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Global challenges, such as the COVID‐19 impacts, climate crisis, and geopolitical tensions, have prompted economic transformations. These issues have led to macroeconomic data assuming non‐normal distributions, necessitating a nonlinear analytical approach. As a result, this study unveils the influence of energy intensity, renewable energy, economic growth, and financial development on carbon dioxide emissions in Iceland from 1995Q1 to 2020Q4 using the Quantile‐on‐Quantile Kernel‐Based Regularized Least Squares (QQKRLS) and Wavelets Quantile Correlation (WQC) methods. The QQKRLS results showed that energy intensity, renewable energy, and economic growth are negatively associated with carbon dioxide emissions across various quantiles, while financial development is positively linked with carbon dioxide emissions. Furthermore, the WQC outcomes confirm the results of the QQKRLS. In addition, in the short and medium term, financial development negatively affects carbon dioxide emissions across various quantiles, while in the long term, financial development positively influences carbon dioxide emissions. In light of the results gleaned from this study, Iceland should continue on its path of renewable energy investments, create policies that will completely decouple economic growth from carbon dioxide emissions, and ensure that the development of the financial system is funding clean energy activities. This provides a roadmap for sustainable economic and environmental development. [ABSTRACT FROM AUTHOR]

Turkey occupies a significant position in the global economy and plans to achieve net‐zero emissions by 2053. Thus, this study uses the non–linear ARDL (NARDL) framework to analyze the effect of energy intensity (EINT), renewable energy (REN), and economic growth (GDP) on CO2 in Turkey from 1970 to 2021. The results are as follows: (i) The variables have a long‐term link; (ii) Over the long‐term, a positive (negative) change in EINT increases (decreases) CO2; a positive (negative) change in REN decreases (increases) CO2; and a positive (negative) change in GDP increases (decreases) CO2. (iii) In the short‐run, an EINT and GDP negative change decreases CO2. In light of these findings, Turkish policymakers should set energy efficiency standards and support clean energy initiatives, which are some of the practical ways of lowering CO2 and addressing other climate challenges. [ABSTRACT FROM AUTHOR]

The relationship between energy consumption, environmental pollution, and economic growth has been the subject of intense research over the past few decades. However, empirical evidence remains scarce and with mixed results. This paper throws a new light on the nonlinear impact of environmental degradation on economic growth depending on the level of energy intensity. This study provides an original approach in the context of Malaysia by utilizing an innovative threshold regression approach suggested by Hansen (Econometrica 68(3):575–603, 2000), which allows the data to endogenously divided into two regimes with an exogenous threshold variable. We find strong evidence that environmental degradation has a nonlinear effect on economic growth in Malaysia. In particular, CO2 has a negative effect on growth, but only after the primary energy intensity reaches a threshold level of 91.33 tons of oil equivalent (TOE)/GDP and the final energy intensity reaches 51.56 TOE/GDP, respectively. Our results are robust in terms of ecological footprint. Several policy implications are highlighted which aim to encourage sustainable energy use for sustainable growth in the future. [ABSTRACT FROM AUTHOR]

China plans to arrive at its peak in the emissions of carbon dioxide and reach carbon neutrality by 2030 and 2060, respectively. What role does internet technology, as a key twenty-first-century technology, play in China's achievement of its two carbon goals? Based on datasets about Chinese prefecture-level cities collected mainly from statistical reports released by the China Internet Network Information Center (CINIC), China City Statistical Yearbook, and China Energy Statistical Yearbook in 2006–2019, this paper empirically examines how the development of the internet influencing energy efficiency. This paper uses the policy of "network power nation" strategy and "internet plus" (NPNIP) as a policy impact to construct a continuous difference-in-difference (DID) model for an empirical investigation, and use a mediating effect analysis to test the transmission mechanism involved in industrial structure upgrading, technological innovation, and economic agglomeration. Empirical findings show that energy efficiency is improved by the development of internet. But this result has significant regional heterogeneity. Internet development can significantly reduce energy intensity in the eastern region and mature resource-based cities, but not the central and western regions and other resource-based cities. The mediating effect results show that the internet improves energy efficiency in three ways: upgrading industrial structure, stimulating technological innovation, and economic agglomeration. The empirical findings in this paper lead to many policy recommendation, including strengthening the formation of new infrastructure, deepening the organic integration of the internet across industries, and exploring the legal regulations on internet technology in specific application areas. [ABSTRACT FROM AUTHOR]

Climatic change and environmental degradation have become a worldwide discourse. Green innovation is commonly viewed as a means of lowering environmental pollution in the era of climate change. Considering this, the primary purpose of this study is to investigate the effects of environmental technology (ET) on CO2 emissions by controlling Saudi Arabia's ICT use, energy use, energy intensity, and financial development. It uses a quantile-based multiple-threshold "nonlinear autoregressive distributed lag (NARDL)" estimation utilizing data from 1990 to 2020. It also conducts the ARDL and NARDL estimation techniques simultaneously for comparative outcomes. The Toda–Yamamoto (T-Y) causality assessment also crosschecks the primary multiple-threshold NARDL estimates. The outcomes reveal that ET promotes environmental pollution due to its low scale compared to the Kingdom's technological base. ICT improves environmental quality, and energy consumption deteriorates it. All three estimation techniques confirm these findings. The multiple-threshold NARDL estimation appears robust and reveals damaging impacts of energy intensity and financial development on emissions. The T-Y causality assessment also authenticates the primary estimation outcomes. The outcomes have important implications for policymakers to focus on enhancing patents for ET, raising ICT diffusion, reducing energy intensity through generating more renewable energies, expanding financial support for ICT and green investments, and ensuring a sustainable environment. [ABSTRACT FROM AUTHOR]

