Reducing Energy Intensity Research Articles

Energy equity as a major driver of energy intensity in South Asia

Energy efficiency is promoted worldwide as an important measure to address growing energy demand and reduce energy intensity of the gross domestic product and emissions of greenhouse gases and air pollutants. We analyzed aggregate and sectoral energy intensities in Bangladesh, India, Nepal, Pakistan, and Sri Lanka during 2000–2017 and decomposed the aggregate energy intensity into its four key determinants. Past energy intensity analysis methods have often used changes in factors related to only energy and economic structure and ignored energy equity factors. We show that energy equity factors (access to electricity and per capita electricity consumption) strongly influence the energy intensity of a country/region. In countries with less than 100% access to electricity, changes in energy equity factors negatively affected energy intensity while changes in energy structure and income level improved it. Energy equity is an important consideration for assessment, development and implementation of sustainable energy efficiency policies of a country.

The impact of digital economy and industrial structure distortion on Xinjiang’s energy intensity under the goal of “double carbon”

Reducing energy intensity is an important measure to achieve the goal of “double carbon” and build a beautiful Xinjiang. Selecting the panel data of 14 regions in Xinjiang from 2010 to 2020, this paper investigates the influence of digital economy and industrial structure distortion on Xinjiang’s energy intensity by using dynamic panel data model, spatial Durbin model, intermediary effect model, and panel smooth transition model. The results show that the digital economy can reduce the energy intensity, but it has regional heterogeneity. The industrial structure distortion has significantly increased Xinjiang’s energy intensity; Digital economy effectively alleviates the industrial structure distortion, thus curbing energy intensity; The influence of digital economy on Xinjiang’s energy intensity has intermediary effect and adjustment effect, and with the improvement of industrial structure distortion, the inhibitory effect of digital economy on Xinjiang’s energy intensity tends to decline. Therefore, it is necessary to speed up the development of digital economy, reduce the industrial structure distortion, strengthen environmental regulation, promote technological innovation, rationally adjust energy prices, raise the entry threshold of FDI, expand opening to the outside world, promote the synchronous scientific development of “four modernizations”, and eliminate the root causes of industrial structure distortion, so as to reduce energy intensity.

Sustainable cooling and heating in smart cities using solar energy system planning

In order to reduce waste and boost efficiency, smart cities must first and foremost eliminate trash. Effectiveness can be demonstrated in virtually any field of endeavour by saving energy, reducing energy intensity, sustaining economic growth, increasing productivity, protecting the environment, and collaborating in the battle against climate change. Because of a lack of money and technological capabilities, smart and sustainable city goals are difficult for impoverished towns to achieve. The study aims at finding the renewable energy solutions with energy efficiency and that should be technically feasible and practicable in poor communities in order to improve living conditions and overall life quality in these communities. In this paper, we use Naïve Bayes classifier to classify the input data to find the situation in which the climate can be maintained in such a way that it reduces the burden of environment in smart cities. The results of simulation shows that the Naïve Bayes classifier is effective enough in building sustainable environment with various tests.

Scenario prediction and decoupling analysis of carbon emission in Jiangsu Province, China

As a major energy consumption province in China, Jiangsu Province is a key area for carbon emission reduction in China. Grasping the future trends of carbon emission in Jiangsu Province will help to find effective ways to reduce carbon emission. This paper proposes the STIRPAT-IGWO-SVR model, including screening the carbon emission influencing factors based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, optimizing the parameters of the support vector regression (SVR) model using the gray wolf optimization (GWO) algorithm improved by the differential evolution (DE) algorithm, and sets five scenarios to predict and compare the carbon emissions of Jiangsu Province under different scenarios. In addition, the Tapio decoupling model is used to analyze the decoupling relationship of carbon emission and economic growth in each scenario. The results show that the STIRPAT-IGWO-SVR model proposed in this paper shows good performance compared with other models. For Jiangsu Province, improving the energy structure has the strongest inhibitory effect on carbon emission, stronger than reducing energy intensity, and far stronger than optimizing the industrial structure. Compared with a single plan, even if the measures are slightly weakened, the implementation of combined planning measures can more effectively control carbon emission.

