|
|
|
Sort Order |
|
|
|
Items / Page
|
|
|
|
|
|
|
| Srl | Item |
| 1 |
ID:
112904
|
|
|
|
|
| Publication |
2012.
|
| Summary/Abstract |
In 2008, the gross domestic product (GDP) of California industry was larger than GDP of industry in any other U.S. states. This study analyses the energy use of and output from seventeen industry subsectors in California and performs decomposition analysis to assess the influence of different factors on California industry energy use. The logarithmic mean Divisia index method is used for the decomposition analysis. The decomposition analysis results show that the observed reduction of energy use in California industry since 2000 is the result of two main factors: the intensity effect and the structural effect. The intensity effect has started pushing final energy use downward in 2000 and has since amplified. The second large effect is the structural effect. The significant decrease of the energy-intensive "Oil and Gas Extraction" subsector's share of total industry value added, from 15% in 1997 to 5% in 2008, and the increase of the non-energy intensive "Electric and electronic equipment manufacturing" sector's share of value added, from 7% in 1997 to 30% in 2008, both contributed to a decrease in the energy intensity in the industry sector.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2 |
ID:
094395
|
|
|
|
|
| Publication |
2010.
|
| Summary/Abstract |
The purpose of this paper is to analyse how oil export dependencies of Middle East and North African (MENA) oil producers have evolved over the past two decades and to identify the main driving factors from an energy policy perspective. The paper expresses the oil export dependency of each economy in terms of a multiplicative identity that captures effective export price, export to primary oil supply ratio, oil dependency and oil export intensity of the country. Using the data for 1980-2006, the evolution in these factors is investigated for seven MENA countries and the influence of the above factors is decomposed using the Laspeyres index. The analysis shows that energy price and increasing energy intensity in the MENA countries have influenced the overall oil export dependency. Reducing the energy intensity can improve oil export revenue share to GDP by 5-10% in most of the countries while Iran can gain significantly by increasing its export volume.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 3 |
ID:
117304
|
|
|
|
|
| Publication |
2013.
|
| Summary/Abstract |
A substantial amount of primary and secondary energy is consumed by the residential sector. Residential energy consumption includes energy required for construction activity and household consumption. Hence there is a need to quantify energy consumption, its significance and causes. Calculating energy intensity of goods and services is the first step towards quantifying the causes. This research is based on the 115 sector classification input-output tables for India, for 1993-94, 1998-99 and 130 sector classification input-output tables for 2003-04 and 2006-07. Energy intensity of sectors related to household consumption has been calculated to analyze the trend between 1993-94 and 2006-07. Indirect energy requirements of Indian households have been assessed in this study from calculations of total primary energy intensity along with private final consumption expenditure. Results indicate that energy consumption has increased for all categories except "medical care and hygiene". Percentage increase in indirect primary energy consumed by households is maximum for "house building" and "recreation" categories. Finally a complete decomposition analysis of indirect primary energy consumed by households has been carried out based on changing structural composition of the private final consumption expenditure, energy intensity patterns, per capita expenditures on energy and population.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 4 |
ID:
096734
|
|
|
|
|
| Publication |
2010.
|
| Summary/Abstract |
Electricity consumption in the industrial sector experienced a dramatic increase between 1998 and 2007, accounting for approximately 75% of China's total electricity consumption. This study analyzes the potential factors influencing the growth of electricity consumption in China's industrial sector over the past decade using a logarithmic mean Divisia index I decomposition method. Results show that activity effect and shift effect (caused by the change in the electricity's share of industrial energy use) are the major factors responsible for the rise in electricity consumption between 1998 and 2007. It is found that structural change also contributed to the increase in electricity consumption, it had only a small effect. In contrast, the technological effect is responsible for a decrease in electricity consumption during this period. The influences of technological effects and shift effects followed approximately an inverse-U-shaped and U-shaped curve, respectively. Furthermore, the results show that the main contributors to incremental electricity consumption among industrial subsectors were manufacturing of raw chemical material and products, manufacturing of non-metal mineral products, smelting and pressing of ferrous and non-ferrous metals, and production and supply of electric power and heat power. These sectors should take priority for industrial restructuring in order to implement policies for energy and electricity savings.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 5 |
ID:
097534
|
|
|
|
|
| Publication |
2010.