Studying the impact of global value chains' (GVCs) participation degrees on carbon emission transfer through international trade (CTIT) in Belt and Road Initiative (BRI) economies is of great significance because these economies are significant participants of GVCs and international trade. The current study, through the inter-regional Input-Output table, calculated the GVCs' participation degrees (forward and backward participation) and CTIT (carbon emission transfer through export (ETET) and emission transfer through import [ETIT] trade) of 27 BRI economies from 2005 to 2018 and investigated the impact of the GVCs on CTIT. Several test results illustrated that endogenous issues did not affect the robustness of study discussions. The study articulates appropriate environmental governance policies that could realise emissions reduction goals. Significant results are (a) participation degree in GVCs increases the CTIT in BRI; (b) energy intensity, energy structure, final demand and secondary industry escalate CTIT; (c) the optimisations of participation degree in GVCs, energy intensity development, industrial structure optimisation and increased awareness of emission lessening among the BRI community could compensate for the growth in CTIT from the constant deepening of GVCs. This study delivers a comprehensive insight into understanding the driving forces that cause the changes in CTIT from the GVCs' perspective. JEL Codes: F02, F18, Q56 [ABSTRACT FROM AUTHOR]

Sustainable development is a global focal point. This study aims to analyze the relationship between energy intensity and green innovation using panel data from 285 Chinese cities spanning from 2003 to 2019. The novel element of this research is the first-time exploration of green innovation through the lens of local industry attributes. It explains the impact of energy intensity on the development of green innovation. By employing a two-way fixed-effect model, the regression analysis reveals that higher energy intensity in cities negatively influences green innovation. Robustness and mechanism tests indicate that in regions with higher energy intensity, governments issue more policies to encourage enterprises and research institutions to pursue green innovation. However, these regions have developed significant path dependence, and local enterprises are reluctant to increase green investment even when facing stringent regulations. Heterogeneity analysis proves that cities with higher levels of digitalization, R&D investment, urbanization, and per capita GDP exhibit an increase in green innovation. The research and findings of this study are of significant importance for policy and strategy formulation, allowing governments and enterprises to develop targeted economic strategies to improve energy efficiency and promote green innovation, thereby achieving sustainable development goals. Potential limitations include data quality, and some key information is difficult to obtain from public sources due to confidentiality, which may result in limitations and biases in the results. [ABSTRACT FROM AUTHOR]

As a comprehensive and systematic approach to innovation, green innovation has become an important tool for reducing haze and carbon intensity. Based on balanced panel data at the city level in China, we use the two-way fixed-effects model to explore the impact of urban green innovation on haze pollution and carbon emission intensity. The conclusions are as follows: 1) The influence of green innovation on carbon emissions intensity and haze pollution exhibits a significant inverted U-shaped relationship. 2) We explore the mediating channels through which green innovation affects carbon emissions intensity and haze pollution. Specifically, the inverted U-shaped impacts of green innovation on energy intensity and resource dependence. 3) The inverted U-shaped relationship between green innovation and carbon emissions intensity holds for both resource-based and non-resource-based cities. 4) The U-shaped relationships, whether regarding carbon emissions intensity or haze pollution, are only applicable to non-environmental priority cities. This paper offers valuable insights for the formulation of more effective environmental management measures by governments. [ABSTRACT FROM AUTHOR]

There is a growing emphasis on fostering green growth and lowering carbon emissions in order to achieve sustainable economic development. This study uses the Tapio decoupling model and analyzes the factors influencing changes in carbon emissions from manufacturing in India utilizing the log mean Divisia index (LMDI) techniques. Furthermore, the nexus between carbon emission intensity, information and communication technology (ICT), total factor productivity (TFP), skill, and energy intensity has been analyzed using the system-GMM approach. It is based on the plant-level Annual Survey of Industries (ASI) datasets for the organized manufacturing sector of India from 2001 to 2002 to 2019 2020 for the major 21 Indian states/UT. The findings reflect the presence of weak decoupling in the manufacturing sector both at the aggregate level and in states. This indicates that both output and emissions are increasing; however, output growth surpasses emission growth, which signifies an effort to transition towards more environmentally friendly production methods and enhanced energy efficiency. The output and population effect are found to be leading factors in carbon emissions, while energy intensity is found to be reducing the effect. Further, the system-GMM estimates show that ICT and energy intensity positively affect total factor productivity, while with an increase in carbon emission intensity, productivity declines. The study confirms the existence of an inverted N-shaped Kuznets curve in the sector. This present study will contribute to formulating energy and environmental strategies to reduce emissions and promote adopting cleaner energy sources. These efforts will facilitate the attainment of carbon neutrality and enhance energy efficiency within the sector. [ABSTRACT FROM AUTHOR]

In this article, we explore the relationships between economic growth and energy intensity in Bahrain, and we analyse how energy intensity, population, and other macroeconomic variables are associated with each in the short and long run. In the empirical section we use data span from 1980 to 2019 and we perform a vector error correction model and cointegration technique to detect causality between the variables used in the model. The main findings of this article show that economic growth, population and FDI increased energy intensity in Bahrain in the short run. Therefore, an urgent need to be embedded in the sustainable energy action plan to limit the harmful effects of economic activity on the environmental quality in Bahrain and to ensure environmental sustainability. [ABSTRACT FROM AUTHOR]