The Influence of the Annealing Method on the Properties of Twice Reduced Thin Steel Sheets

Thin packaging steel sheet is currently used in the food industry, but it is also a frequently used material in other industries. Higher requirements for quality, reduction of energy and material intensity are the main factors that determine its development. The paper compares the test results of thin twice-reduced packaging sheets, which were produced by different annealing - continuous and batch method. Mechanical properties of these materials obtained by the uniaxial and biaxial tensile tests were compared. The anisotropic properties of thin steel sheets, which are demonstrated by the formation of ears on the cups, were evaluated by the deep-drawing cup test.

Energy intensity among European Union countries: the role of renewable energy, income and trade

PurposeThe International Energy Agency states that the global energy intensity must reduce by 2.9% yearly before attaining Sustainable Development Goal 7.3 by 2030. However, the European Union (EU) seeking to attain a climate-neutral EU by 2050 shall require a substantial rate of reducing energy intensity. Consequently, this study aims to investigate how (clean) renewable energy, income, trade openness, technological innovation and nonrenewable energy consumption impact energy intensity for the EU countries.Design/methodology/approachThe quantile regression, augmented mean group and causality techniques were used for analyses. Panel data for 26 EU nations over the 1990 and 2019 period was used.FindingsThe empirical evidence indicates that the variables have long-run equilibrium relationships. However, the analysis revealed that clean energy and income reduce energy intensity whiles trade, technological innovation and nonrenewable energy consumption increase energy intensity. An interactive term analysis shows that renewable energy and trade interact to reduce further, the negative effect of income on energy intensity. Causality results revealed a feedback connection between energy intensity and clean energy, income, trade liberalization as well as the interaction between income and trade liberalization. A one-way causality was obtained between energy intensity and technological innovation, nonrenewable energy consumption and the interaction between clean energy and income.Practical implicationsThe results imply that EU countries stand to gain if more resources are committed to encouraging the production and consumption of cleaner/renewable energy. Advancement in policies that support renewable energy and facilitate green growth will help reduce energy intensity for the region. Trade policies that promote lower energy consumption should be strengthened.Originality/valueThe effect of renewable energy on energy intensity is assessed. The moderating impact of renewable energy and trade openness on the income–energy intensity relationship for the EU countries is examined. Moreover, this study uses the quantile estimation technique to assess the nonlinear effect of the explanatory variables on energy intensity.

Emission reduction effects of vertical environmental regulation: Capacity transfer or energy intensity reduction? Evidence from a quasi-natural experiment in China

There is insufficient research on how to reduce the destructive effects of command-based environmental regulation through institutional design. The implementation of the National Key Monitoring Enterprises provides new evidence to assess the effects of vertical monitoring. This study integrates and matches three types of micro databases in China: industrial, pollution, and patent, and constructs firm-level panel data from 2004 to 2010. The empirical evidence shows that the policy reduces the energy use intensity of monitored enterprises by about 10.4% and sulfur dioxide emission intensity by about 23.9%. The mechanism test shows that this effect is achieved by means of energy structure optimization, process innovation, and end-of-pipe treatment, but the effect on total factor productivity is not significant. Among them, the positive impact is stronger for high-profit and emerging firms. Further, we quantify the policy-induced capacity transfer and technology spillovers from monitored enterprises to non-monitored enterprises. In terms of scale, the policy leads to a simultaneous increase in output and pollution emissions of unmonitored firms in the same industry. However, in terms of efficiency, the policy reduces the energy use intensity and pollution emission intensity of enterprises in the same industry.

