Energy Intensity Research Articles

Impact of Energy Intensity and CO2 Emissions on Economic Growth in Gulf Cooperation Council Countries

This study investigates the impact of energy intensity and CO2 emissions on economic growth in Gulf Cooperation Council (GCC) countries, aiming to understand the interplay between energy consumption, environmental sustainability, and economic performance. We analyze data from 1990 to 2023 across six GCC countries. The study employs the fixed effects model, random effects model, and pooled regression model to examine the relationships between energy intensity, CO2 emissions, and GDP growth, controlling for factors such as foreign direct investment, trade openness, population, unemployment, and urbanization. Our findings reveal a significant negative impact of energy intensity on economic growth, and an increase in energy intensity is associated with a decrease of approximately 0.2969 units in GDP, indicating that higher energy consumption per unit of output hinders economic performance. While CO2 emissions positively affect growth in GCC countries, a one-unit increase in CO2 emissions is associated with an increase of approximately 0.3961 units in GDP. The study emphasizes the necessity for GCC countries to adopt sustainable energy practices to reduce energy intensity and boost economic growth. By aligning economic strategies with environmental sustainability goals, these nations can achieve long-term growth while effectively addressing the challenges of climate change. This research contributes to the ongoing discourse on sustainable development in the region and underscores the importance of harmonizing economic growth strategies with environmental objectives.

Philosophical foundations of posthuman communication studies

The article examines the philosophical foundations of posthuman communication studies – a new branch of the science of communications aimed at studying the nature and structure of technobiomaterial interactions, communications of material and digital actors, their characteristic mechanisms and trends of mutual influence of forces and processes (both human and non–human), leading to the exchange of actions, affects, emotions and meanings, circulation of energy forces and intensities, material formation and discursive diversity, and, thereby, to material changes – multiplication of the possible through the implementation of its specific invariants. A number of changes that necessitate the institutionalization of posthuman communication studies are analyzed: a new understanding of the «human subject» (rejection of the idea of Cartesian subjectivity); revision of the understanding of information (information as a «formation» / procedural generation, rather than a fixed set of data); expansion of the specifics of understanding the processes of interaction and communication (from exchange of information between subjects to process formation and circulation of affects between bodies / objects). A number of philosophical, research and applied theoretical ideas that influenced the formation of the conceptual sphere of posthuman communication studies are considered.

Stochastic convergence of renewable energy intensity across US States: evidence from a panel unit root test with asymmetries and common factors

ABSTRACT This study examines the stochastic convergence of renewable energy intensity (REI) across US states. We test for the stationarity of relative REI (stochastic convergence) using a recently developed quantile panel unit root test that accommodates both cross-sectional dependence and asymmetric behaviour. Our overall finding is that most states exhibit convergence, which implies that economic growth is sustainable with a higher share of renewable energy in the energy mix. This result provides support for those advocating that state governments should increase investment in renewable energy in advancing the clean energy transition. However, over half of the states display asymmetric stochastic convergence, which implies that how effective policies will be in promoting renewable energy efficiency will depend on the size and type of shocks impacting REI. Our results imply that in states that encounter relatively large positive shocks to REI, it may be necessary to invest more in the diffusion of renewable energy technologies and set long-term targets. Asymmetric convergence behavior also makes it difficult to coordinate policy responses across states, providing support for a decentralized approach in which each state invests in renewable energy technologies specific to their unique economic circumstances, rather than adopting a mandated overall national policy approach.

Insight into Carbon Emissions in Economically Developed Regions Based on Land Use Transitions: A Case Study of the Yangtze River Delta, China

