in some years experienced a reduction. However, it can be seen that an increase in energy consumption year on year is predominant; this then suggests that the reductions experienced were the result of a special event; hence, it can be deduced that overall energy consumption has increased slightly. The increase is as a result of the activity effect which contributed the most towards this whilst the structural effect yielded a negligible contribution. Lastly, the intensity effect contributed to the reduction in energy consumption as a result of sectoral shifts; this reduction contributed towards keeping the overall increase in energy consumption low. This study aimed to outline the differences in energy consumed during the production of different vehicle classes, citing various factors responsible for the changes in energy consumption during vehicle production, raising awareness with manufacturers on the impact industrial energy consumption has on the national energy grid and on advising medium to large manufacturers to become suppliers.

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 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 The Impact of Energy Consumption and Economic Growth on Carbon Dioxide Emissions

2020 ◽  
Vol 12 (19) ◽  
pp. 7965
Author(s):  
Oluyomi A. Osobajo ◽  
Afolabi Otitoju ◽  
Martha Ajibola Otitoju ◽  
Adekunle Oke
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Granger Causality ◽  
Co2 Emissions ◽  
Carbon Dioxide Emissions ◽  
Fixed Effects ◽  
Positive Impact ◽  
Clean Energy ◽  
Cointegration Tests ◽  
The Impact

This study explored the effect of energy consumption and economic growth on CO2 emissions. The relationship between energy consumption, economic growth and CO2 emissions was assessed using regression analysis (the pooled OLS regression and fixed effects methods), Granger causality and panel cointegration tests. Data from 70 countries between 1994–2013 were analysed. The result of the Granger causality tests revealed that the study variables (population, capital stock and economic growth) have a bi-directional causal relationship with CO2 emissions, while energy consumption has a uni-directional relationship. Likewise, the outcome of the cointegration tests established that a long-run relationship exists among the study variables (energy consumption and economic growth) with CO2 emissions. However, the pooled OLS and fixed methods both showed that energy consumption and economic growth have a significant positive impact on CO2 emissions. Hence, this study supports the need for a global transition to a low carbon economy primarily through climate finance, which refers to local, national, or transnational financing, that may be drawn from public, private and alternative sources of financing. This will help foster large-scale investments in clean energy, that are required to significantly reduce CO2 emissions.

scholarly journals On the Energy Efficiency in the Next Generation of Smart Buildings—Supporting Technologies and Techniques

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4399 ◽  
Author(s):  
César Benavente-Peces
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Harvesting ◽  
Smart Grids ◽  
Smart Cities ◽  
Clean Energy ◽  
Communication Technologies ◽  
Next Generation ◽  
Smart Buildings ◽  
The Impact

Energy efficiency is one of the most relevant issues that the scientific community, and society in general, must face in the next years. Furthermore, higher energy efficiencies will contribute to worldwide sustainability. Buildings are responsible for 40% of the overall consumed energy. Smart Grids and Smart Buildings are playing an essential role in the definition of the next generation of sustainable Smart Cities. The main goal is reducing the impact of energy consumption on the environment as much as possible. This paper focuses on information communication technologies (ICTs) and techniques, their key characteristics and contribution to obtain higher energy efficiencies in smart buildings. Given that electrical energy is the most used, the investigation mainly centres on this energy. This paper also pays attention to green energies and energy harvesting due to their contribution to energy efficiency by providing additional clean energy. The main contribution of this investigation is pointing out the most relevant existing and emerging ICT technologies and techniques which can be used to optimize the energy efficiency of Smart Buildings. The research puts special attention on available, novel and emerging sensors, communication technologies and standards, intelligence techniques and algorithms, green energies and energy harvesting. All of them enable high-performance intelligent systems to optimize energy consumption and occupants’ comfort. Furthermore, it remarks on the most suitable technologies and techniques, their main features and their applications in Smart Buildings.

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 Decomposition Analysis and Trend Prediction of CO2 Emissions in China’s Transportation Industry

2020 ◽  
Vol 12 (7) ◽  
pp. 2596
Author(s):  
Ming Meng ◽  
Manyu Li
Keyword(s):  
Co2 Emissions ◽  
Carrying Capacity ◽  
Carbon Dioxide Emissions ◽  
Industrial Structure ◽  
Decomposition Analysis ◽  
Carbon Accounting ◽  
Transportation Industry ◽  
Trend Prediction ◽  
Intensity Effect ◽  
Per Capita

China’s transportation industry has become one of the major industries with rapid growth in CO2 emissions, which has a significant impact in controlling the increase of CO2 emissions. Therefore, it is extremely necessary to use a hybrid trend extrapolation model to project the future carbon dioxide emissions of China. On account of the Intergovernmental Panel on Climate Change (IPCC) inventory method of carbon accounting, this paper applied the Logarithmic Mean Divisia Index (LMDI) model to study the factors affected by CO2 emissions. The affected factors are further subdivided into the scale of employees, per capita carrying capacity, transport intensity, average transportation distance, energy input and output structure, energy intensity and industrial structure. The results are as follows: (1) Per capita carrying capacity is the most important factor to promote the growth of CO2 emissions, while industrial structure is the main reason to inhibit the growth of CO2 emissions; (2) the expansion of the number of employees has played a positive role in the growth of CO2 emissions and the organization and technology management of the transportation industry should be strengthened; (3) comprehensive transportation development strategy can make the transportation intensity effect effectively reduce CO2 emissions; (4) the CO2 emissions of the transportation industry will continue to increase during 2018–2025, with a cumulative value of about 336.11 million tons. The purpose of this study is to provide scientific guidance for the government’s emission reduction measures in the transportation industry. In addition, there are still some deficiencies in the study of its influencing factors in this paper and further improvements are necessary for the subsequent research expansion.

CO2 emissions of Turkish manufacturing industry: A decomposition analysis

2011 ◽  
Vol 88 (6) ◽  
pp. 2273-2278 ◽  
Author(s):  
Elif Akbostancı ◽  
Gül İpek Tunç ◽  
Serap Türüt-Aşık
Keyword(s):  
Co2 Emissions ◽  
Manufacturing Industry ◽  
Decomposition Analysis

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.

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