|
| Summary/Abstract |
Electricity consumption in the industrial sector experienced a dramatic increase between 1998 and 2007, accounting for approximately 75% of China's total electricity consumption. This study analyzes the potential factors influencing the growth of electricity consumption in China's industrial sector over the past decade using a logarithmic mean Divisia index I decomposition method. Results show that activity effect and shift effect (caused by the change in the electricity's share of industrial energy use) are the major factors responsible for the rise in electricity consumption between 1998 and 2007. It is found that structural change also contributed to the increase in electricity consumption, it had only a small effect. In contrast, the technological effect is responsible for a decrease in electricity consumption during this period. The influences of technological effects and shift effects followed approximately an inverse-U-shaped and U-shaped curve, respectively. Furthermore, the results show that the main contributors to incremental electricity consumption among industrial subsectors were manufacturing of raw chemical material and products, manufacturing of non-metal mineral products, smelting and pressing of ferrous and non-ferrous metals, and production and supply of electric power and heat power. These sectors should take priority for industrial restructuring in order to implement policies for energy and electricity savings.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 6 |
ID:
097589
|
|
|
|
|
| Publication |
2010.
|
| Summary/Abstract |
Electricity consumption in the industrial sector experienced a dramatic increase between 1998 and 2007, accounting for approximately 75% of China's total electricity consumption. This study analyzes the potential factors influencing the growth of electricity consumption in China's industrial sector over the past decade using a logarithmic mean Divisia index I decomposition method. Results show that activity effect and shift effect (caused by the change in the electricity's share of industrial energy use) are the major factors responsible for the rise in electricity consumption between 1998 and 2007. It is found that structural change also contributed to the increase in electricity consumption, it had only a small effect. In contrast, the technological effect is responsible for a decrease in electricity consumption during this period. The influences of technological effects and shift effects followed approximately an inverse-U-shaped and U-shaped curve, respectively. Furthermore, the results show that the main contributors to incremental electricity consumption among industrial subsectors were manufacturing of raw chemical material and products, manufacturing of non-metal mineral products, smelting and pressing of ferrous and non-ferrous metals, and production and supply of electric power and heat power. These sectors should take priority for industrial restructuring in order to implement policies for energy and electricity savings.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 7 |
ID:
126825
|
|
|
|
|
| Publication |
2014.
|
| Summary/Abstract |
It is now widely recognized that there is a strong relationship between energy consumption and economic growth. Most countries' energy demands declined during the economic depression of 2008-2009 when a worldwide economic crisis occurred. As an export-oriented economy, China suffered a serious exports decline in the course of the crisis. However, it was found that energy consumption continued to increase. Against such a background, this paper aims to assess and explain the factors causing the growth of energy consumption in China. First, we will explain the impact of domestic final use and international trade on energy consumption by using decomposition analysis. Second, embodied energy and its variation across sectors are quantified to identify the key sectors contributing to the growth. Lastly, the policy implications for long-term energy conservation are discussed. The results show that the decline in exports was one of the driving forces for energy consumption reduction in the crisis, but that the growth of domestic demand in manufacturing and construction, largely stimulated by economic stimulus plans, had the opposite effect on energy consumption. International trade contributed to decreasing energy consumption of China during and after the crisis because the structure of exports and imports changed in this period.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 8 |
ID:
088019
|
|
|
|
|
| Publication |
2009.
|
| Summary/Abstract |
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.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 9 |
ID:
093541
|
|
|
|
|
| Publication |
2010.
|
| Summary/Abstract |
Energy intensity in Spain has increased since 1990, while the opposite has happened in the EU15. Decomposition analysis of primary energy intensity ratios has been used to identify which are the key sectors driving the Spanish evolution and those responsible for most of the differences with the EU15 energy intensity levels. It is also a useful tool to quantify which countries and economic sectors have had most influence in the EU15 evolution. The analysis shows that the Spanish economic structure is driving the divergence in energy intensity ratios with the EU15, mainly due to strong transport growth, but also because of the increase of activities linked to the construction boom, and the convergence to EU levels of household energy demand. The results can be used to pinpoint successful EU strategies for energy efficiency that could be used to improve the Spanish metric.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 10 |
ID:
122742
|
|
|
|
|
| Publication |
2013.
|
| Summary/Abstract |
This paper presents an alternative decomposition method to explore the driving forces of change in carbon emissions by using distance functions estimated by data envelopment analysis. The proposed approach can isolate the effects of changes in GDP composition and energy supply composition on the change of carbon emissions. In addition, it is capable of identifying the effects of changes in different input ratios, which may be very important if there are substitution effects among different inputs. Moreover, the proposed model can measure the effects of changes in good and bad output technical efficiencies. Consequently, this decomposition technique allows a change of carbon emissions to be decomposed into contributions from ten factors, which provides more insights for policy makers. We apply this model to decompose carbon emissions in 25 OECD counties and China. For the sample countries as a whole, the empirical results indicate that the economic growth is the crucial driver to carbon emissions increase, while the changes in GDP composition and capital-energy ratio are two main drivers to carbon emissions reduction. In particular, we discuss in detail the driving forces of China's carbon emissions change in order to propose some valuable policy implications for China from an international perspective.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 11 |
ID:
092787
|
|
|
|
|
| Publication |
2009.