This study focused on the land use (LU) structure and carbon emissions (CEs) in the Jiangsu, Zhejiang, Anhui, and Shanghai provinces of the Yangtze River Delta (YRD) in China from 2000 to 2020, using the STIRPAT model and scenario analysis (SA). We conducted an analysis of the influence exerted by relevant factors on land use carbon emissions (LUCEs) and made forecasts regarding the diverse development scenarios of CE trends, aiming to provide methodological guidance for validating the effectiveness of existing policies in reducing CEs and offer direction for achieving the peak CO2 emissions target as soon as possible. It also constitutes a significant reference for the early realization of the peak CO2 emissions target. The results indicated the following: (1) Between 2000 and 2020, CEs resulting from LU in the YRD rose from 2.70 × 108 t to 9.10 × 108 t, marking an increase of 243.77%. In 2020, the built-up area was the predominant contributor to CEs, representing 99.15% of the overall carbon sources, whereas forests served as the main carbon sink, comprising 92.37% of the total carbon sinks (CSs) for that year. (2) For each percent increase in the parameters considered in this study, the corresponding increases in LU CO2 emissions were estimated to be: 1.932% (population), 0.241% (GDP per capita), −0.141% (energy intensity), 0.043% (consumption structure), 1.045% (industrial structure), and 0.975% (urbanization). (3) According to the existing policy framework and development plans, the YRD is expected to achieve peaking carbon dioxide emissions by 2030. If energy conservation and carbon reduction strategies are implemented, this peak could be achieved as early as 2025. However, if economic growth continues to depend primarily on fossil fuel consumption, the region may not hit its carbon peak until 2035. (4) The low-carbon scenario, which considers the needs of social progress alongside the intensity of carbon emission reductions, represents the most effective development strategy for reaching a carbon peak in LU within the YRD. Effectively managing population size and facilitating the upgrading of industrial structures are key strategies to hasten the achievement of peaking carbon dioxide emissions in the region.

The impact of China-US technological innovation, transportation, and power generation on energy, environment, and economic growth sustainability

China and the United States have the highest demand for fossil fuel energy for transportation and power generation, which promotes growth while also damaging the environment. Policymakers, and environmental scientists, are increasingly interested in understanding key strategies to improve energy efficiency to mitigate fossil fuel energy demand and sustain the environment and growth. In this context, this study uses augmented mean groups (AMG) and common correlated effects mean group (CCEMG) estimators to reveal the impact of China-US technological innovation, transportation infrastructure, and power generation on fossil fuel energy demand and fossil fuel energy intensity from 1995 to 2020. Besides, the study examines whether fossil fuel energy use and fossil fuel energy intensity are the main drivers of carbon dioxide emissions (CO2) and economic growth. The analysis results show that technological innovation has a strong adverse influence on fossil fuel energy use, and fossil fuel energy intensity. Electricity generation, road transport infrastructure investment and aviation infrastructure investment have considerably contributed to fossil fuel energy use, and fossil fuel energy intensity. The construction of rail transit infrastructure has significantly alleviated fossil fuel energy demand, and fossil fuel energy intensity. Fossil fuel energy use and fossil fuel energy intensity significantly contribute to carbon dioxide (CO2) emissions and economic growth. However, technological innovation and renewable energy use can substantially reduce carbon dioxide (CO2) emissions, while making a considerable contribution to economic growth. Based on empirical investigation, this study provides a series of useful insights into the sustainable development goals of the Chinese and American economies.

The Pushback Against Canada’s Carbon Pricing System: A Case Study of Two Canadian Provinces, Saskatchewan and Nova Scotia

As part of its plan to transition to an energy secure and environmentally sustainable future, Canada has had a national carbon pricing system since 2019. When first introduced, the $20 (‘$’ refer to Canadian dollars (CAD) in this paper) per tonne price was widely accepted by most Canadians and seen as a way of helping Canada meet its emissions reduction pledges made at the 2015 United Nations Climate Change Conference (COP 21) in Paris. The Canadian system is novel in that it both charges consumers for their emissions and reimburses them for their expected emissions; this is intended to raise awareness of their emissions and encourage those who can afford to opt for lower-emissions energy services to do so. By 2023, the combination of the carbon price reaching $65 per tonne and the post-pandemic economic slowdown was seized on by numerous politicians as a way of pushing back against the carbon pricing system, with most demanding the entire system be scrapped. The debate intensified in late 2023 and into 2024, when the federal government removed the carbon tax on home heating oil because the reimbursement was insufficient to cover the cost of the tax. In this paper, we consider the recent actions of two Canadian provinces, Saskatchewan and Nova Scotia, embroiled in the federal carbon pricing system debate due to the removal of the carbon tax on fuel oil for space heating. The objective of this paper is to identify how some of the reasons, including global post-pandemic inflation and other challenges facing Canadians, such as those cited in third-party polls, have contributed to a rise in the system’s unpopularity. Our method estimates and compares the impacts of the carbon tax on the household energy services for space and water heating, lighting and appliances, and private (i.e., household) transportation for different types of housing (apartment, single-attached, and single-detached) and number of occupants (two, three, and four) in Saskatchewan and Nova Scotia. The results of this work show that while Saskatchewan households have higher energy intensities than those in Nova Scotia, the impact of the carbon tax on Nova Scotians using fuel oil for heating was greater than in Saskatchewan. In Saskatchewan and Nova Scotia, natural gas and electricity, respectively, are used for heating. This paper concludes with a summary of our findings and potential options for improving perceptions of the system.

