A decomposition analysis of CO2 emissions from energy use: Turkish case

Environmental problems, especially “climate change” due to significant increase in anthropogenic greenhouse gases, have been on the agenda since 1980s. Among the greenhouse gases, carbon dioxide (CO₂) is the most important one and is responsible for more than 60% of the greenhouse effect. The objective of this study is to identify the factors that contribute to changes in CO₂ emissions for the Turkish economy by utilizing Log Mean Divisia Index (LMDI) method developed by Ang (2005) [Ang, B.W., 2005. The LMDI approach to decomposition analysis: a practical guide. Energy Policy 33, 867–871]. Turkish economy is divided into three aggregated sectors, namely agriculture, industry and services, and energy sources used by these sectors are aggregated into four groups: solid fuels, petroleum, natural gas and electricity. This study covers the period 1970–2006, which enables us to investigate the effects of different macroeconomic policies on carbon dioxide emissions through changes in shares of industries and use of different energy sources. Our analysis shows that the main component that determines the changes in CO₂ emissions of the Turkish economy is the economic activity. Even though important changes in the structure of the economy during 1970–2006 period are observed, structure effect is not a significant factor in changes in CO₂ emissions, however intensity effect is.     

A sectoral decomposition analysis of Turkish CO2 emissions over 1990–2007

At a time of increased international concern and negotiations for greenhouse gas emission reduction, country studies on the underlying effects of greenhouse gas emission growth gain importance. The case of Turkey is particularly interesting due to rapidly growing emissions, accompanied by a political will and actions to reduce the quick growth. The refined Laspeyres method is used in this study to identify factors that accelerate or reduce the increase in Turkish CO₂ emissions. A year-by-year decomposition over 1990-2007 is carried out at sectoral level based on disaggregated data that is consistent over time and consistent with international standards. Various interesting results on the underlying effects of sectoral emission growth are found. Valuable insights are gained into CO₂ impacts of sectoral policies including energy and emission intensities, fuel switching and activity changes. The results yield important hints for the planning of energy and climate policy.     

Using LMDI method to analyze the change of China's industrial CO2 emissions from final fuel use: An empirical analysis

Based on time series decomposition of the Log-Mean Divisia Index (LMDI), this paper analyzes the change of industrial carbon emissions from 36 industrial sectors in China over the period 1998–2005. The changes of industrial CO₂ emission are decomposed into carbon emissions coefficients of heat and electricity, energy intensity, industrial structural shift, industrial activity and final fuel shift. Our results clearly show that raw chemical materials and chemical products, nonmetal mineral products and smelting and pressing of ferrous metals account for 59.31% of total increased industrial CO₂ emissions. The overwhelming contributors to the change of China's industrial sectors’ carbon emissions in the period 1998–2005 were the industrial activity and energy intensity; the impact of emission coefficients of heat and electricity, fuel shift and structural shift was relatively small. Over the year 1998–2002, the energy intensity change in some energy-intensive sectors decreased industrial emissions, but increased emissions over the period 2002–2005. The impact of structural shift on emissions have varied considerably over the years without showing any clear trend, and the final fuel shift increased industrial emissions because of the increase of electricity share and higher emissions coefficient. Therefore, raw chemical materials and chemical products, nonmetal mineral products and smelting and pressing of ferrous metals should be among the top priorities for enhancing energy efficiency and driving their energy intensity close to the international advanced level. To some degree, we should reduce the products waste of these sectors, mitigate the growth of demand for their products through avoiding the excessive investment highly related to these sectors, increasing imports or decreasing the export in order to avoid expanding their share in total industrial value added. However, all these should integrate economic growth to harmonize industrial development and CO₂ emission reduction.     

CO2 emissions vs. CO2 responsibility: An input–output approach for the Turkish economy

Recently, global warming (greenhouse effect) and its effects have become one of the hottest topics in the world agenda. There have been several international attempts to reduce the negative effects of global warming. The Kyoto Protocol can be cited as the most important agreement which tries to limit the countries’ emissions within a time horizon. For this reason, it becomes important to calculate the greenhouse gas emissions of countries. The aim of this study is to estimate the amount of CO₂—the most important greenhouse gas—emissions, for the Turkish economy. An extended input–output model is estimated by using 1996 data in order to identify the sources of CO₂ emissions and to discuss the share of sectors in total emission. Besides, ‘CO₂ responsibility’, which takes into account the CO₂ content of imports, is estimated for the Turkish economy. The sectoral CO₂ emissions and CO₂ responsibilities are compared and these two notions are linked to foreign trade volume. One of the main conclusions is that the manufacturing industry has the first place in both of the rankings for CO₂ emissions and CO₂ responsibilities, while agriculture and husbandry has the last place.     

