Decomposition for emission baseline setting in China's electricity sector

Decomposition analysis is used to generate carbon dioxide emission baselines in China's electricity sector to the year 2020. This is undertaken from the vantage point of the final consumer of electricity, and therefore considers factors influencing electricity demand, efficiency of generation, sources of energy used for generation purposes, and the effectiveness of transmission and distribution. It is found that since 1980, gains in efficiency of generation have been the most important factor affecting change in the emission intensity of electricity generated. Based upon known energy and economic policy, efficiency gains will continue to contribute to reductions in the emission intensity of electricity generated, however, fuel shifts to natural gas and increases in nuclear generation will further these trends into the future. The analysis confirms other sources in the literature that decomposition is an appropriate technique available for baseline construction, thereby suitable for the emerging carbon market and its related mechanisms.     

Biomass and China's carbon emissions: A missing piece of carbon decomposition

A number of previous studies on China's carbon emissions have mainly focused on two facts: (1) the continuous growth in emissions up till the middle of the 1990s; (2) the recent stability of emissions from 1996 to 2001. Decomposition analysis has been widely used to explore the driving forces behind these phenomena. However, since 2002, China's carbon emissions have resumed their growth at an even greater rate. This paper investigates China's carbon emissions during 1971–2003, with particular focus on the role of biomass, and the fall and resurgence in emissions since the mid-1990s. We use an extended Kaya identity and the well-established logarithmic mean Divisia index (LMDI I) method. Carbon emissions are decomposed into effects of various driving forces. We find that (1) a shift from biomass to commercial energy increases carbon emissions by a magnitude comparable to that of the increase in emissions due to population growth, (2) the technological effect and scale effect due to per-capita gross domestic products (GDP) growth are different in the pre-reform period versus the post-reform period, (3) the positive effect of population growth has been decreasing over the entire period, and (4) the fall in emissions in the late 1990s and resurgence in the early 2000s may be overstated due to inaccurate statistics.     

Changes in industrial electricity consumption in china from 1998 to 2007

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.     

China's energy consumption under the global economic crisis: Decomposition and sectoral analysis

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.     

Decomposition of aggregate energy intensity changes in two measures: ratio and difference

Decomposition analysis has been popular in energy demand analysis and has been found useful in policy-related studies. Past studies include decomposition of changes of an aggregate indicator, measured in terms of either ratios or differences, into several pre-defined contributing factors. Aggregate indicators that are often studied include total national energy demand, energy demand in specific consuming sectors, aggregate energy intensity and energy-related carbon dioxide emissions. However, the possible linkages between the ratio measure and the difference measure, including their decomposition results, have seldom been analysed. This paper examines this issue using the Divisia decomposition technique and a unique pair of decomposition formulae. Numerical examples based on Singapore and Taiwan industrial electricity demand data are presented.     

Analysis of the energy intensity evolution in the Brazilian industrial sector—1995 to 2005

This study developed a method to evaluate the evolution of energy intensity in the Brazilian industrial sector from 1995 to 2004. In order to do so, it was necessary to obtain six different measures (indicators) of the sector energy intensity. Considering the concept of energy intensity as the ratio between energy consumption and the level of economic activity, two measures were used for the energy consumption: a thermal (physical) and an economic one. For the level of economic activity, three measures were used: value of production, value of delivered goods and added value. In the Brazilian industrial sector, most of these indicators have behaved in a similar way. In a disaggregated way, energy intensity indicators show a unified direction of its evolution. However, a more elaborate study on the consumption profile of the Brazilian industrial sector and its economical activities indicates the presence of important deviations concerning the annual rate of change in energy intensity. Besides, there is no evident relation between these deviations and the composition of the different indicators of energy intensity.     

Determinants of energy demand in the French service sector: A decomposition analysis

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.     

Decomposition of industrial energy consumption : An alternative method

The paper develops a logically consistent method for decomposing a change in industrial energy consumption into the effects of three factors – structural change, energy intensity and output level. Numerical illustration of the method is given using 1973–1989 data for industrial energy consumption in the republic of Korea.     

Why did the energy intensity fall in China's industrial sector in the 1990s? The relative importance of structural change and intensity change

There have been a variety of studies investigating the relative importance of structural change and real intensity change to the change in China's energy consumption in the 1980s. However, no detailed analysis to date has been done to examine whether or not the increased energy efficiency trend in the 1980s still prevailed in the 1990s. This article has filled this gap by investigating the change in energy consumption in China's industrial sector in the 1990s, based on the data sets of value added and end-use energy consumption for the 29 industrial subsectors and using the newly proposed decomposition method of giving no residual. Our results clearly show that the overwhelming contributor to the decline in industrial energy use in the 1990s was the decline in real energy intensity, indicating that the trend of real energy intensity declines in the 1980s at the 2-digit level was still maintained in the 1990s. This conclusion still holds even if we lower the growth rate dramatically in line with the belief that the growth rate of China's GDP may be overestimated.     

