Decline In Energy Intensity Research Articles

Energy Intensity Forecasting Models for Manufacturing Industries of “Catching Up” Economies: Lithuanian Case

The objective of this research was to construct energy intensity forecasting models for key manufacturing industries, with a particular focus on “catching up” European economies. Future energy intensity values serve as the foundation for energy demand forecasts, which are essential inputs for the analysis of countries’ decarbonisation scenarios. The Lithuanian case is analysed in the context of its efforts to reach the economic development level of the most advanced European Union (EU) countries. The scientific literature and energy policy analysis, interdependence (correlation and regression), tendency and case analysis, logical economic reasoning, and graphical representation methods have been applied. The energy intensity forecasts until 2050 were based on historical statistical data of value added and final energy consumption of EU countries from 2000 to 2021. The analysis of historical trends revealed a remarkable decrease in industrial energy intensity in most EU countries, including Lithuania. Given the rapid pace of decline in historical energy intensity, the values observed in individual Lithuanian industries have already reached levels comparable to the most economically advanced EU countries. Four econometric trendlines were employed to construct forecasting models for energy intensity. The results for Lithuania demonstrated that the selected trendlines exhibited a high degree of fit with historical energy intensity data from the EU, as evidenced by their R2 values. Furthermore, the forecasts were shown to be highly accurate, with their MAPEs remaining below 10% in most cases. Nevertheless, the logarithmic trendline was found to be the most accurate for forecasting energy intensity in total manufacturing (MAPE = 4.0%), non-metallic minerals (MAPE = 3.5%), and food, beverages, and tobacco (MAPE = 4.1%) industries, with the exponential trendline in the chemical industry (MAPE = 8.7%) and the moving average in the total manufacturing industry (MAPE = 4.0%), food industries (MAPE = 4.0%), and remaining aggregate industries (MAPE = 14.5%). It is forecasted that energy intensity could decline by 8 to 16% to 1.10–1.20 kWh/EUR in Lithuania’s manufacturing industries by 2050.

MACROECONOMIC STRATEGY FOR THE RESTORATION OF THE GAS DISTRIBUTION MARKET ON THE EXAMPLE OF THE MARSHALL PLAN

Ukraine suffered giant human, material, and resource losses from the war. This led to a change in the Strategy and Tactics for the future allocation of resources and strategies for the macroeconomic recovery of the energy sector. A sharp decline in Ukraine's energy intensity in all sectors of the economy resulted in a general decline in the country's gross domestic product. As a result of the military intervention, Ukraine's energy sector is characterized by high import dependence, low energy efficiency, and financial illiquidity. In addition, the subsequent market transformation has led to chaotic pricing of gas resources and utilities and low household income. The article discusses the main aspects of the famous Marshall Plan for the post-war reconstruction of the Ukrainian economic and energy systems. The study pays special attention to the macroeconomic Strategy for the energy sector's recovery. The article considers the existing developments of researchers and practitioners in analyzing the impact of the Marshall Plan on the recovery of European countries after World War II. When implementing this plan in the context of current national realities, the author outlines certain aspects that could be taken into account in the necessary implementation of a standard European policy of Ukraine's reconstruction, intensification of the business legal and competitive environment, and implementation of integrity issues about the focus and priority of individual industries and areas. It is particularly urgent to address the combination of renewable features in the context of European environmental, climate, and economic policies. Considering Ukraine's energy balance in wartime, the existing Energy Strategy should summarize the growth that will be implemented slowly. Gas resources will continue to play an essential role in domestic energy consumption. Therefore, in analyzing existing approaches, trends, and our beliefs, we modeled a possible macroeconomic Strategy for restoring Ukraine's gas distribution sector in the postwar period based on approaches specific to the Marshall Plan. The macroeconomic Strategy for restoring gas distribution companies in postwar Ukraine is a complex concept and consists of several government measures. This Strategy should consider the Marshall Plan, which has already positively affected some countries after World War II. The basis of this recovery plan is access to fuel and energy resources in a technically reliable, safe, cost-effective, and environmentally acceptable manner in the interests of consumers and society. Ukraine suffered giant human, material, and resource losses from the war. This has led to a change in the Strategy and Tactics for the future allocation of resources and macroeconomic recovery strategies for the energy sector. A sharp decline in Ukraine's energy intensity in all sectors of the economy resulted in a general decline in the country's gross domestic product. As a result of the military intervention, Ukraine's energy sector is characterized by high import dependence, low energy efficiency, and financial illiquidity. In addition, the resulting market transformation has led to chaotic pricing for gas resources and utilities.