Energy efficiency and CO2 emissions in Swedish manufacturing industries

This paper analyses the trends in energy consumption and CO₂ emissions as a result of energy efficiency improvements in Swedish manufacturing industries between 1993 and 2008. Using data at the two-digit level, the performance of this sector is studied in terms of CO₂ emissions, energy consumption, energy efficiency measured as energy intensity, value of production, fuel sources, energy prices and energy taxes. It was found that energy consumption, energy intensity and CO₂ emission intensity, measured as production values, have decreased significantly in the Swedish manufacturing industries during the period studied. The results of the decomposition analysis show that output growth has not required higher energy consumption, leading to a reduction in both energy and CO₂ emission intensities. The role of structural changes has been minor, and the trends of energy efficiency and CO₂ emissions have been similar during the sample period. A stochastic frontier model was used to determine possible factors that may have influenced these trends. The results demonstrate that high energy prices, energy taxes, investments and electricity consumption have influenced the reduction of energy and CO₂ emission intensities, indicating that Sweden has applied an adequate and effective energy policy. The study confirms that it is possible to achieve economic growth and sustainable development whilst also reducing the pressure on resources and energy consumption and promoting the shift towards a low-carbon economy.     

Structural decomposition analysis of energy-related CO<Subscript>2</Subscript> emissions in China from 1997 to 2010

The energy-related CO₂ emissions in China have increased dramatically from 3384 to 8333?×?10⁶ t during the last decade. To interpret these drastic changes, we undertake a structural decomposition analysis to decompose the changes in CO₂ emissions from 1997 to 2010 into the following six driving forces: emission coefficient, energy intensity, Leontief, sectoral structure, demand allocation (the shares of consumption, investments, and exports in final demand), and final demand effects. The results show that declines in energy intensity had a decrease impact on CO₂ emissions during the studied period. Changes in the relative importance of intermediate production in total output (the Leontief effect) contributed to decrease CO₂ emissions in the 2000–2002 period and to increase emissions in the other periods. The most important driver behind the steady increase in CO₂ emissions is the large increase in final demand. A further analysis at the sectoral level revealed differences and fluctuations between sectors. Energy intensity fell most strongly in the electric power sector and the coking, gas, and petroleum production sector (two energy-intensive sectors). The shift toward exports and investment increased CO₂ emissions (demand allocation effect). Part of the increases in CO₂ emissions thus stem from production activities for consumption activities elsewhere.     

Comprehensive evaluation of industrial CO2 emission (1989–2004) in Taiwan by input–output structural decomposition

Taiwan currently emits approximately 1% of the world's CO₂—ranking it 22nd among nations. Herein, we use the input–output (I–O) structural decomposition method to examine the changes in CO₂ emission over a 15-year period. By decomposing the CO₂ emission changes into nine factors for the periods of 1989–1994, 1994–1999, and 1999–2004, we have identified the key factors causing the emission changes, as well as the most important trends regarding the industrial development process in Taiwan. The 5-year increment with the largest increase of CO₂ emission was that of 1999–2004, due to the rapid increase of electricity consumption. From the decomposition, the industrial energy coefficient and the CO₂ emission factors were identified as the most important parameters for the determination of the highway, petrochemical materials, iron and steel, the commercial sector, and electric machinery as the major sources of increased CO₂ emission during the past 15 years. From 1989 to 2004, the level of exports and the level of domestic final demand were the largest contributors to the increase in the total increment of CO₂ change. During 1989–2004, the industrial energy coefficient and CO₂ emission factors, being minimally significant during 1989–1994, became extremely important, joining the domestic final demand and the level of exports factors as the major causes of the increase increment of CO₂. This indicates a heavy reliance upon high-energy (and CO₂) intensity for Taiwanese industries; therefore, continuous efforts to improve energy intensity and fuel mix toward lower carbon are important for CO₂ reduction, especially for the electricity and power generation sectors. Relevant strategies for reducing carbon dioxide emissions from major industries are also highlighted.     