End-use energy analysis in the Malaysian industrial sector

The industrial sector is the second largest consumer of energy in Malaysia. In this energy audit, the most important parameters that have been collected are as follows: power rating and operation time of energy-consuming equipments/machineries; fossil fuel and other sources of energy use; production figure; peak and off-peak tariff usage behavior and power factor. These data were then analyzed to investigate the breakdown of end-use equipments/machineries energy use, the peak and off-peak usage behavior, power factor trend and specific energy use. The results of the energy audit showed that the highest electrical energy-using equipment was an electric motor followed by pumps and air compressors. The specific energy use has been estimated and compared with four Indonesian industries and it was found that three Malaysian industries were more efficient than the Indonesian counterpart. The study also found that about 64% electrical energy was used in peak hours by the industries and the average power factor ranged from 0.88 to 0.92. The study also estimated energy and bill savings using highly efficient electrical motors along with the payback period.     

Firm-level determinants of energy and carbon intensity in China

In recent years, China׳s leaders have sought to coordinate official energy intensity reduction targets with new targets for carbon dioxide (CO₂) intensity reduction. The Eleventh Five-Year Plan (2006–2010) included for the first time a binding target for energy intensity, while a binding target for CO₂ intensity was included later in the Twelfth Five-Year Plan (2011–2015). Using panel data for a sample of industrial firms in China covering 2005 to 2009, we investigate the drivers of energy intensity reduction (measured in terms of direct primary energy use and electricity use) and associated CO₂ intensity reduction. Rising electricity prices were associated with decreases in electricity intensity and increases in primary energy intensity, consistent with a substitution effect. Overall, we find that energy intensity reduction by industrial firms during the Eleventh Five-Year Plan translated into more than proportional CO₂ intensity reduction because reducing coal use—in direct industrial use as well as in the power sector—was a dominant abatement strategy. If similar dynamics characterize the Twelfth Five-Year Plan (2011–2015), the national 17 percent CO₂ intensity reduction target may not be difficult to meet—and the 16 percent energy intensity reduction target may result in significantly greater CO₂ intensity reduction.     

Decomposition analysis of the variations in residential electricity consumption in Brazil for the 1980–2007 period: Measuring the activity,intensity and structure effects

Introduced at the end of the 1970s to study the impacts of structural changes on electricity consumption by industry, index decomposition analysis techniques have been extended to various other areas to help in the formulation of energy policies, notably in developed countries. However, few authors have applied these techniques to study the evolution of energy consumption in developing countries. In Brazil, the few available studies have focused only on the industrial sector. In this article, we apply the decomposition technique called the logarithmic mean Divisia index (LMDI) to electricity consumption of the Brazilian residential sector, to explain its evolution in terms of the activity, structure and intensity affects, over the period from 1980 to 2007. The technique is sufficiently robust and flexible to perform this analysis, by disaggregating residential consumers by consumption classes and regions of the country. Among the main results is measurement of the impact of government programs for income transfer and universal service on variations in residential consumption, typical of developing countries.     

Road transport-related energy consumption: Analysis of driving factors in Tunisia

The rapid growth of urban population and the development of road infrastructures in Tunisian cities have brought about many environmental and economic problems, including the rise scored in energy consumption and the increase in the quantity of gas emissions arising from road transport. Despite the critical nature of such problems, no policies have yet been adopted to improve energy efficiency in the transport sector. This paper aims to determine driving factors of energy consumption change for the road mode. It uses decomposition analysis to discuss the effects of economic, demographic and urban factors on the evolution of transport energy consumption. The main result highlighted in the present work is that vehicle fuel intensity, vehicle intensity, GDP per capita, urbanized kilometers and national road network are found to be the main drivers of energy consumption change in the road transport sector during 1990–2006 period. Consequently, several strategies can be elaborated to reduce road transport energy. Economic, fiscal and regulatory instruments can be applied in order to make road transport more sustainable.     

Air quality and climate change co-benefits for the industrial sector in Durban,South Africa

Industries in Durban, South Africa, are a major source of air pollutant emissions and large users of fossil fuel based energy. Durban’s energy strategy prioritises energy efficiency at industries as a key action, whilst industries are also the focus of the city’s air quality management plan (AQMP). In this paper, measures that have been introduced in industries in Durban to effect air quality improvements and reduce energy consumption are examined in terms of their respective impacts on greenhouse gas (GHG) and air pollutant emissions. It was found that co-benefits for GHG mitigation were achieved when petroleum refineries switched from using heavy fuel oil to refinery gas and methane rich gas. Within other industries, co-benefits for air quality stemmed from reducing fossil fuel energy consumption and the improved efficiency of combustion systems. Air quality and energy policies in the city are being executed independently, without consideration of the trade-offs or synergies of the interventions being implemented. Recommendations are made for authorities and industries to consider the co-benefits for GHG mitigation in their AQMPs and where these are not possible to consider offsetting the increased GHG emissions through improved alignment with energy strategies.     