Carbon Emissions from Energy Use in India: Decomposition Analysis

To become the fastest-growing large economy in the world, India has set a target growth rate of 9%, reaching an economy of $5 trillion by 2024-25. It is an immense challenge to meet the growth target and keep the CO2 emissions under control. The present paper aims to discover the determinants for explaining CO2 emissions in India by conducting a complete decomposition analysis, where the residuals are fully distributed to the determinants for the country from 1990-2018. The analysis reveals that the biggest contributor to the rise in CO2 emissions in India is the expansion of the economy (scale effect). The intensity of CO2 and the change in the composition of the economy, which nearly move in tandem, also contribute to the rise in CO2 emissions, although more slowly. A declining energy intensity of the Indian economy is responsible for a considerable reduction in CO2 emissions. As a typical result for an upcoming economy, this paper did not find evidence for an environmental Kuznets curve. This implies that continued economic growth will lead to increased CO2 emissions.

Drivers of global energy export dependency: A decomposition analysis

Exploring energy export dependency under the carbon neutrality target is crucial for energy security and low-carbon transition. Currently, few studies have examined drivers of energy export dependency; furthermore, most of them failed to capture the impact of technology on energy change and were unable to explain the causal factors of energy intensity decline. This study analyzed the trends and drivers of energy export dependency in 40 major countries from 2000 to 2019 through a decomposition approach, and explained the decline of energy intensity caused by technological progress. The empirical results indicate that energy prices and energy export importance are the key drivers of the increase in energy export dependency in OECD countries, while technological progress can effectively reduce the energy export dependency of non-OECD countries by decreasing energy intensity. In addition, OECD countries pay attention to capital-energy substitution capacity, while non-OECD countries attach importance to the improvement of technical efficiency. These findings provide a scientific reference for energy transition and sustainable development in various countries.

Inconsistent definitions of GDP: Implications for estimates of decoupling

Efforts to assess the possibilities for decoupling economic growth from resource use and negative environmental impacts have examined their historical relationship, with varying and inconclusive results. This paper shows that ambiguities in the historical measurement arising from definitional changes to GDP are sufficiently large to affect the results. I review the history of structural revisions to GDP using the example of the United States, and on international comparisons of purchasing power parity, and compare decoupling results using GDP vintages reported between 1994 and 2021 for most countries. Between vintages, 10–15% of countries switch between relative decoupling and recoupling from energy or materials on decadal intervals, and up to as many countries as decouple absolutely in an older vintage stop or newly start absolutely decoupling in the newer vintage. GDP vintages also affect environmental Kuznets curve results on absolute decoupling in Grossman and Krueger's seminal paper and accelerate the International Energy Agency's annual global decline in energy intensity by up to −0.2 percentage points. Inconsistencies in economic measurement introduce ambiguity into historical decoupling evidence and model projections into the future. To advance debate, rigorous reporting and sharing of data vintage for subsequent comparison and replication are urgently needed.

The potential role of renewable power penetration in energy intensity reduction: Evidence from the Chinese provincial electricity sector

This study analyzed the role of renewable power penetration in energy intensity reduction in the provincial electricity sector of China over the period 2006–2016. We determined the net and total effects of renewable power penetration for each provincial electricity sector and separated out the driving forces of the net effect of renewable power penetration using an estimated translog cost function and the difference in difference method. This enabled us to clarify the reasons for the decline in energy intensity caused by renewable power penetration. We found that compared with renewable power penetration, thermal efficiency played a major role in the declining energy intensity, but the potential total role of renewable power penetration cannot be ignored, especially for the initial penetration effect of renewable power. Most of the decline in energy intensity caused by renewable power penetration during 2006–2016 could be attributed to energy price and capital substitution. Our findings have important implications for the Chinese government in the future development of renewable energy and energy efficiency policies.

Pathways to net-zero emissions from China's transportation industry: Considering alternative fuels

