Changes In Energy Intensity Research Articles

Decomposing the South African CO2 emissions within a BRICS countries context: Signalling potential energy rebound effects

This paper employs an LMDI decomposition exercise to investigate the main factors that affect changes in CO2 emissions of South Africa at national level within the BRICS group of countries (Brazil, Russia, India, China, and South Africa) from 1990 to 2014. From the results, it is expected to derive some information on the existence of the energy rebound hypothesis for South Africa with ultimate purpose to direct future research into examining the effect in a micro level. The aim of this paper is not to estimate the precise rebound effect but to decompose the determinants of emission changes in the BRICS countries. The concept of energy rebound would play a role if the improvements in energy intensity might lead to emission increases, instead of the opposite as expected. The overall results suggest that the changes in CO2 intensity and energy intensity had a negative impact to the changes in CO2 emissions: in other words, as the energy intensity (energy consumption per unit of economic output) decreased for all the countries (possible technological developments), the emissions kept rising. For South Africa specifically, the energy intensity was a negative contributor to CO2 emissions only for the part of the examined period (2008–2014).

Investigation of mechanical properties of limesand brick under dynamic loading

The results of experimental study of mechanical properties of samples of lime-sand brick under dynamic loading are presented. The tests were carried out using the traditional Kolsky method and its modification - dynamic splitting (the so-called «Brazilian test»). The laws of change in strength, strain, time properties and energy intensity of the investigated material are established in the strain rate range of 5·102-2.5·103 s-1 under compression and in the stress rate range of 2·101-3·102 GPa/s under tension.

СТАЛИЙ РОЗВИТОК ЕНЕРГЕТИКИ УКРАЇНИ У СВІТОВИХ ВИМІРАХ

У статті визначено основні тенденції розвитку світової енергетики та масштабні зміни, що відбулись за останні роки, в енергетиці. Розглянуто досвід передових країн світу та енергетичних об'єднаннь для формування заходів покращення стану енергофективності.Визначено стан енергоефективності України, зокрема динаміку зміни енергоємності ВВП України, наведено рівень енергоємності з іншими країнами, дана характеристика енергоефективності регіонів України та характеристика споживання основних енергоресурсів. Здійснено порівняння стану енергетики України за індексом Енергетичної Трилеми. Наведено причини зниження енергоємності ВВП України. Виконано моніторинг енергоефективності галузей економіки та регіонів України.Розглянуто орієнтири розвитку енергетичн галузі відповідно до Енергетичної стратегії країни на період до 2035 року. Описано заходи для покращення енергоефективності. Наведено кроки для покращення стану, описані в Директиві Європейського Союзу з енергоефективності. Проаналізовано досвід передових країн світу щодо розвитку інтеграції відновлювальниї джерел енергії в енергетичну систему України.З врахуванням досвіду передових країн світу дані рекомендіції для покращення стану енергоефективності України через поширення використання нетрадиційних відновлювальних джерел енергії, реформи в галузях з викоким рівнем енергоємності та розвитком системи енергоменеджменту.

Overcoming the shortcomings of energy intensity index: a directional technology distance function approach

In multilateral comparisons of environmental performance over time, energy intensity measures, especially “real” energy intensity computed either by index decomposition approach or structural decomposition approach, are the most commonly used measures. Recently, researchers also resort to production-theoretical approach, which relies on data envelopment analysis techniques, to decompose energy intensity changes over time into their subcomponents. While their intuitiveness and computational ease make these indices attractive, their time series properties create considerable challenges in performing informative and fair comparisons among the energy efficiency levels of units considered. Furthermore, the resultant measure of energy intensity in these studies is still the inverse of a partial factor productivity (PFP) measure, i.e., energy productivity, that does not take into consideration compositional differences between inputs of the units being compared (which are also subject to change over time) and that ignores the type of substitution among inputs and, hence, makes it a measure that disguises rather than illuminates. The theoretical part of this paper shows how one can overcome the shortcomings of the energy intensity measure by constructing a new energy index using directional technology distance functions. The new index constructed in this study not only overcomes the shortcomings of the energy intensity measures but also satisfies the axiomatic properties of index numbers that are laid down by Fisher. An empirical application on U.S state-level agricultural sectors further complements existing studies.

