Aggregate Energy Intensity Research Articles

The evolution and driving forces of industrial aggregate energy intensity in China: An extended decomposition analysis

This study adopts the log-mean Divisial index (LMDI) method to decompose the changes in the industrial aggregate energy intensity (IAEI) of China into both macro and technological factors: sectoral energy intensity, industrial structure, research and development (R&D) efficiency, R&D intensity and investment intensity. Afterwards we determine the contributions of 36 industrial sub-sectors to IAEI through different factors using attribution analysis. The results show that the IAEI decreased by 38.26% from 2003 to 2015. This drop is predominantly caused by R&D efficiency (−76.01%). The sub-sectors of ferrous metals (−14.94%) and non-metallic mineral products (−13.36%) are the main contributors to the R&D efficiency effect. The sectoral energy intensity effect contributes −27.19%, mainly due to the sub-sectors of ferrous metals (−15.97%) and non-ferrous metals (−5.68%). The industrial structure effect also contributes to a decline of IAEI (−15.06%), of which, petroleum, coking and nuclear fuel (−5.57%) and ferrous metals (−4.73%) are the sub-sectors that contribute the most. Conversely, investment intensity (174.09%) and R&D intensity (52.06%) contribute to increase the IAEI, largely owing to sub-sectors of petroleum, coking and nuclear fuel processing, chemical materials and non-metallic mineral products. Our findings suggest that the combined effects of the policies implemented during the time frame of 2003 to 2015 led to a reduction in IAEI, with investment intensity being the focus of improvement. Nevertheless, different policies and measures should be put forward in different sub-sectors due to their varying degrees of adaptability and policy sensitivity.

Directed Technical Change and Energy Intensity Dynamics: Structural Change vs. Energy Efficiency

This paper uses a model with Directed Technical Change to theoretically analyse observable heterogeneous energy intensity developments. Based on the empirical evidence, we decompose changes in aggregate energy intensity into structural changes in the economy (structural effect) and within-sector energy efficiency improvements (efficiency effect). The relative importance of these effects is determined by energy price growth and sectoral productivities that drive the direction of technical change. When research is directed to the labour-intensive sector, the structural effect is the main driver of energy intensity dynamics. In contrast, the efficiency effect dominates energy intensity developments, when research is directed to energy-intensive industries. Increasing energy price generally leads to lower energy intensities and temporal energy price shocks might induce a permanent redirection of innovation activities. We calibrate the model to empirical data and simulate energy intensity developments across countries. The results of our very stylised model are largely consistent with empirical evidence.

Energy intensity and its components in Iran: Determinants and trends

Iran energy intensity is among the highest in the world, which has been increasing during the recent decades, originating from the channels related to the efficiency and structural (scale) changes. The present study aimed to investigate the changes in the aggregate energy intensity (EI) and its components including the Efficiency (EE) and Structural Change (SC) indices as well as their driving forces based on a regression analysis. Furthermore, the multilayer perceptron and wavelet-based neural networks (WNN) were proposed to evaluate the ability of regression models in forecasting energy intensity and its components. The results suggested a non-linear relationship between the energy intensity indices and income as well as the capital-output ratio. However, no significant role was observed for trade and energy price index. Further, the turning points measured for income and the capital-labor ratio indicated that the effect of income on energy intensity is increasing while the capital-energy is turning out to be as the substitutes. Furthermore, urbanization could significantly reduce energy intensity. The forecast results indicated that energy intensity and its components may be predicted with a prediction error of less than 0.35%. Finally, EE and SC can be predicted more accurately based on the ANN-based models while the regression models can predict the EI index more precisely.