This article discusses the impact of rail market liberalization on the energy intensity of rail in relation to the export of goods, as well as the identification of multidimensional cause-and-effect relationships between rail energy intensity and the importing country's economic condition, transport performance, and transport distance. Three research questions were formulated: (1) Does the liberalization of the EU transport market and the implementation of a sustainable transport policy contribute to minimizing the energy consumption of rail transport? (2) Does the pursuit of economic growth allow for reducing the energy intensity of goods exported by rail transport in global trade? (3) Is there a justified paradigm for shifting long-distance freight transport from roads to rail? This study concerned 21 directions of the export of goods transported by rail from Poland to partner countries (worldwide) in 2010–2020. A panel model of rail transport energy consumption with random effects was constructed. As a result of rail market liberalization, the export of goods transported by rail across great distances occurs without harming economic development and leads to a reduction in energy intensity. On this basis, key strategies were formulated to promote rail transport in reducing the energy intensity of the transport sector. The authors filled the research gap by identifying the relationship between the energy intensity of exports of goods by rail transport in value terms, depending on the European transport market's liberalization process, the importing countries' economic situation, transport volume, and distance. The presented approach is innovative and can be adapted to the analysis of other modes of transport, including road transport, and other countries (and their structure and export directions). [ABSTRACT FROM AUTHOR]

We empirically evaluate the effect of China's Belt and Road Initiative (BRI) on the energy intensity of countries along the route. Furthermore, we decompose this overall effect into direct effects via connectivity and indirect effects through development. We apply a relatively new synthetic control method based on interactive fixed effects to identify the causal effects of the BRI. Our main results include: (1) the overall effect of the BRI reduces the energy intensity of countries along the route by 0.0152 toes per thousand dollars, of which the direct effect is 0.0125 (82%); (2) the indirect effect in the current status is limited, mainly through the contradictory effects of economic growth and industrial structural change; and (3) countries along the route with a lower level of development, higher levels of energy technology, more abundant energy endowments, and less stringent carbon regulations experience a greater reduction in energy intensity after the BRI. [ABSTRACT FROM AUTHOR]

Urban energy issues have attracted global attentions due to the key role in controlling climate change. As one of the world's largest metropolises, Beijing has been focusing on improving urban energy performances to achieve green transition and sustainable development during the past decades, for which purpose the measurement and decomposition of energy performance is of vital importance. In this paper, exergy is introduced as one of the indicators under the frame of index decomposition analysis. An hierarchical framework is constructed to reveal the contributions from different level of urban energy system to overall energy performance. Beijing's energy and exergy consumption and intensity are then analyzed and compared from the city and sector level during 2008–2017. Results suggest that Beijing's city and sector-level energy performance has been improving during the last 10 years and technical improvements contribute significantly from both energy and exergy perspectives. Meanwhile, changes from Beijing's industrial structure and energy supply structure display neutral contributions, which probably indicate the underestimation of structural contribution is caused under the IDA framework. [ABSTRACT FROM AUTHOR]

Abstract Our study pores on evaluating the impact of firm specific and macro level determinants of energy intensity of Indian firms belonging to manufacturing and power sector. We collect a panel dataset of 3316 firms for 10 years ranging from 2010 to 2020. We employ the advanced biased corrected method of moments estimator and the quantile regression estimator for panel data models for our empirical analysis. We find that poor labor efficiency is largely responsible for increasing energy intensity of the sample firms. Energy intensity can be optimized by investing in better plant and machinery. Moreover, machineries that require frequent repairs and maintenance need to be replaced with latest tools. While larger firms are found to be energy intensive, profitable firms are found to be in a better position to enhance their energy efficiency. Under macroeconomic scenario, GDP growth and trade openness lead to boosting up the energy consumption at the firm level whereas, the global energy prices act as a constraint and necessitate careful use of energy. Based on our findings we provide certain policy recommendations and suggestions in order to limit energy intensity and enhance energy efficiency of the Indian manufacturing firms.

We study the impact of energy price changes on energy consumption intensity and its substitution effect on consumption intensity of labor, capital and raw materials, through the decomposition of input consumption intensity in Iranian manufacturing industries from 2006 to 2018. Using translog cost function, we find that increase in energy prices has a negative effect on energy intensity of all manufacturing industries and thus increasing energy prices as a strategy to reduce energy intensity is effective, although its effect on different manufacturing industries are not the same. Moreover, we find that the effect of energy price changes on consumption intensity of capital and raw material is small, while its effect on consumption intensity of energy and labor is large. An overall assessment of the change in energy prices on the input consumption intensity shows that an increase in energy prices improves not only energy efficiency but also the efficiency of labor and capital consumption. However, relative performance of energy price reform in Iran depends on general economic conditions, as well as the process of price changes. [ABSTRACT FROM AUTHOR]

Based on the panel data of 96 countries from 2013 to 2020, this study innovatively adopts the TIMG index to measure global digital economy (DE) and examines the impact of DE on carbon emissions. We find that there is an inverted U-shaped relationship between DE and carbon emissions, and energy intensity is the mediating channel. Heterogeneity analysis reveals that lower-middle-income countries can enter the 'carbon reduction dividend stage' of DE faster than high-income and upper-middle-income countries. Our findings provide empirical evidence and policy references for effectively utilizing DE for carbon reduction. [ABSTRACT FROM AUTHOR]

Objectives This review article delves into the determinants of energy intensity in emerging economies, spanning the past 30 years of research accessed from Web of Science. The review employ data visualization techniques to present a bird's-eye view of the research landscape, showcasing the geographical distribution of studies, prominent authors, and key journals in the field. Material and methods This bibliometric study utilized the March 2023 edition of the Web of Science (WoS) Core Collection database for its papers. The literature review covers the years 1993 to 2023 and includes all studies on the subject of energy intensity in the pursuit of emerging economic goals. Journal articles are isolated from the other document types using an additional filter. The WoS Core Collection database had a total of 3,918 articles. Results Through a systematic assessment of methodological approaches, we evaluate the robustness of the existing literature, pinpointing areas where methodological improvements and novel data sources can enhance future research. It offers valuable insights for policymakers, researchers, and practitioners striving to develop effective strategies for reducing energy intensity and promoting green growth. Conclusions In conclusion, emerging economies' energy intensity levels are shaped by a complex interplay of determinants that were highlighted by the analysis of factors influencing energy intensity on economic growth. In order to achieve a more sustainable and resilient energy future, emerging economies must first address these determinants through research, collaboration, and policy actions.