The Realistic Way to the Decoupling of Carbon Dioxide Emissions from Economic Growth in China’s Service Sector

ABSTRACT Service sector development in China has increased the demand for energy and, potentially, carbon dioxide (CO2) emissions. However, there are no studies on decoupling and its determinants in China’s service sector from the point of view of technology and efficiency. A decoupling indicator based on the extended Kaya identity and production decomposition analysis was innovatively adopted to examine the relationship between service CO2 emissions and economic growth. The results show that: (1) the decoupling state of China’s service sector fluctuated from 2000 to 2008, was stable from 2008 to 2012 in the expansive coupling state, and finally stepped onto a stable state of weak decoupling from 2012 to 2019; and (2) during the sample period, the rapid expansion of the economy scale was the primary inhibiting factor for decoupling, while the decline in potential energy intensity and the progress in energy-saving technology effect was the key promoters. Furthermore, scenario analysis indicates that the possibility of decoupling energy growth from service CO2 emissions significantly relies on technological progress and efficiency improvements. China should focus on technology and efficiency, reduce energy intensity, and strengthen provincial cooperation to reduce service CO2 emissions.

Can green technology innovation alleviate the regional energy dilemma? Evidence from 30 provinces in China

High energy intensity and energy consumption structure are the main contradictions restricting China’s green economic growth. Green technology innovation is an important factor to alleviate the energy dilemma. Referring to the IPC Green Inventory launched by the World Intellectual Property Organization, the green patents of 30 provinces in China from 2004 to 2019 are screened. Based on the panel data of 30 provinces in China, this study empirically tests the impact of green technology innovation on energy intensity and energy structure by employing fixed effect model and quantile regression model. The empirical results show that green technology innovation can significantly reduce energy intensity and energy structure, and the long-term effect is obviously higher than the short-term effect. Compared with the green utility model patent representing general innovation, the green invention patent representing disruptive innovation expresses more momentous long-term and short-term effect. The sustainable effect of green technology innovation will gradually weaken with the reduction of energy intensity and energy structure. For provinces with low energy structure, the impact of green technology innovation is no longer significant. Instrumental variable method and robustness test prove that the conclusion of this study is robust. This study provides support for the government and enterprises to promote technological innovation and play a part in alleviating the energy dilemma.

Scenario of carbon dioxide (CO2) emission peaking and reduction path implication in five northwestern provinces of China by the low emissions analysis platform (LEAP) model

Achieving global peaking of carbon dioxide (CO2) emissions as early as possible is a common goal for all countries. However, CO2 emissions in the northwest China still show a rapid growth trend. Thus, we used the Low Emissions Analysis Platform (LEAP) model to build three scenarios to investigate the peak of CO2 emissions and reduction pathways in five northwestern provinces of China. The results show that: 1) the CO2 emissions of five northwestern provinces under the baseline, the policy, and the green scenarios will peak in 2035 (1663.46 × 106 tonnes), 2031 (1405.00 × 106 tonnes), and 2027 (1273.96 × 106 tonnes), respectively. 2) The CO2 emissions of all provinces, except Qinghai, will not peak before 2030 in the baseline scenario. Under the policy and green scenarios, each province will achieve the peak of CO2 emissions by 2030. 3) The CO2 emissions from agriculture, transportation, and other sectors will peak before 2030 under the baseline scenario. The CO2 emissions from construction will peak before 2030 in policy scenario. The industry and commerce will peak before 2030 in green scenario. 4) The emission reduction effect indicates that CO2 emissions from 2020 to 2040 will be reduced by 4137.70 × 106 tonnes in the policy scenario and 7201.46 × 106 tonnes in the green scenario. The industrial coal and thermal power are the sectors with the greatest potential to reduce CO2 emissions. Accelerating the restructuring of industries and energy structures and improving technologies to reduce energy intensity can promote the achievement of the peak in CO2 emissions by 2030.

Do Energy Prices and Industrialization Affect Energy Intensity? The Case of Turkey Under Structural Breaks

This study differs from other studies with the research of the energy density of Turkey, which imports more than half of its energy demand. While GDP per capita in Turkey increased by 347% in 2019 compared to 1968, energy consumption per capita increased by 324% in parallel with this. In other words, efficient use of energy in Turkey continues to be a big problem despite technological developments. Therefore, it is considered important to reduce energy intensity in Turkey, which is dependent on foreign energy. In this study, the relationship between GDP per capita, industrialization and energy prices, and energy intensity in the 1968-2019 period in the Turkish economy is investigated. The unit root process was determined by Perron (1989) and Zivot and Andrews (1992) tests, which allow structural breaks as an empirical method, and Gregory and Hansen (1996), a structural break cointegration test, was used. Empirical findings have shown that there is a long-term relationship between the variables. The Fully Modified Least Squares Method (FMOLS) estimator was used as the cointegration estimator. According to the cointegration estimation results, the increase in economic growth and energy price increases reduces energy intensity. However, higher industrialization leads to more intensive use of energy.