CO2 emissions from electricity generation in seven Asia-Pacific and North American countries: A decomposition analysis

The Logarithmic Mean Divisia Index (LMDI) method of complete decomposition is used to examine the role of three factors (electricity production, electricity generation structure and energy intensity of electricity generation) affecting the evolution of CO₂ emissions from electricity generation in seven countries. These seven countries together generated 58% of global electricity and they are responsible for more than two-thirds of global CO₂ emissions from electricity generation in 2005. The analysis shows production effect as the major factor responsible for rise in CO₂ emissions during the period 1990–2005. The generation structure effect also contributed in CO₂ emissions increase, although at a slower rate. In contrary, the energy intensity effect is responsible for modest reduction in CO₂ emissions during this period. Over the 2005–2030 period, production effect remains the key factor responsible for increase in emissions and energy intensity effect is responsible for decrease in emissions. Unlike in the past, generation structure effect contributes significant decrease in emissions. However, the degree of influence of these factors affecting changes in CO₂ emissions vary from country to country. The analysis also shows that there is a potential of efficiency improvement of fossil-fuel-fired power plants and its associated co-benefits among these countries.     

Analysis on energy intensive industries under Taiwan's climate change policy

This study addresses the planning and implementation of energy, industry, and carbon economy policies concerning the development of the Taiwan's energy intensive industries from perspective of climate change. As a newly industrialized country, Taiwan attaches greater importance to the development of green energy and low-carbon industries, in cooperation with global pressure for carbon reduction due to climate changes, through energy and industrial conferences. Thus, in the past year the Taiwanese government constructed four laws concerning energy and carbon reduction in order to drive the green energy industry; furthermore, it plans to reduce current carbon emission benchmarks. Nevertheless, statistical analysis found that in the last decade, energy intensive industries have presented structural unbalance regarding energy consumption, CO₂ emissions, energy intensity, contributions to the GDP, and product value. Industries in the industrial sector have high energy consumption, high carbon emissions, and increase total domestic consumption and carbon emissions, which have disproportionate contributions to industrial added value; nevertheless, the government continues to approve investments for such energy intensive industries, and results in continuous increases in energy consumption and carbon emissions. This contradictory phenomenon indicates that newly industrialized countries rely on a manufacturing economic structure, which is difficult to adjust and violates the trends of a global low-carbon economy. Hence, the government must examine and adjust such unbalanced industrial structures, where such adjustments are executed in a fair and just manner, and encourage the development of high value-added measures for low-carbon manufacturing and service sectors to become equal with competitors in a global economy.     

Decomposition analysis and mitigation strategies of CO2 emissions from energy consumption in South Korea

Energy-related CO₂ emissions in South Korea have increased substantially, outpacing those of Organisation for Economic Co-operation and Development (OECD) countries since 1990. To mitigate CO₂ emissions in South Korea, we need to understand the main contributing factors to rising CO₂ levels as part of the effort toward developing targeted policies. This paper aims to analyze the specific trends and influencing factors that have caused changes in emissions patterns in South Korea over a 15-year period. To this end, we employed the Log Mean Divisia index method with five energy consumption sectors and seven sub-sectors in terms of fuel mix (FM), energy intensity (EI), structural change (SC) and economic growth (EG). The results showed that EG was a dominant explanation for the increase in CO₂ emissions in all of the sectors. The results also demonstrated that FM causes CO₂ reduction across the array of sectors with the exception of the energy supply sector. CO₂ reduction as a function of SC was also observed in manufacturing, services and residential sectors. Furthermore, EI was an important driver of CO₂ reduction in most sectors except for several manufacturing sub-sectors. Based on these findings, it appears that South Korea should implement climate change policies that consider the specific influential factors associated with increasing CO₂ emissions in each sector.     

Economic growth,energy consumption and CO2 emissions in India: a disaggregated causal analysis

This study examines the long-run and short-run causal relationships among energy consumption, real gross domestic product (GDP) and CO₂ emissions using aggregate and disaggregate (sectoral) energy consumption measures utilising annual data from 1971 to 2011. The autoregressive distributed lag bounds test reveals that there is a long-run relationship among the variables concerned at both aggregate and disaggregate levels. The Toda–Yamamoto causality tests, however, reveal that the long-run as well short-run causal relationship among the variables is not uniform across sectors. The weight of evidences of the study indicates that there is short-run causality from electricity consumption to economic growth, and to CO₂ emissions. The results suggest that India should take appropriate cautious steps to sustain high growth rate and at the same time to control emissions of CO₂. Further, energy and environmental policies should acknowledge the sectoral differences in the relationship between energy consumption and real gross domestic product.     