Abstract China, the world’s largest carbon emitter, has one of the most stringent provincial emissions reduction programs, incorporated into its Five-Year National Plan to reduce carbon emissions. However, the widening energy intensity gap between provinces poses a great challenge for carbon reduction. In this study, we analyze the convergence of Energy intensity (EIC), i.e., the time-dependent decrease of differences among regional energy intensity over time focusing on a data set of 30 Chinese provinces from 2000 to 2015. Our goal is to identify the provinces that are responsible for the observed divergence in energy intensity and identify the factors causing that divergence in each individual case. The Theil index is used to capture inter-provincial energy inequality. We use the LMDI decomposition analysis to identify the drivers of energy inequality (energy consumption structure, energy efficiency, and industrial structure). The results suggest that reducing energy intensity in Inner Mongolia, Xinjiang, and Hebei is the key to solving China's increasing energy intensity “gap” dilemma. The factors causing the energy intensity divergence in Inner Mongolia and Xinjiang are related to lagging economic growth and low energy efficiency, which impedes carbon emission reductions significantly. The factors causing the divergence of energy intensity in Hebei are rooted in its heavy industrial structure. Our findings are directly applicable to crafting regional energy policy with more targeted and practical emission reduction programs.

Abstract The inequality in CO2 emissions from agricultural energy consumption is a major challenge for coordinating low-carbon agricultural development across regions in China. However, the evolutionary characteristics and driving factors of inequality in China’s agricultural energy-related CO2 emissions are poorly understood. In response, the Kaya–Theil model was adopted to examine the three potential factors influencing CO2 emission inequality in China’s agricultural energy consumption. The results revealed that, from 1997 to 2021, agricultural energy-related CO2 emissions per capita showed a significant upward trend, with prominent polarization and right-tailing phenomena. Overall, the inequality was on a downward trend, with the Theil index falling from 0.4109 in 1997 to 0.1957 in 2021. Meanwhile, the decomposition of the national inequality revealed that the within-group inequality declined from 0.3991 to 0.1634, which was greater than between-group inequality, based on zoning the 28 provinces into three grain production functional areas. As for the three kaya factors, the energy intensity contributed the most to the overall inequality, followed by the agricultural economic development and CO2 emission intensity. Based on these results, this study provided some potential strategies to reduce agricultural-related CO2 emissions.

The aim of this paper is to investigate the dependence of carbon dioxide (CO2) emissions on various factors, including GDP, total energy consumption, renewable energy, nuclear energy, urbanisation, energy intensity, energy import dependency, and industry share of GDP, in 22 European countries from 1992 to 2019. To achieve this objective, standard panel models are used, along with advanced estimation techniques such as the Common Correlated Effect Estimator (CCE) and Instrumental-Variable Estimation Panel Models with Common Factor (2SIV - two-stage IV approach). The results of the analysis show that several factors exhibit a significant impact on CO2 emissions. Based on the 2SIV (MG) model, an increase in renewable energy production is associated with a reduction in CO2 emissions, as shown by the coefficient of –0.0924. In addition, the expansion of nuclear power plant energy production also contributes to emission reductions, although with a lower coefficient of –0.0088. In contrast, an increase in energy consumption is found to be strongly positively correlated with CO2 emissions, as indicated by a significant coefficient of 1.399. Additionally, a mitigating effect of Energy Intensity on CO2 emissions within the context of the 2SIV models is uncovered. This suggests that improvements in energy efficiency and technological progress may lead to a decoupling of energy intensity from CO2 emissions. The study contributes to the existing literature on the determinants of CO2 emissions by examining a wide range of factors and using advanced estimation techniques. The results underline the importance of economic and energy-related factors in shaping decarbonisation pathways in European countries, and highlight the importance of adopting sustainable energy practices and policies to mitigate climate change.