Exergoeconomic aspects of sectoral energy utilization for Turkish industrial sector and their impact on energy policies

This study deals with this thermo-economic analysis of energy utilization in the industrial sector (IS) towards establishing energy policies. The relations between capital costs and thermodynamic losses for subsectors in the IS are investigated. In the analysis, Turkey is taken as an application country based on its actual data over the period from 1990 to 2003. Energy and exergy analyses are performed for eight industrial modes, namely iron–steel, chemical–petrochemical, petrochemical–feedstock, cement, fertilizer, sugar, non-metal industry, other industry. The energy and exergy utilization efficiency values for the entire Turkish IS are obtained to range from 63.45% to 70.11%, and from 29.72% to 33.23%, respectively. The ratio of thermodynamic loss rate-to-capital cost values is also calculated to vary from 0.76 to 1.01.     

Decomposition analysis of energy consumption in Chinese transportation sector

The purpose of this paper is to identify the relations between transportation energy consumption and its impacted factors. We first analyze the current status of transportation energy consumption in China. Then, the logarithmic mean Divisia index (LMDI) technique is used to find the nature of the factors those influence the changes in transportation energy consumption. We find that: (1) In 2006, the transportation energy consumption increased by 7.63 times against that in 1980. (2) Up to 2006, the oil consumed by transportation accounted for 49.6% of that in the whole country, which almost equaled to the net oil import. (3) In the light of the increasing energy consumption intensity, the energy-utilization effectiveness of transportation sector has been declining gradually. (4) The transportation activity effect is the most important contributor to increase energy consumption in the transportation sector and the energy intensity effect plays the dominant role in decreasing energy consumption.     

Decomposition analysis of CO2 emission in long-term climate stabilization scenarios

To achieve the stabilization of greenhouse gas (GHG) concentrations in the atmosphere, the international community will need to intensify its long-term efforts. Many EU countries have released national long-term scenarios toward 2050, and their ambitious targets for CO₂ emission reduction are aiming at a decrease of more than 50% of today's emission. In April 2004, Japan began a research project on its long-term climate policy. This paper discusses the long-term scenarios in other countries and the medium-term scenarios in Japan to support the development of a Japan's long-term climate stabilization scenario. In this study, CO₂ emission is decomposed with an extended Kaya identity (indexes: CO₂ capture and storage, carbon intensity, energy efficiency, energy intensity, economic activity) and a Reduction Balance Table is developed.     

Changes in the GHG emission intensity in EU-15: Lessons from a decomposition analysis

This paper analyses the reduction in greenhouse gas emissions in 15 countries of the European Union between 1990 and 2007 to find out the contribution of different countries. Using the log-mean Divisia index decomposition approach, it identifies the driving factors of emissions related to energy and other industrial activities. It also focuses on two success cases (namely Germany and the United Kingdom) and contrasts the developments with two less successful cases (namely Spain and Italy). A scenario analysis is then used to indicate the emission reduction possibility through cross-learning. The study shows that the emission intensity has reduced significantly in both energy-related activities and other processes at the aggregate level, while the performance varies significantly at the individual country level. Changes in the energy mix, a reduction in energy intensity and a reduction in the emission intensity from other process-related emissions were mainly responsible for the success in the EU-15.     

Taking out 1 billion tons of CO2: The magic of China's 11th Five-Year Plan?

China's 11th Five-Year Plan (FYP) sets an ambitious target for energy-efficiency improvement: energy intensity of the country's gross domestic product (GDP) should be reduced by 20% from 2005 to 2010 [National Development and Reform Commission (NDRC), 2006. Overview of the 11th Five Year Plan for National Economic and Social Development. NDRC, Beijing]. This is the first time that a quantitative and binding target has been set for energy efficiency, and signals a major shift in China's strategic thinking about its long-term economic and energy development. The 20% energy-intensity target also translates into an annual reduction of over 1.5 billion tons of CO₂ by 2010, making the Chinese effort one of the most significant carbon mitigation efforts in the world today. While it is still too early to tell whether China will achieve this target, this paper attempts to understand the trend in energy intensity in China and to explore a variety of options toward meeting the 20% target using a detailed end-use energy model.     

On China's energy intensity statistics: Toward a comprehensive and transparent indicator

A transparent and comprehensive statistical system in China would provide an important basis for enabling a better understanding of the country. This paper focuses on energy intensity (EI), which is one of the most important indicators of China. It firstly reviews China's GDP and energy statistics, showing that China has made great improvements in recent years. The means by which EI data are released and adjusted are then explained. It shows that EI data releases do not provide complete data for calculating EI and constant GDP, which may reduce policy transparency and comprehensiveness. This paper then conducts an EI calculation method that is based on official sources and that respects the data availability of different data release times. It finds that, in general, China's EI statistics can be considered as reliable because most of the results generated by author's calculations match the figures in the official releases. However, two data biases were identified, which may necessitate supplementary information on related constant GDP values used in the official calculation of EI data. The paper concludes by proposing short- and long-term measures for improving EI statistics to provide a transparent and comprehensive EI indicator.