Grey relation performance correlations among economics,energy use and carbon dioxide emission in Taiwan

This study explores the inter-relationships among economy, energy and CO₂ emissions of 37 industrial sectors in Taiwan in order to provide insight regarding sustainable development policy making. Grey relation analysis was used to analyse the productivity, aggregate energy consumption, and the use of fuel mix (electricity, coal, oil and gas) in relation to CO₂ emission changes. An innovative evaluative index system was devised to explore grey relation grades among economics, energy and environmental quality. Results indicate that a rapid increase in electricity generation during the past 10 years is the main reason for CO₂ emission increase in Taiwan. The largest CO₂ emitting sectors include iron and steel, transportation, petrochemical materials, commerce and other services. Therefore, it is important to reduce the energy intensity of these sectors by energy conservation, efficiency improvement and adjustment of industrial structure towards high value-added products and services. Economic growth for all industries has a more significant influence, than does total energy consumption, on CO₂ emission increase in Taiwan. It is also important to decouple the energy consumption and production to reduce the impacts of CO₂ on economic growth. Furthermore, most of the sectors examined had increased CO₂ emissions, except for machinery and road transportation. For high energy intensive and CO₂ intensive industries, governmental policies for CO₂ mitigation should be directed towards low carbon fuels as well as towards enhancement of the demand side management mechanism, without loss of the nation's competitiveness.     

Transport sector CO2 emissions growth in Asia: Underlying factors and policy options

This study analyze the potential factors influencing the growth of transport sector carbon dioxide (CO₂) emissions in selected Asian countries during the 1980–2005 period by decomposing annual emissions growth into components representing changes in fuel mix, modal shift, per capita gross domestic product (GDP) and population, as well as changes in emission coefficients and transportation energy intensity. We find that changes in per capita GDP, population growth and transportation energy intensity are the main factors driving transport sector CO₂ emission growth in the countries considered. While growth in per capita income and population are responsible for the increasing trend of transport sector CO₂ emissions in China, India, Indonesia, Republic of Korea, Malaysia, Pakistan, Sri Lanka and Thailand; the decline of transportation energy intensity is driving CO₂ emissions down in Mongolia. Per capita GDP, population and transportation energy intensity effects are all found responsible for transport sector CO₂ emissions growth in Bangladesh, the Philippines and Vietnam. The study also reviews existing government policies to limit CO₂ emissions growth, such as fiscal instruments, fuel economy standards and policies to encourage switching to less emission intensive fuels and transportation modes.     

Driving forces of residential CO2 emissions in urban and rural China: An index decomposition analysis

There exist many differences between urban and rural China among which residential CO₂ emissions arising from energy consumption is a major one. In this paper, we estimate and compare the energy related CO₂ emissions from urban and rural residential energy consumption from 1991 to 2004. The logarithmic mean Divisia index decomposition analysis is then applied to investigate the factors that may affect the changes of the CO₂ emissions. It is found that energy intensity and the income effects, respectively, contributed most to the decline and the increase of residential CO₂ emissions for both urban and rural China. In urban China, the population effect was found to contribute to the increase of residential CO₂ emissions with a rising tendency. However, in rural China, the population effect for residential CO₂ emissions kept decreasing since 1998.     

Energy consumption and CO2 emissions of the European glass industry

An in-depth analysis of the energy consumption and CO₂ emissions of the European glass industry is presented. The analysis is based on data of the EU ETS for the period 2005–2007 (Phase I). The scope of this study comprises the European glass industry as a whole and its seven subsectors. The analysis is based on an assignment of the glass installations (ca. 450) within the EU ETS to the corresponding subsectors and an adequate matching of the respective production volumes. A result is the assessment of the overall final energy consumption (fuel, electricity) as well as the overall CO₂ emissions (process, combustion and indirect emissions) of the glass industry and its subsectors in the EU25/27. Moreover, figures on fuel mix as well as fuel intensity and CO₂ emissions intensity (i.e. carbon intensity) are presented for each of the subsectors on aggregated levels and for selected EU Member States separately. The average intensity of fuel consumption and direct CO₂ emissions of the EU25 glass industry decreased from 2005 to 2007 by about 4% and amounted in 2007 to 7.8 GJ and 0.57 _tCO₂${\mathrm{t}}_{{\text{CO}}_{\mathrm{2}}}$ per tonne of saleable product, respectively. The economic energy intensity was evaluated with 0.46 toe/1000€ (EU27).     

Industrial CO2 emissions from energy use in Korea: A structural decomposition analysis

This paper attempts to quantify energy consumption and CO₂ emissions in the industrial sectors of Korea. The sources of the changes in CO₂ emissions for the years 1990–2003 are investigated, in terms of a total of eight factors, through input–output structural decomposition analysis: changes in emission coefficient (caused by shifts in energy intensity and carbon intensity); changes in economic growth; and structural changes (in terms of shifts in domestic final demand, exports, imports of final and intermediate goods, and production technology). The results show that the rate of growth of industrial CO₂ emissions has drastically decreased since the 1998 financial crisis in Korea. The effect on emission reductions due to changes in energy intensity and domestic final demand surged in the second period (1995–2000), while the impact of exports steeply rose in the third period (2000–2003). Of all the individual factors, economic growth accounted for the largest increase in CO₂ emissions. The results of this analysis can be used to infer the potential for emission-reduction in Korea.     