China, the world's largest carbon emitter, has one of the most stringent provincial emissions reduction programs, incorporated into its Five-Year National Plan to reduce carbon emissions. However, the widening energy intensity gap between provinces poses a great challenge for carbon reduction. In this study, we analyze the convergence of Energy intensity (EIC), i.e., the time-dependent decrease of differences among regional energy intensity over time focusing on a data set of 30 Chinese provinces from 2000 to 2015. Our goal is to identify the provinces that are responsible for the observed divergence in energy intensity and identify the factors causing that divergence in each individual case. The Theil index is used to capture inter-provincial energy inequality. We use the LMDI decomposition analysis to identify the drivers of energy inequality (energy consumption structure, energy efficiency, and industrial structure). The results suggest that reducing energy intensity in Inner Mongolia, Xinjiang, and Hebei is the key to solving China's increasing energy intensity "gap" dilemma. The factors causing the energy intensity divergence in Inner Mongolia and Xinjiang are related to lagging economic growth and low energy efficiency, which impedes carbon emission reductions significantly. The factors causing the divergence of energy intensity in Hebei are rooted in its heavy industrial structure. Our findings are directly applicable to crafting regional energy policy with more targeted and practical emission reduction programs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Finance is the lifeblood of the national economy, and green finance should provide high-quality services for the green development of the economy and society. The establishment of green finance reform and innovation pilot zones is an important initiative to advance China′s green finance reforms, playing a significant role in achieving environmental pollution control and the 'dual carbon' goals. This study regarded the green finance reform and innovation pilot zones established in 2017 as a quasi-natural experiment. Based on panel data from 267 Chinese cities at or above prefecture level from 2012 to 2021 and using the difference-in-differences model, this study examined the impact of green finance pilot policies on urban pollution and carbon emission reduction and further analyzed their mechanisms and heterogeneity. The findings were as follows: ① Green finance pilot policies significantly promoted urban pollution and carbon emission reduction, and this conclusion still held after a series of robustness tests. ② Mechanism analysis showed that green finance pilot policies mainly promoted pollution and carbon emission reduction by reducing energy intensity and encouraging green innovation, with the intermediary effect of energy intensity being more significant. ③ From the perspective of heterogeneity, compared with eastern cities, cities with lower financial development levels, and non-resource-based cities, pilot policies had more pronounced effects on pollution and carbon emission reduction in central and western cities, cities with higher financial development levels, and resourcebased cities. Therefore, it is necessary to expand the pilot work of green finance in an orderly manner and establish a coordinated mechanism for promoting pollution and carbon emission reduction through green finance among regions to improve the quality and efficiency of green financial services for the real economy. By increasing support for energy conservation and technological innovation, it helps to leverage the incentive mechanism of optimizing resource allocation through green finance pilot policies, deepen the supply-side structural reform of green finance, strengthen the construction of digital service platforms for green finance, build a bridge between demand and supply of green finance, promote the matching of supply and demand of green finance according to local conditions, strengthen green finance support for key areas and weak links, and promote coordinated efficiency of pollution and carbon emission reduction. [ABSTRACT FROM AUTHOR]

Using plant-level data for 2008-2017, we examine the impact of the adoption of ISO 14000 by Indian manufacturing plants on their energy intensity. The propensity-score-matching difference-in-difference (PSM-DID) estimator is used to assess the effect. Our results show that the adoption of ISO 14000 tends to reduce energy intensity in Indian manufacturing plants, especially among the low and low-medium technology industries. ISO 14000 lowers energy intensity in industrial plants in energy-intensive industries, and the effect is stronger for the group of such industries covered under the Perform–Achieve–Trade (PAT) scheme of the Indian government, a market-based compliance mechanism for energy efficiency improvement. [ABSTRACT FROM AUTHOR]

Energy intensity convergence can be used to assess the effectiveness of policies in reducing energy intensity. This study analyzes the energy intensity convergence in Indonesia based on panel data of 33 provinces from 2010 to 2018. Spatial econometrics techniques are used in the estimation of beta convergence to measure the spatial dependence of energy intensity. Empirical results show that there is evidence of both absolute and conditional beta convergences with no evidence of sigma convergence. From the results, this study found that other variables, such as provincial income, the role of manufacturing industries, the role of international trade, FDI, and population density, might encourage energy intensity convergence. From the estimation results, several policy recommendations are derived to increase energy efficiency: First, using a more efficient industrial technology. Second, attracting foreign investment to non-industrial sectors. Third, developing exports from sectors that use less energy to increase energy efficiency. [ABSTRACT FROM AUTHOR]

The increase in emissions and concentration of carbon dioxide in the atmosphere necessitates the implementation of direct carbon dioxide capture technologies. The article presents the characteristics of a single-stage membrane unit for the direct capture of carbon dioxide from the air. A membrane with a selectivity of α C O 2 / N 2 = 70 and permeability P C O 2 = 108 m 3 (S T P) (m 2 · h · b a r) is chosen as the reference variant. It is demonstrated that increasing the pressure difference in the system by reducing the pressure of the permeate stream results in an improvement of all analyzed parameters. Manipulating both the membrane surface and its CO2 permeability yields similar results. With an increase in permeability or membrane surface area, the proportion of CO2 in the retentate and permeate decreases, while the degree of carbon dioxide recovery increases. However, the energy intensity of the process is a complex issue due to the presence of a local minimum in the obtained characteristics. Therefore, a relationship between the constants of energy intensity values for the separation process on the surface area field and CO2 membrane permeability is presented. The minimum energy intensity of the process obtained is 22.5 k W h / k g C O 2 . The CO2 content in the retentate for all analyses did not exceed 280 ppm. [ABSTRACT FROM AUTHOR]

Taking the Yangtze River Delta (YRD) of China as the research area, this paper studies the influence of freight structure adjustment and energy intensity on carbon dioxide (CO2) emission from the transportation industry. Sample data from 1990 to 2019 are selected, and co-integration analysis is performed using three independent variables: energy intensity, turnover ratio of railway to highway (R/H), and turnover ratio of railway to waterway (R/W). Then, an autoregressive distribution lag-error correction model (ARDL-ECM) is established to estimate the long-run and short-run relationships among the variables through unit root test, autoregressive distributed lag (ARDL) boundary test, and Granger test. The results show that in the long run, the growth of energy intensity leads to the long-term growth of CO2 emission in the transportation sector of the YRD, and R/W and R/H have a suppressive effect on CO2 emission. Granger causality indicates that there is a bidirectional causal relationship between energy intensity and CO2 emission. This work can be a reference for government departments to formulate policies related to carbon emissions in the transportation industry. [ABSTRACT FROM AUTHOR]