Structural Change and Convergence of Energy Intensity Across OECD Countries, 1970-2005

This paper uses a new dataset derived from a consistent framework of national accounts to compute and evaluate energy intensity developments across 18 OECD countries and 50 sectors over the period 1970-2005. We find that across countries energy intensity levels tend to increase in a fairly wide range of Services subsectors, but decrease in most Manufacturing sectors. A decomposition analysis reveals that changes in the sectoral composition of the economy explain a considerable and increasing part of aggregate energy intensity dynamics. A convergence analysis reveals that only after 1995 cross-country variation in aggregate energy intensity levels clearly tends to decrease, driven by a strong and robust trend break in Manufacturing and enhanced convergence in Services. Moreover, we find evidence for the hypothesis that across sectors lagging countries are catching-up with leading countries, with rates of convergence on average being higher in Services than in Manufacturing. Aggregate convergence patterns are almost exclusively caused by convergence of within-sector energy intensity levels, and not by convergence of the sectoral composition of economies.

Industrial structure, energy-saving regulations and energy intensity: Evidence from Chinese cities

Exploring the drivers of declining energy intensity is necessary in order to accelerate the transition to a low-carbon economy in China. To date, studies have typically adopted case analysis to link enterprise features and energy-saving performance. The impact of internal industrial configuration in terms of size and ownership structure on aggregate energy intensity remains to be examined. To fill this research gap, this paper tests the impact of the internal structure of industries on city-level energy intensity, by employing a unique panel dataset of 283 cities for the period 2005 to 2010. The Driscoll-Kraay method and instrumental variable are used to treat residual cross-sectional dependence and endogeneity, respectively. Results suggest that small-scale enterprises exerts a negative effect on energy intensity. A 1% increase in the output-value proportion of small-sized firms will lead to a decrease in total energy intensity of 0.067%. In contrast, the same change by medium enterprises will raise energy intensity by 0.031%. A negative and/or non-significant coefficient suggests that for most energy-intensive large and state-owned enterprises, China's 2006 top-down energy-saving regulation has been quite effective in targeting key energy-intensive enterprises in China. The findings reveal that state-owned enterprises (SOEs) can act as promoters of, rather than barriers to, low-carbon policy implementation in China. Given that the effectiveness of energy-saving regulation will be undermined as a result of diluted regulatory strength in each enterprise, market-oriented energy price reform is proposed as a fundamental driver for guaranteeing a continual decline in energy intensity.

Measuring energy intensity in Japan: A new method

Energy intensity and energy conservation have been important pillars of energy policies in Japan. Recently, the government has introduced new initiatives to enhance energy efficiency and reduce energy intensity. We analyze the energy intensity in Japan for the period 1973–2006 by proposing a new method which takes into account all other inputs used in production and corrects for the bias in the traditional energy intensity measure. We show that the traditional energy intensity measure has serious flaws. The traditional measure overestimates actual energy intensity before the mid-1980s and largely underestimates afterwards. It is found that aggregate energy intensity has risen remarkably from 1991 to 2001. The main cause of this rise is the rapid rise in energy intensity in manufacturing and energy sectors.

A spatial–temporal decomposition approach to performance assessment in energy and emissions

There has been growing interest among researchers and policymakers in comparing or benchmarking countries on the basis of their performance in energy consumption or energy-related CO2 emissions. Such studies allow variations among countries to be revealed, the contributing factors identified, and the scope for improvement better understood. At the same time, tracking changes or quantifying improvements in energy use or emissions over time in a country have long been a focus area of researchers and policy makers. To provide a fuller picture on country performance in a multi-country study over time, it would be of interest to integrate the above-mentioned spatial and temporal analyses in a single analysis framework. This paper deals with this issue using the technique of index decomposition analysis. A spatial–temporal approach is introduced and two application cases are presented to illustrate how the approach can be applied. The first analyzes variations and changes in the aggregate CO2 intensity of electricity production for ten countries from 1990 to 2010, and the second deals with variations and changes in the aggregate energy intensity for eight economic regions of China from 2002 to 2012. In addition, two different ways of presenting the results are introduced. Our study shows that the proposed approach can supplement studies which are conducted purely on a spatial or temporal basis.