Numerical analysis and experimental study on micro-holes in solid-liquid two-phase abrasive flow machining

In order to solve the problem that the aperture of the small hole part is too small and the irregular shape of the surface is difficult to be processed. A solid - liquid two - phase abrasive grain polishing method is proposed. Based on the standard model and SIMPLEC algorithm, the numerical simulation of the surface of the micro – holes were carried out under different inlet speed conditions. The change of the turbulence kinetic energy, dynamic pressure and turbulence intensity of the micro – holes flow channel with the inlet velocity is discussed. The quality control law of the inlet velocity on the sol-id-liquid two-phase abrasive flow polishing. In order to verify the accuracy of the numerical analysis, the necessary solid-liquid two-phase flow polishing test was carried out with the micro-hole parts. The surface roughness of the inner surface of the micro-holes before and after polishing was tested. The results show that the surface roughness is reduced from 1.702 before polishing to 0.303 after polishing. The solid - liquid two - phase abrasive flow machining can effectively improve the surface quality of micro – holes.

Analysis of the energy intensity of Kazakhstan: from data compilation to decomposition analysis

There are large gaps in energy consumption data and consequently in the estimates of CO2 emissions from fuel combustion in Kazakhstan. This study provides the first comprehensive review of energy consumption trends in Kazakhstan, discusses several important discrepancies in energy statistics and presents an improved versions of Energy Balances, developed using additional data. The results indicate that Kazakhstan’s energy intensity of gross domestic product (GDP) declined by 30% from 1.14 to 0.8 toe/thousand 2005USD between 2000 and 2014. To understand factors influencing this decline, the change in energy intensity of GDP was decomposed using the Logarithmic Mean Divisia Index I method. The upstream sector (mainly oil and gas) played the most important role in the observed GDP energy intensity change. Although the share of this sector in total GDP increased, causing an increase in energy intensity due to inter-sectoral structural effects, the consequences were counteracted by a twofold decline in the sector’s energy intensity, resulting in a net decrease. On the contrary, the power and heat, transport and household sectors saw an increase in energy intensity between 2000 and 2014. The results clearly demonstrate that there is an urgent need for policies and measures to be put in place in the power and heat, household and transport sectors, to support renewable energy development, increase buildings’ energy efficiencies, replace inefficient stoves and improve heating systems and encourage changes in public transportation systems. Furthermore, improving energy statistics and setting appropriate sectoral energy intensity reduction targets are crucial for achieving real efficiency improvements in the economy.

Understanding China's industrial CO2 emissions: A comprehensive decomposition framework

Because industrial sector in China is energy-intensive, clarifying the main factors driving CO2 emissions in this sector is of great importance for the carbon emission reduction and further sustainable development of China's economy. This paper combines production-theoretical decomposition analysis (PDA) and index decomposition analysis (IDA) to decompose China's industrial CO2 emission changes into seven factors: energy mix change, potential energy intensity change, economic activity, energy usage efficiency, energy saving technology change, GDP technical efficiency, and GDP technology change. The main findings are as follows: (1) during 2000–2015, industrial CO2 emissions increased 2.6560 times, economic activity was the largest contributor to increasing industrial CO2 emissions but varied significantly across provinces. (2) GDP technology change and potential energy intensity change were the dominant contributors to industrial CO2 mitigation. However, in several western provinces, potential energy intensity change played a positive role in increasing CO2 emissions. Therefore, local governments should adopt effective measures to improve technology levels in western provinces. (3) Energy-saving technology change also led to a reduction in CO2 emissions in most provinces, although its inhibiting effect was very small (annual average decrease rates were less than 3%). (4) Energy mix change, energy usage efficiency, and GDP technical efficiency played insignificant roles in affecting industrial CO2 emissions and had mixed results across provinces. This detailed information about the factors driving industrial CO2 emissions will be important for central and local governments in China in formulating emission-reduction policies.

Analysis on the influencing factors of carbon emissions from energy consumption in China based on LMDI method

Based on the time series decomposition of the Log-Mean Divisia Index, this paper analyzes the driving factors of carbon emissions from energy consumption by introducing the indicators of energy trade in China during the period of 2000–2014. The carbon emissions are decomposed into carbon emission coefficient, population, economic output, energy intensity, energy trade, energy structure and industrial structure effect in the manuscript. The result indicates that economic activity has the largest positive effect on the variation of carbon emissions. The energy trade has a greatest opposite effect on carbon emission change. At the same time, China has achieved a considerable decrease in carbon emission mainly due to the improvement of energy intensity and the optimization of energy and industrial structure. However, the influences of those changes in energy intensity, energy and industrial structure are relatively small. In addition, through the analysis by using a suitable index of energy trade, it was found that improving the conditions of energy trade can effectively optimize the energy structure and reduce the carbon emission in China.