Achieving Sustainable Development worldwide largely depends on the implementation of comprehensive energy transformation and decarbonization across all sectors of the economy. It necessitates an analysis of the factors and consequences associated with these efforts. Therefore, this article aims to assess and analyze the factors and barriers influencing greenhouse gas (GHG) emissions reduction and the adoption of decarbonization strategies. Furthermore, it seeks to outline the development prospects of EU countries and Ukraine in the context of energy transformation and the achievement of sustainable development. The research findings highlight a trend of decreasing GHG emissions in both the EU and Ukraine from 2006 to 2022, despite the growing dynamics of GDP. In addition, an increase in the share of renewable energy and a decrease in energy intensity of the GDP of the studied countries have been observed. The energy and transport sectors are identified as the most difficult sectors for decarbonization, and therefore the implementation of hydrogen technologies in them is the most urgent. The interdependence between CO2 emissions, GDP volume, and energy intensity of GDP in European countries has been proven based on the results of regression analysis for the period of 2012-2022. The obtained dependency allows for predicting emissions in European countries, and the lower the energy intensity, the smaller the carbon footprint will be. The government policy of supporting low-carbon technologies, which manifests itself in the adoption and implementation of environmental legislation, in particular hydrogen strategies, is studied. Climate legislation provides a global framework for economic and social transformations to address global warming and transition away from fossil fuels. From 2022, the war in Ukraine has become a serious challenge for the sustainable development of Europe and affects carbon emissions and climate sustainability. Without achieving peace, it is impossible to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Using a sample of manufacturing enterprises from the World Bank Survey during the period from 2006 to 2020, this study explores the impact of information and communication technologies (ICT) on corporate energy intensity and its mechanisms. Empirical results show that ICT adoption significantly improves the energy intensity of manufacturing enterprises in emerging and developing countries; a change in the standard deviation of ICT adoption can contribute 22.58% of the difference in corporate energy intensity. On the one hand, ICT adoption intensifies market competition and reduces product price markups, leading manufacturing enterprises to reduce investment in energy conservation. On the other hand, ICT adoption is complementary to energy and can promote energy input to replace traditional factors such as labor and capital, thereby increasing corporate energy intensity. The market competition effect and factor substitution effect account for 14.96% and 73.71% of the total effect. This study also confirms the Solow Productivity Paradox in ICT adoption, leading to the failure of the productivity mechanism for ICT to reduce energy intensity. [ABSTRACT FROM AUTHOR]

It is still necessary to regularly investigate the breakdown of socio-economic elements as a starting point for analyzing the effects of diverse human production activities on PM2.5 intensity from industrial and regional viewpoints. In this paper, the emission factor model was adopted to measure PM2.5 emissions in the Beijing–Tianjin–Hebei (BTH) region at the regional and industrial levels. The logarithmic mean Divisia index (LMDI) decomposition model was employed to analyze the factors affecting PM2.5 emissions related to energy consumption in the BTH region at the regional and sectoral levels. Building on this foundation, a system dynamics (SD) model was established to make a prediction regarding PM2.5 pollution in the BTH region in 2025. This study found that secondary industry was a major source of PM2.5 emissions in the BTH region. Coal remained the main form of energy consumption in the BTH region. Secondly, the effect size of the factors affecting PM2.5 intensity ranked in the order of energy intensity, energy structure, and industrial structure. Thirdly, in 2025, PM2.5 emissions in the BTH region will decline appreciably, but there is still a certain gap in terms of meeting the targets of "the 14th Five-Year Plan" between the three provinces and cities. These results indicate that the BTH region should achieve the effective management of PM2.5 pollution at the source through the following initiatives: it is necessary to carry out the continuous adjustment of energy structures to gradually increase the proportion of clean energy; we must steadily promote the decline in energy intensity reduction, and gradually strengthen scientific and technological innovation; and we must continue to promote the optimization of the industrial structure and increase the proportion of tertiary industry every year. [ABSTRACT FROM AUTHOR]

The decarbonization of European economies is an established reality that has been accelerating in recent years. The focus of EU policy is on the dynamic transformation of the energy balances of Member States, which most significantly impacts economies reliant on coal. In the context of emerging megatrends, this study sets out to determine the extent of changes occurring in the economies of European Union countries in relation to the Green Deal paradigm. The objective of this article is to introduce a comprehensive method developed by the authors for assessing the dynamics of energy transformation in the European Union countries under study. This method is divided into two phases. Initially, countries are classified according to the energy transformation dynamics matrix. Subsequently, the actual assessment of energy transformation dynamics is conducted using a novel composite indicator, the ETPI (Energy Transition Progress Index), based on analyses for 2022 and 2013 using Eurostat data. The results identify leaders in energy transformation, such as Sweden, Germany, Denmark, France, Italy, Spain, Austria, Finland, and the Netherlands, while highlighting significant challenges facing Poland and Bulgaria. [ABSTRACT FROM AUTHOR]

Energy intensity is a critical indicator of a country’s energy efficiency and environmental sustainability. This review article delves into the determinants of energy intensity in emerging economies, spanning the past 30 years of research accessed from Web of Science. Leveraging advanced tools such as RStudio and Biblioshiny, we analyze a rich quantity of scholarly publications to offer a comprehensive synthesis of the field’s progress. The review begins by providing a conceptual framework for understanding energy intensity and its relevance in the context of emerging economies. We then investigate the key determinants that have been explored in the literature, including technological advancements, industrial structure, economic growth, urbanization, financial development, trade and environmental regulations. Our analyses highlight the evolving trends and research gaps in each determinant, shedding light on the dynamic nature of energy intensity in emerging economies. Furthermore, we employ data visualization techniques to present a bird’s-eye view of the research landscape, showcasing the geographical distribution of studies, prominent authors, and key journals in the field. Through a systematic assessment of methodological approaches, we evaluate the robustness of the existing literature, pinpointing areas where methodological improvements and novel data sources can enhance future research. It offers valuable insights for policymakers, researchers, and practitioners striving to develop effective strategies for reducing energy intensity and promoting green growth. As emerging economies continue to play a pivotal role in the global energy landscape, understanding and addressing the determinants of energy intensity remains crucial for a sustainable future. [ABSTRACT FROM AUTHOR]