Directed Technical Change and Energy Intensity Dynamics: Structural Change vs. Energy Efficiency

This paper uses a theoretical model with Directed Technical Change to analyse the observed heterogeneous energy intensity developments. Based on the empirical evidence on the underlying drivers of energy intensity developments, we decompose changes in aggregate energy intensity into structural changes in the economy (Sector Effect) and within-sector energy efficiency improvements (Efficiency Effect). We analyse how energy price growth and the relative productivity of both sectors affect the direction of research and hence the relative importance of the aforementioned two effects. The relative importance of these effects is determined by energy price growth and relative sector productivity that drive the direction of research. In economies that are relatively more advanced in sectors with low energy intensities, the Sector Effect dominates energy intensity dynamics given no or moderate energy price growth. In contrast, the Efficiency Effect dominates energy intensity developments in economies with a high relative technological level within their energy-intensive industries if moderate energy price growth is above a certain threshold. We further show that temporal energy price shocks might induce a permanent redirection of innovation activities towards sectors with low-energy intensities.

Multilevel decomposition analysis of energy intensity in the Thai road transport sector

ABSTRACTThis article presents the changes of aggregate energy intensity in the road transport sector in Thailand. Seven vehicle types in the Greater Bangkok (GBKK) and the provincial areas are considered during 1990–2007. Vehicle types consist of sedans, vans and pickups, motorcycles, taxis, buses, trucks, and others. The logarithmic mean Divisia multilevel decomposition method is employed to investigate the changes in aggregate energy intensity through structural effect, energy intensity effect, and fuel share effect. Results show that the aggregate energy intensity decreased by 39.6% in 2007 due to decreasing in energy intensity and structural effects. In the area level, the aggregate energy intensity decreased in the provincial area by 30.3% and in the GBKK area by 13.4%. The energy intensity effect decreased in all vehicle types, except in taxis, while the structural effect decreased in all vehicle types, except in sedans. Results could be used to formulate strategic plans of energy-efficiency measures in the transport sector.

Industrial energy use and carbon emissions reduction: a UK perspective

Progress in reducing industrial energy demand and carbon dioxide (CO2 ) emissions is evaluated with a focus is on the situation in the United Kingdom (UK), although the lessons learned are applicable across much of the industrialized world. The UK industrial sector is complex, because it may be viewed as consisting of some 350 separate combinations of subsectors, devices and technologies. Various energy analysis and carbon accounting techniques applicable to industry are described and assessed. The contributions of the energy‐intensive (EI) and nonenergy‐intensive (NEI) industrial subsectors over recent decades are evaluated with the aid of decomposition analysis. An observed drop in aggregate energy intensity over this timescale was driven by different effects: energy efficiency improvements; structural change; and fuel switching. Finally, detailed case studies drawn from the Cement subsector and that associated with Food and Drink are examined; representing the EI and NEI subsectors, respectively. Currently available technologies will lead to further, short‐term energy and CO2 emissions savings in manufacturing, but the prospects for the commercial exploitation of innovative technologies by mid‐21st century are far more speculative. There are a number of nontechnological barriers to the take‐up of such technologies going forward. Consequently, the transition pathways to a low carbon future in UK industry by 2050 will exhibit large uncertainties. The attainment of significant falls in carbon emissions over this period depends critically on the adoption of a limited number of key technologies [e.g., carbon capture and storage (CCS), energy efficiency techniques, and bioenergy], alongside a decarbonization of the electricity supply. WIREs Energy Environ 2016, 5:684–714. doi: 10.1002/wene.212This article is categorized under: Energy Efficiency > Science and Materials Energy Efficiency > Economics and Policy Energy Efficiency > Climate and Environment

Analysis of the importance of structural change in non-energy intensive industry for prospective modelling: The French case

A large number of studies have been conducted on the contribution of technological progress and structural change to the evolution of aggregate energy intensity in the industrial sector. However, no analyses have been done to examine theses changes in the non-energy intensive industry in France. We analyzed their importance in French industry with respect to their energy intensity, energy costs, value added, labour and the diffusion of production sites by using data at the 3-digit level with 236 sectors. Using a new decomposition method that gives no residual, this paper attempted to examine, over 10 years from 1996 to 2005, the changes that occurred in an area that has been neglected in energy analysis. We found that structural change had an overwhelming effect on the decline of aggregate energy intensity. Furthermore, we found that the higher the level of sector disaggregation, the more significant the changes that can be attributed to structural change, due to the homogeneity of this industrial group. The results of our study show that it is important to take into account the effects of structural change in “bottom-up” modelling exercises so as to improve the accuracy of energy demand forecasting for policy-makers and scientists.