How accurate are energy intensity projections?

Recent projections of energy intensity predict a more rapid decline in intensity than has occurred in the recent past. To assess how well such projections have performed in the past, I assess the accuracy of the business as usual energy intensity projections embedded in the annual World Energy Outlook (WEO) produced by the International Energy Agency since 1994. Changes in energy intensity depend on economic growth, and historical errors in projecting energy intensity can partly be explained by errors in projecting the rate of economic growth. However, recent projections of the elasticity of energy intensity with respect to economic growth probably overstate the likely future reduction in energy intensity even if economic growth is projected accurately. This could be because energy efficiency policies are not implemented as effectively as expected or because the economy-wide rebound effect is larger than modeling assumes.

Theoretical Explanations for the Inverted-U Change of Historical Energy Intensity

Historical experience shows that the economy-wide energy intensity develops nonmonotonically like an inverted U, which still lacks direct theoretical explanations. Based on a model of structural change driven by technological differences, this paper provides an attempt to explore the underlying mechanisms of energy intensity change and thus to explain the above empirical regularity accompanied by structural transformation, through introducing a nested constant elasticity of substitution production function with heterogeneous elasticities of substitution. According to some reasonable assumptions, this extended model not only describes the typical path of structural change but also depicts the inverted-U development of economy-wide energy intensity. With the availability of Swedish historical data, we take calibration and simulation exercises which confirm the theoretical predictions. Furthermore, we find that: (1) elasticities of substitution may affect the shapes and peak periods of the inverted-U curves, which can explain to a certain extent the heterogeneous transitions of economy-wide energy intensity developments in different economies; and (2) over long periods of time, the economy-wide energy intensity determined by the initial industrial structure and sectoral energy intensity tends to grow upward, while structure change among sectors provides a driving force on reshaping this trend and turning it downward.

The role of government in industrial energy conservation in China: Lessons from the iron and steel industry

This paper tracks the energy use and changes to China's energy-efficiency regulatory framework governing the iron and steel industry for the last thirty years. The detailed institutional analysis identifies both abating and augmenting effects of the regulatory framework changes on the energy intensity changes. The paper then assesses the impacts of various other factors on the energy intensity of China's iron and steel industry by using time-series data on the sector level. The quantitative analysis shows that technology progress, specifically the production process transition from high-energy intensive open-hearth furnace (OHF) to more energy efficient basic-oxygen furnace (BOF), is the biggest contributor to energy intensity reductions in China's iron and steel industry in the last thirty years, even after controlling for regulatory change and policy incentives. The ownership reform resulting from changes in the regulatory framework change contributed to energy intensity reductions in China's iron and steel industry, while fast market expansion resulting from market liberalization and regulation decentralization served as a principal barrier for energy efficiency improvements. Government policies, represented by financial subsidies from governments, correspond with energy intensity reductions in key large and medium sized enterprises, but interestingly, seem to be ineffective at producing energy intensity reductions for the industry as a whole. As other research indicated, rising coal prices also contributed to energy intensity reductions in China's iron and steel industry. Finally, the paper concludes that, to further incentivize energy intensity reductions, the Chinese government should consider correcting the negative impacts of the regulatory framework change, as well as transferring production processes to the highly energy efficient electric-arc furnace (EAF) and extending policy regulations to wider enterprise groups.

Reducing global CO2 emissions with the technologies we have

The energy intensities of the various industrial sectors differ considerably across countries. This suggests a potential for emissions reductions through improved accessibility to efficient technologies. This paper estimates an upper-bound CO2 emission mitigation potential that could theoretically be achieved by improved access to efficient technologies in industrial sectors. We develop a linear optimization framework that facilitates the exchange of sectoral production technologies based on the World Input-Output Database (WIOD), assuming perfect substitutability of technologies and homogeneity within economic sectors, while ignoring barriers to technological adoption and price driven adjustments. We consider the full global supply chain network and multiple upstream production inputs in addition to energy demand. In contrast to existing literature our framework allows to consider supply chain effects of technology replacements. We use our model to calculate emission reduction potentials for varying levels of access to technology. If best practice technologies were made available globally, CO2 emissions could theoretically be reduced by more than 10 gigatons (Gt). In fact, even second-tier production technologies would create significant global reduction potentials. We decompose sectoral emission reductions to identify contributions by changes in energy intensity, supply chain effects and changes in carbon intensities. Excluding the latter, we find that considering supply chain effects increases total mitigation potentials by 14%. The largest CO2 emission reduction potentials are found for a small set of developing countries.