In the context of the national ‘dual carbon’ strategy, expediting the green and low-carbon transformation has become a focal point across various industries. The challenge of reducing carbon dioxide (CO2) emissions in the transportation sector is exceptionally formidable, given its heavy reliance on energy. Swift progress within this industry unavoidably entails heightened energy consumption, consequently exacerbating CO2 emissions within the sector. This article aims to identify an attainable, comprehensive pathway towards achieving net-zero emissions within the industry. The study reveals that strict control over the growth rate of the transportation industry's total output value and significant promotion of energy intensity decline can lead to a substantial 44% reduction in CO2 emissions by 2050, equivalent to approximately 2.17 Gt and 2.15 Gt of CO2eq. Successfully achieving net-zero emissions necessitates the replacement of fossil fuels with alternative transportation fuels in the range of 3.34 EJ to 15.22 EJ, accompanied by technological advancements to drive cost reductions. Additionally, considering non-CO2 radiation forcing, each scenario requires carbon dioxide removal (CDR) ranging from 0.17 Gt to 2.67 Gt for achieving net-zero emissions. This article comprehensively examines key factors including economy, energy, and technology, conducting an in-depth investigation into the viable pathway to achieve net-zero emissions within the industry. The findings presented herein offer valuable insights into facilitating the industry's low-carbon development and supporting the attainment of the national ‘dual carbon’ goal.

Impact of Energy Productivity and Industrial Structural Change on Energy Intensity in China: Analysis Based on Provincial Panel Data

Since 2000, China’s energy intensity has shown a fluctuating downward trend. Most existing studies have attributed the decline to technological progress, and only a few studies have recognized the role of industrial structure change. In this paper, a multi-region and multi-sector CGE (computable general equilibrium) model and a numerical simulation method are used to study how technological progress and structural transformation affected the energy intensity of 30 provincial-level regions in China from 2000 to 2019. The results show the following points. (1) The contribution of technological progress to the decline in energy intensity was the highest in the central region, followed by the western region, and was the lowest in the eastern region. (2) The progress of energy technology in the agriculture and industry sectors promoted the transition of energy consumption to the service sector, thereby reducing the overall energy intensity. This effect was the strongest in the eastern region, followed by the central region, and was the weakest in the western region. (3) The progress of energy technology in the service industry promoted the transition of energy consumption to industry and agriculture, thereby enhancing the energy intensity, and this effect was the strongest in the eastern region, followed by the western region, and the weakest in the central region. The conclusion of this paper provides a theoretical basis for realizing regional carbon peaking in sequence in China.

China's carbon emissions peaking pathway in the post-COVID-19 era.

Several countries have weakened the carbon emission objectives to immediately revive the economy in the post-COVID-19 era. Therefore, it is a challenge worth addressing to readjust the economic development and carbon emissions after the COVID-19 pandemic. From the perspective of China's carbon emissions, this study shapes a multi-objective dynamic optimization model based on the material capital input and R&D support aspects. The proposed model imitates China's economic development, energy consumption, and carbon dioxide (CO2) emissions. The model provides theoretical suggestion for the government to revive economic development and reduce carbon emissions. In addition, this research paper compares the evolutionary path of carbon peak under the two scenarios. The first scenario requires maintaining the pre-epidemic development state and pace of carbon emission reduction, referred to as the baseline scenario (BS). The second scenario is termed the optimal scenario (OS) based on the model calculation. The study findings exhibit that China is not able to accomplish the 2030 CO2 emission peak objective, under the BS. However, China under the OS shall expectedly accomplish the 2030 carbon peak objective ahead of schedule, while the peak CO2 emissions shall be around 11.28 billion tons. Reportedly, at least 788 million tons of CO2 reduction contrasted with the BS. Furthermore, there is an 80.35% decline in energy intensity as compared to 2005. Consequently, the study results contribute theoretical guidance for the "green recovery" of China's economy and the adjustment of carbon emission reduction's path after the COVID-19 epidemic. Consistent with this, the research method also contributes to the theoretical research on carbon emissions at the national level while extending a new research perspective for the economic and environmental fields.

How is energy intensity affected by industrialisation, trade openness and financial development? A dynamic analysis for the panel of newly industrialized countries

Exploring the factors that affect energy intensity is a worthy research topic because a decline of energy intensity lowers greenhouse gas emissions and increases energy security. Therefore, using the World Bank data from 2000 to 2020, this study examined how industrialisation, trade openness, financial development, and urbanisation affected energy intensity in 12 Newly Industrialized Countries (NICs). We used panel autoregressive distributed lag/pooled mean group (ARDL/PMG), cross-sectional ARDL (CS-ARDL), and fully modified ordinary least squares (FMOLS) to determine the long- and short-run effects of explanatory variables on the dependent variable, energy intensity. All variables are found stationary after the unit root test and cointegration test confirms that variables are linked in the long run. Panel ARDL/PMG and CS-ARDL results show that industrialisation increases energy intensity in the long and short runs. These tests also show that financial development increases energy intensity over time but not immediately. Trade openness decreases energy intensity in the long run but not in the short run. Urbanisation has negligible effects. Dumitrescu and Hurlin (2012) Granger causality test result shows that energy intensity causes trade openness. The test also shows two-way causality between industrialisation, financial development, and energy intensity. Results-driven policy recommendations, such as investment in efficient and environmentally friendly technologies, and facilitation of trade openness, are made following the conclusion.