Energy target-based responsibility system and corporate energy efficiency: Evidence from the eleventh Five Year Plan in China

China initiated an energy target-based responsibility system for local bureaucrats in its eleventh Five Year Plan, influencing officials' promotion incentives. Leveraging manually collected provincial energy intensity targets (EIT) and a unique firm-level dataset, we investigate the effect of such a target-based responsibility system on corporate energy efficiency in China. We find that the EIT constraint has a negative effect on corporate energy efficiency. On average, a one-percentage-point increase in the EIT leads to the decline of corporate energy efficiency by 7.7%. The finding indicates that overall enhanced provincial energy efficiency was not driven by improved corporate energy efficiency but by economic restructuring in the eleventh Five Year Plan. We also show that the inhibition effect tends to be pronounced for state-owned firms, export-oriented firms, capital-intensive firms, and firms located in central regions. In the context of dual control of energy intensity reduction and amount reduction (the Dual Control Policy), this study provides timely policy implications by shedding light on the effects of such a target-based performance system on corporate energy efficiency.

Asymmetric and moderating role of industrialisation and technological innovation on energy intensity: Evidence from BRICS economies

The present research explores the effect of economic growth, technological innovation, trade openness, and industrialisation on energy intensity in the BRICS economies using a dataset from 1990 to 2019. Furthermore, this study evaluates the combined effects of industrialisation and technological innovation on energy intensity. We employed second-generation approaches such as Westerlund co-integration, method of moments quantile regression (MMQR), and panel causality. In addition, we conducted a robustness analysis by using the long-run estimators including the dynamic ordinary least square (DOLS), fully modified ordinary least square (FMOLS) and fixed effect-ordinary least square (FE-OLS). The MMQR allows for a heterogeneous income-energy intensity nexus at different conditional quantile distributions of energy intensity, which the conventional mean regressions would generally ignore. The empirical evidence from the MMQR confirms that economic growth and industrialisation contribute to higher energy intensity; meanwhile, trade openness and technological innovation decrease the energy intensity. The combined effects of industrialisation and technological innovation reduce energy intensity in the BRICS economies. The outcomes from the MMQR are supported by the DOLS, FMOLS, and FE-OLS estimators. Furthermore, the causal interaction between the energy intensity drivers is also investigated using the Dumitrescu-Hurlin panel causality tests, which reveal that industrialisation and technological innovation Granger cause energy intensity. Meanwhile, a bidirectional causal interaction between economic growth and energy intensity is found, as well as between trade openness and energy intensity. Policymakers must design industrial policies that promote technological innovation, which is the mechanism of inhibiting industrialisation.

Системные основы теории долгосрочного технико-экономического развития

Modern ideas of the theory of long-term technical and economic development and evolutionary economics are systematically criticized, since the models created on their basis do not provide predictive capabilities even in predicting deep economic cri-ses. Based on the general approach to systems theory formulated by N. Wiener, the pe-riodization of Kondratiev cycles, the provisions of the history of the economy, the histo-ry and theory of automated control systems, the ideas of technological structures are deepened. The first, second, third and fourth technological modes ensured the growth of labor productivity due to an increase in material intensity, energy intensity and capital intensity of production based on an increase in the scale of obtaining and using scientific and technical information. The improvement of production was carried out through its mechanization, the replacement of human labor by the work of machines, including the simplest control systems, which were later replaced by automatic lines. The fifth and sixth technological modes ensured the growth of labor productivity with a simultaneous reduction in material intensity, energy intensity and capital intensity of production on the basis of an increase in the scale of obtaining and using scientific and technical in-formation. The improvement of production was carried out by replacing automatic lines with flexible automated production, then by creating automated intelligently controlled automated systems.

