An empirical spatiotemporal decomposition analysis of carbon intensity in China's industrial sector

2018 ◽  
Vol 195 ◽  
pp. 133-144 ◽  
Author(s):  
Juan Wang ◽  
Mingming Hu ◽  
João F.D. Rodrigues
Keyword(s):  
Decomposition Analysis ◽  
Industrial Sector ◽  
Carbon Intensity

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.

scholarly journals Which Sectors Really Matter for a Resilient Chinese Economy? A Structural Decomposition Analysis

2019 ◽  
Vol 11 (22) ◽  
pp. 6333 ◽  
Author(s):  
Xin Mai ◽  
Roger C. K. Chan ◽  
Chaoqun Zhan
Keyword(s):  
Real Estate ◽  
National Economy ◽  
Financial Services ◽  
Decomposition Analysis ◽  
Industrial Sector ◽  
Chinese Economy ◽  
Infrastructure Development ◽  
Structural Decomposition Analysis ◽  
Economic Sectors ◽  
Economic Resilience

This study explores the structural effect of economic resilience with a case of China by examining the extent to which the major economic sectors contribute to the relative resilience of China’s overall economy. By applying a time series analysis, we use the Hodrick–Prescott filter to delineate China’s national economy on a quarterly basis and reveal different performances in responding to two recent economic crises in 1997 and 2008. Using quarterly data pertaining to eight economic sectors (including agriculture, industry, and major service sectors) and the national GDP from 1993Q1 to 2017Q2, we examine their effects on China’s economic resilience by simulating the responses of the national economy to a unit shock from each sector. Results show that the construction, real estate, and financial services have the greatest potential to “disturb” the national economy whereas the industrial sector has the greatest potential to “stabilize” it. The findings correspond with the understanding that extensive infrastructure development and the real estate boom have driven China’s rapid urban development and created economic prosperity, whereas the sectoral decomposition of economic resilience compels a critical reflection on the risks of this growth model.

scholarly journals Spatial Differences in Carbon Intensity in Polish Households

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3108 ◽  
Author(s):  
Edyta Sidorczuk-Pietraszko
Keyword(s):  
Regional Differences ◽  
Fossil Fuels ◽  
Driving Forces ◽  
Ghg Emissions ◽  
Decomposition Analysis ◽  
Policy Instruments ◽  
Carbon Intensity ◽  
Greenhouse Gasses ◽  
Key Factor ◽  
Per Capita

Knowledge about the driving forces behind greenhouse gasses (GHG) emissions is crucial for informed and evidence-based policy towards mitigation of GHG emission and changing production and consumption patterns. Both national and regional-level authorities are capable of addressing their actions more effectively if they have information about the spatial distribution of phenomena related to the policies they conduct. In this context, the main aim of this paper is to explain the regional differences in carbon intensity in Poland. The differences in carbon intensity between regions and the national average were analysed using index decomposition analysis (IDA). Aggregate carbon intensity for regional economies as well as the carbon intensity of households was investigated. For both levels of analysis: total emissions and emission from households economic development is the key factor responsible for the inter-regional differences in carbon emission per capita. In the case of total emissions, the second important factor influencing these differences is the structure of the national power system, i.e., its concentration and the production of energy from fossil fuels. For households, disposable income per capita is a key factor of differences in CO2 emission per capita between regions. Higher households’ incomes contribute to higher emission per capita, mostly due to the shift in consumption towards more energy- and material-intensive goods. The contribution of energy emissivity is quite low and not as varied as in the case of income. This suggests that policy instruments targeted at the consumption of fuels can be rather uniform across regions, while more developed regions should also be subject to measures supporting less energy-intensive consumption. On the other hand, policy in less developed regions should prevent them from following the path of per capita emissions growth.

scholarly journals Industrial Electrification and Efficiency: Decomposition Evidence from the Korean Industrial Sector

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 5120
Author(s):  
Jiyong Park ◽  
Taeyoung Jin ◽  
Sungin Lee ◽  
Jongroul Woo
Keyword(s):  
Decomposition Analysis ◽  
Electricity Consumption ◽  
Industrial Sector ◽  
Intensity Effect ◽  
Production Effect ◽  
Industrial Sectors ◽  
Index Approach ◽  
Efficiency Decomposition ◽  
Factor Decomposition ◽  
Efficiency Effects

For this study, we conducted a decomposition analysis of industrial electricity consumption based on the logarithmic mean Divisia index approach. An empirical dataset consisting of 11 industrial sectors in Korea from 2000 to 2018 was used. The three-factor decomposition equation was extended to include four factors by decomposing the energy intensity effect into electrification and electricity consumption efficiency effects. The empirical results are summarized as follows: The increase in electricity consumption in the Korean industrial sector from 2000 to 2018 is mostly caused by the production effect. While the structure effect decreases electricity consumption, the intensity effect increases it. The key findings indicate that the hidden electrification effect can be confusing to researchers with regard to the intensity effect. The empirical evidence suggests that the intensity effect has a positive effect on electricity consumption induced by the electrification effect, although the efficiency effect continuously decreased electricity consumption. The decomposition results of some sectors show that electrification, rather than the production effect, contributed the most to the increase in electricity consumption. This implies that while replacing fuel with electricity has been successfully achieved in several sectors, there are still challenges regarding increasing energy efficiency and expanding clean electricity generation.

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 Study on Global Industrialization and Industry Emission to Achieve the 2 °C Goal Based on MESSAGE Model and LMDI Approach

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 825 ◽  
Author(s):  
Shining Zhang ◽  
Fang Yang ◽  
Changyi Liu ◽  
Xing Chen ◽  
Xin Tan ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Co2 Emissions ◽  
Carbon Emissions ◽  
Energy Supply ◽  
Industrial Sector ◽  
Carbon Intensity ◽  
Global Energy ◽  
Energy Supply System ◽  
Industrial Carbon ◽  
Global Energy Supply

The industrial sector dominates the global energy consumption and carbon emissions in end use sectors, and it faces challenges in emission reductions to reach the Paris Agreement goals. This paper analyzes and quantifies the relationship between industrialization, energy systems, and carbon emissions. Firstly, it forecasts the global and regional industrialization trends under Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway2 (SSP2) scenarios. Then, it projects the global and regional energy consumption that aligns with the industrialization trend, and optimizes the global energy supply system using the Model for Energy Supply Strategy Alternatives and their General Environmental Impact (MESSAGE) model for the industrial sector. Moreover, it develops an expanded Kaya identity to comprehensively investigate the drivers of industrial carbon emissions. In addition, it employs a Logarithmic Mean Divisia Index (LMDI) approach to track the historical contributions of various drivers of carbon emissions, as well as predictions into the future. This paper finds that economic development and population growth are the two largest drivers for historical industrial CO2 emissions, and that carbon intensity and industry energy intensity are the top two drivers for the decrease of future industrial CO2 emissions. Finally, it proposes three modes, i.e., clean supply, electrification, and energy efficiency for industrial emission reduction.

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