Remittances are a crucial part of economic expansion, especially in Central Asia. Nevertheless, it is not possible to ignore its environmental damage. This paper is a pioneer in investigating the association among CO2 emissions, remittances, energy consumption and economic development in Central Asian countries (Uzbekistan, Kazakhstan, Kyrgyzstan and Tajikistan) spanning the period of 1995–2022. As a methodology, the FMOLS estimator is applied to check linear impact and long-run association as well. Panel threshold regression model and 2SLS method are applied to examine potential non-linear relations among the studied variables. Hausman–Taylor and Amacurdy estimators are employed to control the endogeneity issue among the variables of interest. The results suggest the existence of a long-run relationship among the studied variables. Precisely, applying the FMOLS method, remittances negatively impact CO2 emissions in the long run. The relationship between CO2 emissions and remittances is distorted when the endogeneity issue is considered with the Panel threshold regression model, 2SLS method, and Hausman–Taylor and Amacurdy estimators. This distortion validates the linear impact of remittances on CO2 emissions in CA. The Dumitrescu–Hurlin causality test shows that all independent variables have a causal effect on the dependent variable, validating the effect of the studied variables. Consequently, decision-makers should facilitate remittances towards more environmentally friendly and sustainable solutions to prevent the detrimental effects of remittance inflows on carbon emissions in Central Asia. [ABSTRACT FROM AUTHOR]

This study utilizes panel data between 1995 and 2015 for a cross section of 33 developing (low- and middle-income) countries to investigate the impact on domestic energy intensity both of domestic R&D and of possible spillovers from foreign R&D conducted in developed (high-income) countries. More specifically, it examines R&D spillovers from developed countries (North) to domestic energy intensity in developing countries (South) through disembodied channels, total goods imports, and imports of machinery and equipment. Our main findings, based on panel cointegration techniques, are as follows: First, domestic R&D in the long run does not contribute to reductions in energy intensity in developing countries; second, there is no evidence to suggest that disembodied North–South R&D spillovers affect the long-run level of domestic energy intensity; third, there are nevertheless significant spillovers from R&D conducted in industrial countries that reduce energy intensity in developing countries; and fourth, while many imported goods are not a channel for North–South R&D spillovers, such spillovers are transmitted through imports of machinery and equipment. [ABSTRACT FROM AUTHOR]

The objective of this study is to investigate the correlation between energy intensity and environment-related technology in industrialized countries. By utilizing panel data from 23 countries over a span of 32 years (1990–2021), this research aims to contribute to the comprehension of the role of green innovation in sustainable development. The study employs the Stochastic Impacts by Regression on Population, Affluence, and Technology model while controlling for variables including population growth, gross domestic product in purchasing power parity, Information and Communication Technology capital deepening, renewable energy consumption, and green innovation represented by research and development expenditure on environment-related technology. The results of the analysis, employing panel unit root tests, cross-sectional dependence tests, and a Method of Moments quantile regression, reveal that green innovation has a positive influence on diminishing energy intensity, with a more substantial impact at higher quantiles. Moreover, ICT capital deepening is determined to have a positive and noteworthy effect on reducing energy intensity. The findings of this study offer valuable insights for policymakers in their endeavours to accomplish sustainable development goals.

AbstractAs the global ambition is directed at net-zero 2050 amidst energy intensity-efficiency targets, the advanced economies, such as the United States of America (USA) has been consistently charged with more target-driven commitments. Considering this, the current study finds the influence of commercial, industrial, and household energy intensities on both the economic and environmental indicators. A set of cointegration approaches was employed to evaluate the long-run and short-run relationship between covariates and carbon emission over the period 1974–2019. Empirical findings reveal that all the covariates are positive and significantly related to carbon emissions. For instance, the emission of carbon dioxide is worsened by economic growth in both the short- and long-run. Additionally, intense use of energy across the commercial, household, and industrial sectors is responsible for an increase in environmental degradation arising from the emission of carbon emission. Importantly, environmental degradation that is attributed to energy intensity is far more (twice) in the commercial sector and household sector, than in the industrial sector. Regarding the economic aspects, there is statistical evidence that research and development expenditure in energy efficiency improves economic growth while higher energy intensities in the commercial and industrial sectors are detrimental to economic expansion. As a policy, the study suggests that the share of renewable or clean energy technology in the country’s energy mix should be significantly increased to over-turn the undesirable economic, environmental, and global warming-related issues in the United States. Other few directions for policy implication were addressed.

Since the 21st century, as the digital economy has flourished and the Fourth Industrial Revolution has deepened, emerging technologies have exerted a significant influence on social development, leading to the rapid informatization and digitalization of society. Therefore, in the digital age, industrial intellectualization and energy intensity may interact. In this study, an industrial intelligent system is constructed considering three aspects, and the relationship is explored between industrial intellectualization and energy intensity from 2006 to 2018 in China. Industrial intellectualization can effectively improve energy efficiency and thus restrain energy intensity with a significant lag effect. In addition, China's energy intensity is highly spatially autocorrelated and spatially agglomerated. The negative spatial spillover effect of industrial intellectualization on energy intensity is also of concern. Finally, the nonlinear effects of industrial intellectualization on energy intensity are comprehensively analyzed under different levels of economic growth, technological progress, industrial restructuring, educational progress, fi- nancial development, and environmental regulation. [ABSTRACT FROM AUTHOR]