Dynamic Effects and Regional Differences of Industrialization and Urbanization on China’s Energy Intensity under the Background of “Dual Carbon”

Based on China’s provincial panel data during 2012–2019, this paper performs an empirical analysis of the dynamic effect and regional difference of industrialization and urbanization on the energy intensity in China by separating the energy intensity into three levels including low, middle and high and using the dynamic panel data with system GMM estimation. The results show that the energy intensity will increase by 0.4298% for every 1% increase in the industrialization level on the premise of keeping other variables unchanged. For every 1% increase in the urbanization level, the energy intensity will increase by 0.5674% on average. For every 1% increase in energy intensity in the previous period, the energy intensity in that year will increase by 0.7968% on average. Moreover, there are regional differences in the effects of industrialization and urbanization on the energy intensity in areas with different energy intensities. In addition, all of the factors including the development level of the regional economy, energy price, and technological innovation have different effects on the energy intensity in China. Meanwhile, there exist the rebound effects of the technological innovation in China, and the energy price has an induced effect on the technological innovation. Undoubtedly, industrialization and urbanization jointly promote the increase in energy intensity. At the same time, the level of economic development, energy prices and technological innovation are also reasons for the differences in the energy intensity among regions. Therefore, in order to effectively reduce energy intensity while carrying out technological innovation, promoting high-quality development and increasing income, it is necessary to improve the internal quality of industrialization and urbanization, and to promote new resource-saving and environmentally friendly methods of industrialization and urbanization.

An assessment of environmental impacts and economic benefits of multiple aluminum production methods

The booming development of the aluminum industry has greatly contributed to China's economic development, but it also imposed a burden on the environment. Recent technological development has emerged various methods for aluminum production to improve production efficiency and reduce environmental impacts, while reducing energy intensity in traditional production practices can also lower emissions and remain low production costs. However, which approach that performs better in achieving economic benefits and reducing environmental impacts is unclear. This study analyzed six major aluminum production methods based on alumina production process and energy mix. Environmental parameters were derived based on life cycle assessment, and economic cost parameters were formed by building an economic benefits model. This paper then analyzed the potential of achieving economic benefits and environmental impacts reduction for each method using life cycle assessment and principal component analysis. Finally, the greenhouse gas emissions from the aluminum industry in 2030 based on scenario analysis was analyzed. We found that Bayer process-hydropower method performs the best in reducing environmental impacts and achieving economic benefits, while the sinter process-thermal power method performs the worst. The effect of reducing emissions by changing the energy mix (75%) was more significant than that by changing the alumina production process (up to 10%). Furthermore, we used scenario analysis to expand the capacity share of the Bayer process-hydropower method with optimal comprehensive benefit increased by 22.2%, the cost of electricity decreased by 313.77 CNY/t-Al, and the global warming potential was reduced by nearly 1/3. Thus, our results reveal the significant benefits of the Chinese government's push to increase the share of clean energy applications in the aluminum industry.

Drivers of global carbon emissions 1990–2014

The identification of the drivers of carbon emissions is fundamental for carbon reductions at the national level. In this study, structural decomposition analysis (SDA) is applied to 112 countries in the world from 1990 to 2014. Carbon dioxide emissions are decomposed into six driving factors: population, fuel mix, energy intensity, production structure, consumption patterns, and consumption volume. Then, the contributions of five final consumers and the six driving factors to the total carbon dioxide emissions are quantified. Based on the CO2 emissions intensity and the CO2 emissions growth rates, 112 countries are classified into 4 groups and the effects of all driving factors vary significantly among groups. Energy intensity is the most significant factor that negatively influences the total carbon emission in all groups. Fuel mix and production structure show potential positive effects on reducing carbon emissions in Group 2 (e.g. the USA, Greece, Italy) and Group 3 (e.g. Germany, the UK, Sweden), but they increase the carbon emissions in Group 1 (e.g. China) and Group 4 (e.g. Indonesia, Thailand, Pakistan). Consumption volume results in a dramatic increase in the carbon emissions in all groups, which implies that the increasing purchasing power of households and government is the most notable obstacle to carbon dioxide mitigation. Population growth accelerates the carbon emissions in developing countries in Group 4. Thus, the race between household consumption volume growth and energy intensity reduction is vital for carbon emission mitigation in Group 4.