|
| Summary/Abstract |
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.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 12 |
ID:
089001
|
|
|
|
|
| Publication |
2009.
|
| Summary/Abstract |
The paper presents a decomposition analysis of the changes in carbon dioxide (CO2) emissions from passenger cars in Denmark and Greece, for the period 1990-2005. A time series analysis has been applied based on the logarithmic mean Divisia index I (LMDI I) methodology, which belongs to the wider family of index decomposition approaches. The particularity in road transport that justifies a profound analysis is its remarkably rapid growth during the last decades, followed by a respective increase in emissions. Denmark and Greece have been selected based on the challenging differences of specific socio-economic characteristics of these two small EU countries, as well as on the availability of detailed data used in the frame of the analysis. In both countries, passenger cars are responsible for half of the emissions from road transport as well as for their upward trend, which provokes the implementation of a decomposition analysis focusing exactly on this segment of road transport. The factors examined in the present decomposition analysis are related to vehicles ownership, fuel mix, annual mileage, engine capacity and technology of cars. The comparison of the results discloses the differences in the transportation profiles of the two countries and reveals how they affect the trend of CO2 emissions.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 13 |
ID:
175260
|
|
|
|
|
| Summary/Abstract |
Debt can influence the energy consumption of private sectors and public agencies by changing their fiscal budget constraints. From 1996 to 2016, China has had rapid debt growth and become the second-largest borrower in the world. Additionally, China has been the largest energy consumer since 2009. The impact of debt growth on its energy consumption, however, is not much addressed in the literature. Using an extended LMDI model, we investigate the impact of China’s debt on its energy consumption from 1996 to 2016 in a new way. The results show that (1) among the closed set of debt-related factors and other conventional variables studied, private debt per capita makes the strongest contribution to China’s energy consumption, and population has a moderate impact on the growth of energy consumption; (2) energy efficiency improvement, output efficiency of government debt, debt structure adjustment, and increased tertiary industry share are mitigating forces of energy consumption. These results provide a new, holistic perspective for the Chinese government to formulate synergistic policies of risk control and pollution control.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 14 |
ID:
111397
|
|
|
|
|
| Publication |
2012.
|
| Summary/Abstract |
To-date, decomposition analysis has been widely used at the macro-economic level and for in-depth analyses of the industry and transport sectors; however, its application in the residential sector has been rare. This paper uses the Log-Mean Divisia Index I (LMDI-I) methodology to decompose gas consumption trends in the gas-connected residential sector in Ireland from 1990 to 2008, which despite an increasing number of energy efficiency policies, experienced total final consumption growth of 470%. The analysis decomposes this change in gas consumption into a number of effects, examining the impact over time of market factors such as a growing customer base, varying mix of dwelling types, changing share of vacant dwellings, changing size of new dwellings, the impact of building regulations policy and other factors such as the weather. The analysis finds the most significant effects are changing customer numbers and changing intensity; the analysis also quantifies the impact of building regulations and compares it with other effects such as changing size of new dwellings. By comparing the historical impact on gas consumption of policy factors and non-policy factors, this paper highlights the challenge for policy-makers in achieving overall energy consumption reduction.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 15 |
ID:
125444
|
|
|
|
|
| Publication |
2013.
|
| Summary/Abstract |
In recent decades, Ireland has been an important example of a development pathway where rapid economic growth was accompanied by rising energy demand and increasing carbon emissions. Understanding the driving forces of carbon emissions is necessary for policy formulation and decomposition analysis is widely used for this purpose. This study uses an extended Kaya identity as the scheme and applies the log mean Divisia index (LMDI I) as the decomposition technique. Change in carbon emissions is decomposed from 1990 to 2010 and includes a measure of the effect of renewable energy penetration. Results illustrate that scale effects of affluence and population growth act to increase emissions and are countered primarily by energy intensity and fossil fuel substitution. Renewable energy penetration has a minor effect but has been increasing in recent years. Policy will need to significantly reduce intensity and increase renewables if applicable targets are to be reached. This requires not only a comprehensive suite of policies and measures but emphasis on the development path and 'non-technical' change for optimal outcomes.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 16 |
ID:
088274
|
|
|
|
|
| Publication |
2009.