Decomposition analysis on factors affecting electricity substitution in Guangdong province, China

AbstractElectricity substitution is an effective measure for reducing pollutant emissions and promoting the consumption of renewable energy. The current research lacks a quantitative analysis method for the factors affecting regional electricity substitution. This article proposes a decomposition model of the factors affecting electricity substitution based on Logarithmic Mean Divisia Index method to expand the depth and breadth of electricity substitution. Results show that: (1) Macro‐level electricity substitution in Guangdong province develops steadily, with 1694.93 × 108 kWh of total electricity substitution quantity during the period 2006–2020. The electricity substitution quantity in production sector accounts for 83.92% of the total, which is much larger than that in household sector. (2) Sustained improvement of labour productivity gives the largest contribution (3592.32 × 108 kWh) to the increase of electricity substitution in production sector during the period 2006–2020. Living standard effect has the largest contribution (452.21 × 108 kWh) to the increase of electricity substitution in household sector during the period 2006–2020. Electrification level effect and population effect have significant impact on electricity substitution development, while industrial structure has little impact on electricity substitution. (3) Energy intensity effect and energy consumption growth effect negatively influence electricity substitution in Guangdong province. The decline of energy intensity in the production sector has driven the decrease of electricity substitution quantity, contributing −2540.36 × 108 kWh to electricity substitution during the period 2006–2020. Policy implications like continuously promoting breakthroughs in electricity substitution technologies, improvement of electrification rate in the sectors with potential for substitution, and improvement the price mechanism for fossil fuels and electricity can promote the deepening development of electricity substitution and the realisation of the carbon neutrality goal.

An empirical analysis of the nexus between digital financial inclusion, industrial structure distortion, and China's energy intensity.

Stimulating the shift to low-carbon energy and decreasing energy intensity are crucial strategies for green growth. Reducing energy intensity is an important measure to achieve the goal of "double carbon" and building a beautiful new China. Based on the provincial panel data of China from 2011 to 2020, this paper empirically tests the relationship among digital financial inclusion, industrial structure distortion, and energy intensity by using the spatial Durbin model and the intermediary effect method. The results show that the development of digital financial inclusion can promote the decline of energy intensity, and industrial structure distortion has a partial intermediary effect in the relationship between digital financial inclusion and energy intensity. Because of this, it is important to speed up the development of digital financial inclusion, increase the innovation of digital financial inclusion products and services, strengthen the supervision of digital financial inclusion, and reduce the distortion of the industrial structure so that digital finance can play its full role in reducing energy intensity.

Outward foreign direct investment and energy intensity: evidence from the listed companies in China.

Since 2005, China's outward foreign direct investment (OFDI) has increased year by year, which corresponds to the continuous decline of energy intensity. But there is limited literature concerning their relationship nowadays. To answer whether or not OFDI can reduce energy intensity, this paper selects data from 29 provinces in China from 2006 to 2015 and establishes a fixed-effects model to analyze the relationship. Further, this paper divides OFDI into technology-intensive ones and non-technology-intensive ones in order to distinguish the impact of outward foreign direct investment from different types of enterprises on the energy intensity. Combined with the micro-data of A-share listed companies in Shanghai and Shenzhen stock exchanges, we find that OFDI plays a significant role in reducing the energy intensity in China, and OFDI of high-technology-intensive enterprises has a greater effect on the decrease of energy intensity than that of low-technology-intensive enterprises. This paper classifies OFDI from the perspective of enterprise technology intensity, which enriches the existing research results in the field of international cooperation and energy intensity. It also overcomes the limitations of previous literature data and provides new evidence for encouraging high-tech enterprises to strengthen international cooperation from a micro level.

Low-carbon economic growth in Chinese cities: a case study in Shenzhen city.