Peeling the onion: Analyzing aggregate, national and sectoral energy intensity in the European Union

One of the most promising ways of meeting climate policy targets is improving energy efficiency, i.e., reducing the amount of scarce and polluting resources needed to produce a given quantity of output. Relying upon the World Input-Output Database (WIOD), we investigate the decline in energy intensity in the EU27 countries between 1995 and 2009. Changes in energy intensity can be attributed to two different drivers: changes in the industrial composition of an economy and changes in its sectoral energy intensities. We conduct a series of index decomposition analyses (IDA) to isolate the effects exerted by these drivers. We then take the findings from the index decomposition analysis and subject them to panel estimations. The objective is to control for factors that may have shaped the evolution of energy intensity in the European Union. We estimate the changes in energy intensity as well as the changes in (energy-relevant) structural change and in the sectoral energy intensities. Therefore, we are able to reveal the channels through which factors such as economic growth, capital intensity, and energy prices affect energy intensity.

Peeling the Onion: Analyzing Aggregate, National and Sectoral Energy Intensity in the European Union

One of the most promising ways of meeting climate policy targets is improving energy efficiency, i.e. reducing the amount of scarce and polluting resources needed to produce a given quantity of output. This study undertakes an empirical exercise using the World Input-Output Database (WIOD), a harmonized dataset comprising time-series of input-output tables along with environmental satellite accounts and socioeconomic information. The paper consists of two parts. In the first part we begin with an aggregated picture of EU27 energy intensity and its evolution between 1995 and 2009. Then we dig deeper and introduce sectoral detail to identify the economic changes that occurred during the same period. Finally, we disaggregate the EU27 into countries for regional analysis and perform a sectoral disaggregation for a fine-grained picture of energy intensity in Europe. In the second part of the study we take our findings from index decomposition analysis and subject them to panel estimations. The objective is to control for factors that may have shaped the evolution of energy intensity in the European Union. In particular, we investigate the impact of technological change, structural change, trade, environmental regulation and country-specific characteristics.

Provincial energy intensity in China: The role of urbanization

Chinese policymakers have attached great importance to energy intensity reduction. However, the unprecedented urbanization process exercises additional pressure on the realization of energy intensity reduction targets. A better understanding of the impacts of urbanization is necessary for designing effective policies aimed at reaching the next energy intensity reduction targets. This paper empirically investigates the impacts of urbanization on China's aggregate and disaggregated energy intensities using a balanced panel dataset of 30 provinces covering the period from 2000 to 2012 and panel estimation techniques. The results show that urbanization significantly increases aggregate energy intensity, electricity intensity and coal intensity.

Decomposition Analysis of Aggregate Energy Intensity Changes in Tunisia over the Period 1980–2007

The aim of this paper is to investigate the main factors that have contributed to the decline in aggregate energy intensity of the Tunisian economy, during the period 1980–2007. Using the Logarithmic Mean Division Index (LMDI) decomposition method, we decompose the total changes in energy intensity into inter-fuel substitution effects, technological effects, and structural effects. The decomposition analysis is carried out at two levels of sectoral disaggregation (3 sectors and 13 sub-sectors) and uses three energy sources: petroleum, natural gas, and electricity. Our results show that the main contributor to the decline in energy intensity of the Tunisian economy throughout the period studied is the technological effect. This result was confirmed when we decomposed the energy intensity changes in the industrial and service sectors. On the other hand, the inter-fuel substitution effect contributed to increasing energy intensity, but without affecting its general downward trend. Finally, for the structural effects, we observed a significant mutual effect of cancellation at sector and sub-sector levels.