Role of Green Financing and Eco-Innovation for Energy Efficiency in Developed Countries: Contextual Evidence for Pre- and Post-COVID-19 Era

Following the environmental concerns such as global warming, climate change, and environmental degradation, scholars and policymakers discovered energy utilization as the key factor in these issues. Therefore, economies are paying more attention to green finance and eco-innovation to reduce energy usage and enhance energy efficiency. The prime objective of this study is to explore whether the mentioned variables exhibit any influence on the energy efficiency target achievement. In this sense, the current study explores the association of green finance and eco-innovation with energy intensity in the group of seven economies from 1990 to 2020. By using panel data approaches, this study employs diagnostic tests that confirm the heterogeneous slopes and the existence of panel cross-section dependence. Also, the cointegration tests validate the existence of a long-run equilibrium relationship between the variables. Based on the asymmetric distribution of the data, this study employs the method of moments quantile regression. The empirical results reveal that green finance and eco-innovation significantly reduce energy intensity across the selected quantiles. Control variables such as urban growth and trade openness also adversely affect energy intensity. However, economic growth is the only significant factor that enhances energy intensity. The results are robust as validated by the panel quantile regression and the Granger panel heterogenous causality test. Based on the findings, this study recommends that green finance be promoted and environmental-related technology innovation be encouraged to achieve the goal of energy efficiency in developed economies. This study also provides additional policies appropriate for environmental recovery.

Enhancing energy efficiency of Indian industries: Effectiveness of PAT scheme

India adopted Cap and Trade in energy intensity via a scheme called Perform Achieve and Trade (PAT) to improve the energy efficiency of energy intensive industries through target setting and allowing trade in energy saving certificates. The first cycle ran from April 2012 to March 2015, where the Bureau of Energy Efficiency assigned targets to identified firms in eight industrial sectors. This paper aims to examine the effectiveness of the PAT scheme in inducing firms to reduce energy intensity in the Cement, Fertilizer, and Pulp and Paper Industries. Using a difference-in-differences model, we do a firm level analysis for three industries over an 11 year period (2005 to 2015) and estimate the average treatment effect of the PAT scheme on the firms that were assigned the targets. We find that the PAT scheme improved the energy intensity of the designated firms by 2.7 percent and 1.6 percent in the cement and the fertilizer industry, respectively. The associated CO2 emission savings was about 22.5 million metric tons in the cement industry. However, the scheme was not effective in causing an additional decline in energy intensity in the pulp and paper sector. Another robust result is that the energy intensity of firms is declining in research and development investment.

Assessing the impact of the carbon market on the improvement of China's energy and carbon emission performance

All countries are actively taking measures to address carbon neutrality. As a policy measure for China to respond to climate change, the carbon market is necessary and significant for assessing its impact on energy and the environment. This study uses data from 30 provinces in China from 2000 to 2017 and employs a difference-in-differences model to estimate the impact of the carbon market on energy and environmental performance. The empirical results show that the carbon market has significantly improved energy and environmental performance, as shown by a 14.14% reduction in energy intensity and an increase in carbon emission efficiency by 4.21%; a series of robustness test results show that the carbon market only has long-term stability characteristics in reducing energy intensity, but is unstable in improving emission efficiency; market reform and technological innovation have played a significant intermediary role in the impact of the carbon market on energy and environmental performance; and the carbon market has significant heterogeneity effects; only Beijing, Chongqing, and Hubei have significant energy intensity reduction effects. Finally, the results revealed that the carbon market is beneficial for improving energy and environmental performance, which provides a universal reference for countries worldwide to implement carbon emission reduction policies.