Low-carbon economic growth in cities is important for reduction of carbon emissions in China. As the best practice city in China, Shenzhen city has experienced rapid economic growth with low carbon emissions. The study aims to evaluate the performance of Chinese cities on low-carbon economic growth through the case study of Shenzhen city. The study carries out the Tapio decoupling model for analyzing decoupling state, and uses the Kaya-Logarithmic Mean Divisia Index decomposition model to determine the main driving factors of carbon emissions in Shenzhen. Results indicate that Shenzhen has greatly decoupled carbon emissions with economic growth. The analysis of driving factors of carbon emission shows that the declining energy intensity and the upgrading industrial structure effectively hamper the increase of carbon emissions in Shenzhen. The decline in energy intensity in Shenzhen may come from an improvement of production efficiency of the industries. However, the irrational energy consumption structure, fast-growing economic output, and industry scale are hampering the low carbon emissions of Shenzhen. All estimated industries are highly dependent on coal and oil although some industries have slightly increased their proportion of clean energy consumption. Pursuing more clean energy consumption in the industry will be a key development strategy for reducing emissions in the future. Moreover, as Shenzhen is a fast-growing city, the increasing economic output and industry scale are inevitable. Changing people's way of living could also help in reducing carbon emissions in cities.

Characteristics and driving factors of carbon emissions in China

Many regions or countries seek to transition to a low-carbon economy, but there is ambiguity about how carbon emissions change with economic growth. This paper captures characteristics of carbon emissions in China using the Tapio Method. To detect driving factors of carbon emissions in economic growth, we adopt the Log-Mean Divisia Index decomposition method. The results of the paper are as follows: (1) Economic growth in most regions of China has outpaced the growth rate of carbon emissions, showing the characteristics of decoupling. (2) Metropolitan cities have a greater impact on the level of decoupling in neighboring provinces and municipalities. (3) The decoupling of carbon emissions from economic growth is caused by declining energy intensity in China. (4) The energy mix and industrial structure have little impact on the growth rate of carbon emissions. In addition, some policy implications are summarized according to the findings of this paper.

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.

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.

Decoupling analysis on China's civil aviation carbon emissions from transportation revenue: A three-dimension decomposition framework

With the rapid development of China's civil aviation, carbon emissions have brought severe environmental problems. Understanding the internal dynamic relationship between carbon emission and air transportation development is conducive for the industry to realize green development more effectively. Based on the Tapio decoupling theory, this study investigated the decoupling status between civil aviation carbon dioxide (CO2) emissions and transportation revenue. A three-dimension decomposition model was constructed and applied to further explore the influencing factors of various decoupling status. The empirical study resulted in three key findings. Firstly, there is still much room for efficiency improvement in civil aviation overall transportation process. Compared with the external economic environment and the production process, the improvement of civil aviation operation process needs to be further strengthened. Secondly, the civil aviation carbon emission decoupling status was dominated by negative decoupling. The growth of air transportation revenue still deeply depends on the fossil fuel consumption. Thirdly, the decline of potential energy intensity significantly propels the decoupling progress of China's civil aviation; meanwhile, external economic environment and potential transportation intensity are key inhibitors of the decoupling development.

Decomposition and Decoupling of Regional Carbon Emissions

This paper applies the logarithmic mean divisia index to explore the decomposition and decoupling of sectoral carbon emissions across four provinces in the Yangtze River Delta (YRD). The results show that (1) the YRD experienced a significant upward trend in sectoral carbon emissions, among which Anhui and Jiangsu provinces experienced the largest increase in carbon emissions. (2) Anhui and Jiangsu showed expansive coupling or weak decoupling in the “10th Five-Year Plan (FYP)”, and Shanghai and Zhejiang indicated weak decoupling and strong decoupling in the “11th FYP”, “12th FYP”, and “13th FYP”. These observations show that the YRD has been transforming its economic growth patterns and increasingly concentrating on the green economy. (3) Shanghai was the most progressive in decoupling. An inspection of decoupling indicators reveals that declining energy intensity contributed most to decoupling, whereas the population scale was less important. In addition, the industry structure and energy structure varied among the provinces.

Decomposition analysis of carbon emissions: Considering China’s energy efficiency

Carbon emissions reduction has become a public concern since Paris Climate Conference in 2015, while energy efficiency improvements and the development of clean energy are crucial to carbon reduction. To investigate carbon dioxide emissions in China at different phases in 2000–2016, this research adopts the logarithmic mean Divisia index (LMDI) technique to study four drivers: population, economic development level, energy intensity, and carbon emission intensity. The results show that: (1) The rate of increase in CO2 emissions has decreased from an average of 10.6% in 2000–2011 to 0.79% in 2011–2016; (2) Declining energy intensity (-39.89%) is the largest contributor to China’s carbon reduction among the four drivers in 2012–2016, followed by declining carbon emission intensity (-9%); (3) With rising energy efficiency and increased use of clean energy, China is transitioning to a sustainable economy. More innovative green technologies should be employed to enhance the efficiency of energy use and optimize energy structure to combat climate change.