The Role of Energy Quality in Shaping Long-Term Energy Intensity in Europe

On the European aggregate level there is an inverted-U curve for long-term energy intensity. In the 19th century aggregate European energy intensity rose, followed by a declining trend during the 20th century. This article discusses the possible explanations for the declining trend during the 20th century and explores the role of energy quality as expressed in energy prices. For the first time a complete set of national energy retail prices covering two centuries has been constructed and used for Britain, while the energy price data previously available for Sweden until 2000 has been updated to 2009. This allows us to explore the role of energy quality in shaping long-term energy intensity. We find no relation between energy quality and energy intensity in the 19th century, while energy quality may have stimulated the declining energy intensity in Europe over the 20th century, but is not the sole or even main reason for the decline. Rather, increased economic efficiency in the use of energy services seems to have been the main driver for the decline after 1970, presumably driven by the information and communication technology.

Exploring energy efficiency in several European countries. An attribution analysis of the Divisia structural change index

This paper aims at exploring the influence that the changes in sectoral composition in most EU economies have had on aggregate energy intensity. We rely on the so-called Logarithmic Mean Divisia Index (LMDI) method, implemented within a multiplicative energy intensity approach. Then, based on the Index Decomposition Analysis (IDA), we present, develop and apply a new methodology that enables the exploration of the contribution of each sector to the percent change in the structural factors index. Our findings show: (a) a greater importance of the intensity factor over the structural one, (b) a positive influence of structural change in some ex-communist countries, and (c) a strong, negative contribution of the industrial sector (including construction) to changes in aggregate energy intensity in most European economies, particularly in the Western ones. In short, adaptation to more efficient techniques, innovation, R&D, and substitution for higher quality energies, seem to be the action lines to follow, although in former communist countries these strategies should be accompanied by other policies aiming at accelerating the transition processes.

Dynamics and determinants of energy intensity in the service sector: A cross-country analysis, 1980–2005

We present a detailed analysis of energy intensity developments across 23 service sectors in 18 OECD countries over the period 1980–2005. We find that the shift towards a service economy has contributed to lower overall energy intensity levels in the OECD, but this contribution would have been considerably larger if the service sector had realized the same degree of energy efficiency improvements as the manufacturing sector. In most OECD countries energy intensity levels in services tend to decrease relatively slow, especially after 1995. If we control this trend for the impact of structural changes within the services sector – by means of a decomposition analysis – we find that in about one-third of the OECD countries, energy intensity levels in services have increased over time. The impact of structural changes on aggregate energy intensity dynamics in services has increased considerably after 1995, highlighting a relatively poor energy efficiency performance within a wide range of service sectors. We show that the introduction of Information and Communication Technology (ICT) plays a potentially important role here. Using panel data regression analysis, we find a limited role for energy prices in explaining variation in energy productivity, while climate conditions clearly impact energy productivity.

Extended Divisia index decomposition of changes in energy intensity: A case of Korean manufacturing industry

This study aims to examine the energy efficiency of the manufacturing industry of Korea by using the extended Divisia index decomposition of Choi and Ang (2012). First, we applied the Sato–Vartia index decomposition to the energy intensity of the manufacturing industry in Korea. Second, we attributed the growth rate of aggregate energy intensity to 10 sub-manufacturing industries through two channels: real energy intensity and structural change. The result of the decomposition illustrates that the aggregate energy intensity index decreased in the period 1981–2010. The index decomposition analysis demonstrates that real energy intensity decreased by 85.85%, whereas structural change increased energy intensity by 69.37% over the same period of time. The negative effect of structural change is partly a result of the increasing portion of energy intensive industry in manufacturing. The result reflects that industrial structure in Korea can be an important aspect for improving energy efficiency.

The energy transition of the transition economies: An empirical analysis

The aggregate manufacturing energy intensity of 28 countries in Eastern Europe and Central Asia had declined by 35% during 1998–2008. This study reveals a strong evidence of convergence: less efficient countries improved more rapidly and the cross-country variance in energy productivity narrowed over time. An index decomposition analysis indicates that energy intensities declined largely because of more efficient energy use rather than shifts from energy intensive to less intensive manufacturing activities. Income growth and energy price increases were the main drivers of the convergence. They dominated the impact of trade, which led to specialization in energy intensive industries.