The driving forces of the change in China's energy intensity: An empirical research using DEA-Malmquist and spatial panel estimations

Energy shortage and environmental degradation have become significant hurdles for China's sustainable development nowadays. One of the most efficient and effective ways to ease energy shortage is to sufficiently reduce energy intensity. In the extant literature on the influential factors of China's energy intensity, the regional imbalance and spatial spillover effects were basically ignored, which may yield to biased and unreasonable results. As a result, in this paper, the driving forces of China's provincial energy intensity were for the first time investigated by combining the Data Envelopment Analysis (DEA)-Malmquist and spatial panel approaches for the period between 2000 and 2014. The results indicate that technological progress plays a dominant role in decreasing China's overall energy intensity. In both the Eastern and Central regions, the technological progress and its components can decrease energy intensity, while this effect doesnot significantly exist in the Western region. Rapid industrialization should be responsible for China's currently high energy intensity, while energy price hiking is conducive to the decrease in energy intensity. Moreover, there is also clear evidence that these factors influence on energy intensity partly through the spatial spillover effects.

Decomposition analysis of the decoupling indicator of carbon emissions due to fossil energy consumption from economic growth in China

This study decomposed the indicator of decoupling of carbon emissions due to fossil energy consumption from economic growth in China via the logarithmic mean Divisia index (LMDI) method to explore key factors influencing decoupling status in different periods. The decoupling indicator was decomposed into energy structure, energy intensity, economic structure, and economic output effects over each period. Decoupling varied due to changes in economic growth and energy intensity during different periods. The economic output effect significantly enhanced decoupling, while the energy intensity effect greatly decreased decoupling. The energy structure and economic structure effects had slight impacts on decoupling. A comparative analysis across different sectors and industrial subsectors revealed that industrial growth determined the status of decoupling of carbon emissions from economic growth in China. In terms of industrial subsectors, the major sources of carbon emissions were electricity, steam, and water production and other energy-intensive subsectors. The energy-intensive subsectors, such as coal mining and washing, petroleum and natural gas exploitation, and chemical manufacture, had great effects on the decoupling of carbon emissions, whereas non-energy-intensive subsectors, such as instruments, meters, cultural and office machinery, and ordinary equipment manufacture, had relatively slight impacts on the decoupling. Policy implications in terms of economic growth, economic structure, and energy consumption were discussed.

Measuring improvements in industrial energy efficiency: A decomposition analysis applied to the UK

Decomposition analysis can provide a useful efficiency metric for the industrial sector, it does so by separating the influence of changes in energy intensity from structural and activity changes. The activity refactorisation (AR) approach to decomposition analysis offers a potentially improved methodology, with a better correlation to real efficiency improvements. This is achieved through combining monetary and physical output data. Here the AR approach is compared to other methodologies for the United Kingdom industrial sector over the period 1997–2012. Even with limited availability of physical output data the AR approach was found to provide significantly different results to those obtained using only monetary output measures. When monetary output was the sole measure of activity, intensity (efficiency) improvements were overestimated. It is recommended that physical output data is supplied alongside energy demand and monetary output data in national accounts to better track efficiency improvements and allow such improved metrics to feed into decarbonisation policy discussions.

Provincial-level carbon emission drivers and emission reduction strategies in China: Combining multi-layer LMDI decomposition with hierarchical clustering

Understanding provincial-level driving mechanisms of carbon emissions is critical for achieving China's national action targets on climate change mitigation. The paper combines two-layer logarithmic mean divisia index (LMDI) decomposition with Q-type hierarchical clustering to systematically evaluate the contributions of related drivers from 30 provinces to the growths in China's national carbon emissions, and accordingly puts forward more targeted emissions reduction strategies for each cluster of provinces based on the features of CO2 emissions and underlying emissions driving forces. It was concluded that the contributions of various provinces to national CO2 emissions growths and their respective driving mechanisms differed considerably and changed dynamically over time. From 1996 to 2013, Shandong, Hebei, Inner Mongolia, Jiangsu and Guangdong were the top five provincial drivers behind carbon emissions growths in China, and provincial economic expansion and energy intensity reduction played dominant roles, respectively, in raising and abating carbon emissions. Across the sub-periods, the driving effects of economic activity, energy intensity and energy structure changes on carbon emissions and their evolving trends clearly varied by province. Certain provinces, such as Beijing and Shanghai, have presented significantly decreased contributions to national carbon emissions growths and even became negative contributors; while other provinces, such as Hebei, Shanxi and Anhui, have made increased contributions. Therefore, the formulation of China's emissions reduction strategies should consider both the features of provincial carbon emissions and the underlying causes shaping them, and should be adjusted in a timely manner to respond to different development stages.