|
| Summary/Abstract |
This paper analyzes the changes in the energy consumption of the service sector in France over the period 1995-2006, using the logarithmic mean Divisia index I (LMDI I) decomposition method. The analysis is carried out at various disaggregation levels to highlight the specifics of each sub-sector and end-use according to their respective determinants. The results show that in this period the economic growth of the service sector was the main factor that led to the increase in total energy consumption. Structure, productivity, substitution and intensity effects restricted this growth, but with limited effect. By analyzing each end-use, this paper enables a more precise understanding of the impact of these factors. The activity effect was the main determinant of the increase in energy consumption for all end-uses except for air conditioning, for which the equipment rate effect was the main factor. Structural changes in the service sector primarily impacted energy consumption for space heating and cooking. Improvements in productivity limited the growth of energy consumption for all end-uses except for cooking. Finally, energy efficiency improvements mainly affected space-heating energy use.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 17 |
ID:
169753
|
|
|
|
|
| Summary/Abstract |
Fuel economy standards are a key measure to increase the rate of efficiency improvements in passenger cars. The fuel consumption of vehicles can be improved in three ways: incremental technical efficiency improvements within powertrain technologies, market shifts to more efficient types of powertrains and by limiting increases in the size and performance of vehicles. This study quantifies the effect of each of these three drivers on the fuel consumption of British vehicles between 2001 and 2018 using driver-reported data on real-world fuel consumption. Analysis shows the introduction of EU fuel economy standards in 2008/09 had little effect on the rate of real technical efficiency improvements in British vehicles. Instead of adopting technical improvements at a higher rate or limiting the size and power of vehicles, these results suggest vehicle manufacturers met emissions standards by increasing the divergence between laboratory tests and real-world fuel consumption. This study adds to the growing literature calling for official test procedures to be representative of real-world driving.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 18 |
ID:
112308
|
|
|
|
|
| Publication |
2012.
|
| Summary/Abstract |
Ireland recorded significant growth in energy-related carbon emissions from 1990 to 2007 as the country underwent rapid economic development. Using the LMDI decomposition analysis method, this paper aims to identify and analyse the driving forces of CO2 emissions in eleven final energy consuming sectors. This multi-sectoral analysis is based on four economic sectors, the residential sector and gives a detailed representation of transport in keeping with UNFCCC recommendations. Scale, structure and intensity effects are explored and substantial heterogeneity in sectoral performance is observed. Scale growth in economic and transport activity was considerable. Some improvements in energy intensity were recorded in the economic sectors. In transport, increases in intensity contributed to a significant increase in emissions, while energy intensity decreased in the residential sector. The declining emissions coefficient of electricity was important in limiting emissions but renewable energy has been slow to penetrate the demand side. The results have relevance in considering development paths and can aid in identifying policy measures required to address the key driving forces of emissions in the sectors. The rapid increase in transport emissions in particular raises concerns of future lock-in to a higher emissions trajectory.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 19 |
ID:
103598
|
|
|
|
|
| Publication |
2011.
|
| Summary/Abstract |
This study presents fossil-fuel related CO2 emissions in Austria and Czechoslovakia (current Czech Republic and Slovakia) for 1830-2000. The drivers of CO2 emissions are discussed by investigating the variables of the standard Kaya identity for 1920-2000 and conducting a comparative Index Decomposition Analysis. Proxy data on industrial production and household consumption are analysed to understand the role of the economic structure. CO2 emissions increased in both countries in the long run. Czechoslovakia was a stronger emitter of CO2 throughout the time period, but per-capita emissions significantly differed only after World War I, when Czechoslovakia and Austria became independent. The difference in CO2 emissions increased until the mid-1980s (the period of communism in Czechoslovakia), explained by the energy intensity and the composition effects, and higher industrial production in Czechoslovakia. Counterbalancing factors were the income effect and household consumption. After the Velvet revolution in 1990, Czechoslovak CO2 emissions decreased, and the energy composition effect (and industrial production) lost importance. Despite their different political and economic development, Austria and Czechoslovakia reached similar levels of per-capita CO2 emissions in the late 20th century. Neither Austrian "eco-efficiency" nor Czechoslovak restructuring have been effective in reducing CO2 emissions to a sustainable level.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 20 |
ID:
177145
|
|
|
|
|
| Summary/Abstract |
Although energy technological progress has been regarded as an important driver for reducing carbon emissions, the existence of carbon rebound effect prevents a portion of the potential carbon reductions to be realized. Compared with the energy rebound effect, research on the carbon rebound effect is scarce because it is always equated with the energy rebound effect. However, the carbon rebound effect is more complex. Given that the traditional method for carbon rebound effect assessment only reflects energy rebound effects, our study proposed an improved production-theoretical decomposition analysis (PDA)-Meta-frontier Malmquist index (MMI)-based method and explored carbon rebound effects in China from 2006 to 2015. Our results show that (1) the eastern and western regions faced fewer carbon rebound effect risks compared with those of the central region due to decreasing emission intensity associated with energy technological progress; (2) the reductions in emission intensity in the eastern region relied both on coal and non-coal technology, whereas the western region only relied on coal technology; and (3) the non-coal technology in the eastern region was at the meta-frontier, whereas the non-coal technology of other regions exhibited catch-up effects.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|