Energy efficiency can help facing the climate crises. Yet the energy intensity has decreased more slowly than required to achieve climate goals. Based on this premise, we build an agent-based model to study the effects of different energy efficiency policies. Policies analysed range from indirect policies – taxes, incentives, and subsidies – to direct technological policies, where a public research laboratory invests in R&D to establish a new technological energy efficiency paradigm. Results reveal that, although most of the policies effectively reduce energy intensity, the research lab is the most efficient in promoting energy efficiency without negative impacts on macroeconomic and public finance conditions. However, the success of this policy requires a long-term commitment, highlighting the importance of complementing this strategy with more "ready to use" measures. The findings also indicate that most policies do not induce significant macroeconomic rebound effects. Concerns about macroeconomic rebound effects may likely be overstated. • Improvements in energy efficiency help face the ongoing climate and energy crises. • Yet, energy intensity has declined more slowly than needed to meet climate goals. • The paper builds an agent-based model to study different energy efficiency policies. • Indirect policies work but are outperformed by direct technological policies. • The macroeconomic rebound effect induced by most of the policies is rather small. [ABSTRACT FROM AUTHOR]

Environmental information disclosure (EID) is an important measure to promote multiple subjects' collaborative management of pollution emissions. In this paper, we first measure the carbon dioxide (CO2) emissions of 282 cities in China from 2006 to 2020, and clarify the theoretical mechanisms and transmission channels of EID affecting CO2. Subsequently, the Time-varying difference-in-differences (DID) and the mediation effect model are used to assess the impact of EID on CO2 and its transmission mechanism, respectively. The study shows that although EID is a voluntary environmental regulation, the policy significantly reduces CO2, and this reduction effect has regional and low-carbon policy intensity heterogeneity. The study also shows that green technology innovation and energy intensity mediate the carbon reduction effect of EID. This study has important reference significance for reducing greenhouse gas emissions and improving the quality of economic development. [ABSTRACT FROM AUTHOR]

The Subsidized energy system of Iran, with its high financial burden, failed to achieve its intended economic goals, resulting in increased energy consumption and pollutant emissions. Energy product subsidies in Iran are among the highest in the world and have important implications for developing countries. This study examines the impact of subsidy removal policy on energy and emission intensities using a Dynamic Computable General Equilibrium model. The findings reveal that after subsidy removal, total output experiences an annual growth of around 1.5%, with output composition changes mainly favoring agriculture and services that are less energy dependent. However, prices soar by at least 10% owing to the higher costs of energy products. The decreasing trend in energy intensity after subsidy reform is accompanied by a decrease in emission intensity. Higher prices of energy after subsidy removal and the corresponding improvement in the efficiency of energy consumption lead to lower emission intensity. [ABSTRACT FROM AUTHOR]

The article discusses the interaction of disc vibration working elements of a seed drill with soil to reduce traction resistance and energy consumption in soil processing. Regularities characterizing the impact of vibrations on the soil are identified, and a mechanical-mathematical model of soil cutting by the vibrational disc-working element of a seed drill is developed. Mathematical dependencies for determining the parameters of vibro-impact interaction of the cutting edge of the disc-working element with the soil are obtained. The efficiency conditions of the vibro-cutting process, in terms of reducing traction resistance and energy consumption, are established. A methodology for selecting rational parameters for vibro-cutting soil in the design and operation of the disc-working element of seeding equipment is developed. Experimental results of a prototype vibrational working equipment are presented, confirming theoretical findings and demonstrating the effectiveness and feasibility of vibrational soil cutting by the disc-working element for reducing traction resistance and energy costs. The research, the results of which are presented in this article, is funded by the Committee on Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan (grant AP14869252 "Development of the universal sowing complex with increased productivity for the agro-industrial production of the Republic of Kazakhstan"). [ABSTRACT FROM AUTHOR]

This paper investigated the dynamic and causal relationship among energy intensity, economic growth, urbanization, energy consumption, FDI, and PM2.5 in 1995–2019 period for China, India, Germany, Canada, USA and United Kingdom countries through Panel Fourier Bootstrapping ARDL (PFBARDL) model and Panel Fourier causality test. According to PFBARDL results, the evidence of cointegration between the variables was detected. In the PFBARDL model, the error correction coefficient is determined as -0.169. Results showed that there is a bidirectional causality between economic growth and PM2.5 release, between fdi and PM2.5 release, between energy intensity and PM2.5 release. Rising economic growth, energy consumption structure, and urbanization will have an adverse effect on PM2.5 concentrations. Policy makers must carefully balance the connection between mitigation of PM2.5 and diminishing energy consumption, and increasing economic growth, urbanization, and energy intensity for determining policies to control PM2.5 concentrations. Thus, in order to reduce PM2.5, the governments must explore a new economic pattern to decouple the linkage between PM2.5 and economic growth. [ABSTRACT FROM AUTHOR]

Decoupling of production activities and greenhouse gas (GHG) emissions, or a decline in GHG intensity, is a key metric for gauging GHG mitigation performances. In this study, we explore the determinants of GHG intensity in Canadian industries to understand its key drivers. This study is relevant, because Canada is a developed country characterized by high energy and GHG intensities. Canada has also introduced a series of policy measures to mitigate GHG emissions, including a carbon tax and investments in renewable electricity. The most significant factor for GHG intensity is energy intensity. However, fuel mix, policy trends, and sectoral shifts are essential. After conducting stationarity and cointegration tests, we estimated the relationship between GHG intensity and these determinants using panel error correction, dynamic fixed effects, and dynamic OLS methods to determine the long-run relationships. Besides the strong effect of energy intensity, we found that industrial production mix that indicates sectoral shifts, fuel mix, and the time-fixed effects that capture factors such as the introduction of a carbon tax and technology standards have statistically significant impacts on GHG intensity. We found that industries that rely more on fuel sources other than electricity are characterized by higher GHG intensity. The policy implication is that energy efficiency and fuel switching are essential for reducing GHG intensity, but the role of factors such as sectoral shifts should not be ignored. [ABSTRACT FROM AUTHOR]