Energy conservation in China’s light industry sector: Evidence from inter-factor and inter-fuel substitution

Following the impressive economic achievements in the past decades, China is faced with energy and environmental challenges. To carry out more effective and targeted energy policies, the heterogeneities of different industrial sectors are of great importance. The energy consumption of China’s light industry in 2012 was 316 million tons of coal equivalents, which is about the energy consumption of South Korea. The paper explored the substitution relationships between various input factors and fuel sources, and showed that electricity price reform is crucial for energy conservation in China’s light industry. Then, the dynamics of energy intensity change is examined by decomposing energy intensity into budget effect, substitution effect, output effect and technology advance effect. The result revealed that the substitution effect between input factors is a key driving force. However, technology progress seems to contribute very little. For future energy policy alternatives, promoting the implementation of new conservation technology and electricity price reform may be effective measures.

What drives CO2 emissions from China’s civil aviation? An exploration using a new generalized PDA method

Understanding the main drivers contributing to the increased CO2 emitted by airlines can inform carbon-reduction policies for the civil aviation sector. Production decomposition analysis (PDA) is a theoretical tool widely used to investigate the factors influencing changes in CO2 emissions. Instead of the standard constant returns to scale assumption, the study proposes a new generalized PDA method that considers the influence of changes in scale efficiency. The study used a panel data set for China's airlines during the period of 2007–2013 to conduct an empirical analysis and generate meaningful results. First, it was found that changes in Revenue Ton Kilometers is the largest factor contributing to increased civil aviation CO2 emissions. Second, changes in potential energy intensity play a dominant role in decreasing CO2 emissions for most airlines. Third, changes in production technology effects exert a relatively small influence on CO2 emissions, and the effect of scale efficiency change positively contributes to curbing CO2 emissions. Based on the PDA analysis, we propose policy implications related to civil aviation of China.

Exploring Change in China’s Carbon Intensity: A Decomposition Approach

This paper aims to explore the change of CO2 intensity in China at both national and provincial levels. To serve this purpose, we introduce a decomposition model which integrates the merits of index decomposition analysis and production-theoretical decomposition analysis. Based on the decomposition, we also estimate the potential reduction of CO2 intensity for China and its provinces. Using a panel data set including China’s 30 provinces during the period of 2006–2012, the empirical analysis is conducted and meaningful results are obtained. First, the potential energy intensity change was the dominant driving factor for the decrease of CO2 intensity, which contributed to a total reduction of 19.8%. Second, the energy efficiency change and the CO2 emission factor change also play positive roles in the CO2 intensity reduction for most provinces. Third, provinces in the western area generally showed a relatively large potential reduction in CO2 intensity, while those in the eastern area only demonstrated a small reduction.

Multiplicative structural decomposition analysis of energy and emission intensities: Some methodological issues

Structural decomposition analysis (SDA) has been a popular tool for studying a country's energy or emission performance. At the same time, there has been an increasing use of intensity indicators, such as energy consumption and carbon emissions per unit of economic output, in energy and emission performance reporting. The ratio change of an energy or emission intensity indicator can be more conveniently handled in the multiplicative form. In the context of multiplicative SDA of intensity indicators, this study investigates three specific methodological issues. The first is about sub-aggregate decomposition which provides detailed results at the sectoral/regional level to explain the observed aggregate intensity change. The second is the possible linkages between multiplicative SDA and additive SDA when studying changes in an intensity indicator over time. Arising from the convergence between SDA and index decomposition analysis (IDA) in application, the third issue is about the conceptual and empirical linkages between these two decomposition analysis techniques in the multiplicative form. A better understanding of these three issues will help to promote the use of multiplicative SDA of intensity indicators. A case study that looks into China's energy intensity change from 2007 to 2012 is presented.