CO2 emissions reduction of Chinese light manufacturing industries: A novel RAM-based global Malmquist–Luenberger productivity index

Climate change has become one of the most challenging issues facing the world. Chinese government has realized the importance of energy conservation and prevention of the climate changes for sustainable development of China's economy and set targets for CO₂ emissions reduction in China. In China industry contributes 84.2% of the total CO₂ emissions, especially manufacturing industries. Data envelopment analysis (DEA) and Malmquist productivity (MP) index are the widely used mathematical techniques to address the relative efficiency and productivity of a group of homogenous decision making units, e.g. industries or countries. However, in many real applications, especially those related to energy efficiency, there are often undesirable outputs, e.g. the pollutions, waste and CO₂ emissions, which are produced inevitably with desirable outputs in the production. This paper introduces a novel Malmquist–Luenberger productivity (MLP) index based on directional distance function (DDF) to address the issue of productivity evolution of DMUs in the presence of undesirable outputs. The new RAM (Range-adjusted measure)-based global MLP index has been applied to evaluate CO₂ emissions reduction in Chinese light manufacturing industries. Recommendations for policy makers have been discussed.     

Global overview of industrial energy intensity

Given the need to reduce the CO₂ emissions coming from the manufacturing sector, it is important, for planning purposes, to know which countries and which manufacturing sub-sectors have the greatest potential for reducing energy use. Using data from the International Atomic Energy Agency and the United Nations Industrial Development Organization, the authors estimate trends in global decoupling of energy use and manufacturing value added, compare energy-use intensity in six country groups and estimate the potential for reducing energy use and CO₂ emissions under two scenarios and compare selected sub-sector energy intensity and estimate the potential for reducing energy use CO₂ emissions. The comparison of energy intensities across country groups and among countries suggests that there still remains significant potential to reduce energy use and associated CO₂ emissions. The analysis of four sub-sectors in developing and transition economies also shows similar but varied potential for reducing energy use and associated CO₂ emissions.     

Identifying the driving forces of national and regional CO2 emissions in China: Based on temporal and spatial decomposition analysis models

This study explores the driving forces of the changes of national and regional CO₂ emissions using temporal decomposition analysis model, and investigates the driving forces of the differences of CO₂ emissions between China's 30 regions and the national average using spatial decomposition analysis model. The changes or the differences in national and regional CO₂ emissions during 2000–2014 are decomposed into nine underlying determinants. Temporal decomposition results show that economic scale effect is the dominant driving force leading to the increases in both national and regional CO₂ emissions, while energy intensity effect is the main contributor to the reduction of CO₂ emissions. Contribution of various variables to CO₂ emissions between eastern region and central region are roughly same. Spatial decomposition results demonstrate that the differences of CO₂ emissions among China's 30 regions are expanding increasingly. Economic scale effect is main driving force responsible for the difference in CO₂ emissions among regions, and energy intensity effect, energy structure effect and industrial structure effect are also important factors which result in the increasing differences in regional CO₂ emissions. In addition, resource-based and less developed regions have greater potential in the reduction of CO₂ emissions. Understanding CO₂ emissions and the driving forces of various regions is critical for developing regional mitigation strategies in China.     

Contributing to local policy making on GHG emission reduction through inventorying and attribution: A case study of Shenyang,China

Cities consumed 84% of commercial energy in China, which indicates cities should be the main areas for GHG emissions reduction. Our case study of Shenyang in this paper shows how a clear inventory analysis on GHG emissions at city level can help to identify the major industries and societal sectors for reduction efforts so as to facilitate low-carbon policy-making. The results showed total carbon emission in 2007 was 57 Mt CO₂ equivalents (CO₂e), of which 41 Mt CO₂e was in-boundary emissions and 16 Mt CO₂e was out-of-boundary emissions. The energy sector was dominant in the emission inventory, accounting for 93.1% of total emissions. Within energy sector, emissions from energy production industry, manufacturing and construction industry accounted for 88.4% of this sector. Our analysis showed that comparing with geographical boundary, setting system boundary based on single process standard could provide better information to decision makers for carbon emission reduction. After attributing electricity and heating consumption to final users, the resident and commercial sector became the largest emitter, accounting for 28.5% of total emissions. Spatial analysis of emissions showed that industrial districts such as Shenbei and Tiexi had the large potential to reduce their carbon emissions. Implications of results are finally discussed.