A step towards energy efficiency in G7 countries: analyzing the role of economic complexity and shadow economy on energy intensity

A step towards energy efficiency in G7 countries: analyzing the role of economic complexity and shadow economy on energy intensity

Understanding the Historical Trend of Final Energy Intensity of GDP During Economic Transitions: The Case of Portugal (1960–2014)

Understanding the Historical Trend of Final Energy Intensity of GDP During Economic Transitions: The Case of Portugal (1960–2014)

The BRICS Nations Framework for Curbing Carbon Emissions: Evidence From Energy Intensity, Renewable Energy, and Environmental Policy

The BRICS Nations Framework for Curbing Carbon Emissions: Evidence From Energy Intensity, Renewable Energy, and Environmental Policy

Frictional Abrasion of Rubber: Transition from Sliding to Rolling

ABSTRACT To develop applicable friction and wear models on tire scale, reliable test data are required. Consequently, friction tests on block level are requested because the distribution of contact pressure as well as slip velocity is nearly homogeneous at the contact surface of the sliding rubber block. However, wear mechanism and energy intensity levels of sliding rubber blocks and rolling rubber wheels or tires differ significantly. Consequently, linking both sliding and rolling frictional abrasion is required; thus, a wear model for rubber material is introduced to consider both deformation slip and sliding. The model input for sliding friction and resulting wear rate is derived from linear friction test experiments using sliding rubber blocks at different loading. A unique and sophisticated re-mesh algorithm ensures proper mesh modification due to abrasion of the structure. A wear energy evolution approach is developed to consider low abrasion with small sliding distances to predict wear at rolling rubber wheels. The simulation framework of abrasion modeling is successfully validated using laboratory abrasion tests.

Coupling coordination and spatial network characteristics of carbon emission efficiency and urban green innovation in the Yellow River Basin, China

Carbon emission and sustainable development have attracted global attention. Promoting urban green innovation (UGI) in the Yellow River Basin (YRB) will help in lowering the intensity of carbon emissions and improve the safety and sustainability. A SBM-DEA model was constructed to measure carbon emission efficiency (CEE) and the degree of coupling and coordination with UGI was calculated in 73 prefecture-level cities in the YRB. The spatial association network of CEE coupled with UGI is constructed by using a modified gravity model, social network analysis and the quadratic assignment procedure (QAP), to analyze spatial potential energy, network characteristics and clustering characteristics. The study found that: (1) The coupling coordination degree of CEE and UGI in the YRB shows fluctuating growth, mutual promotion and continuous coordinated development. (2) The spatial linkage between CEE and UGI is gradually close, and the potential energy of the spatial linkage increases year by year, with obvious spatial spillover effect, indicating that the radiation and influence between cities are gradually increasing. In contrast to the middle stream, the upstream and downstream regions show a higher percentage of spatial potential energy in the entire network, and their network structure is more intricate and robust. (3) The clustering patterns of the three major urban clusters are examined using the block model, exploring the positioning and functions of various cities in these urban conglomerations, which includes the net spillover, net benefit, two-way spillover and broker plate, so as to strengthen the connection and coordinated development between cities. (4) Factors such as spatial adjacency, industrial structure, population density, digital economy and urbanization level, and energy intensity significantly impact the spatial association network, along with temporal and regional heterogeneity. Therefore, tailored policies are needed in the YRB to strengthen collaboration between CEE and UGI, fostering the development of a circular economy and promoting sustainable development.

Corporate social responsibility and energy efficiency: Empirical evidence from the manufacturing sector of India

AbstractThe strategic business firm manages today's profitability and tomorrow's sustainability to achieve a comparative advantage in the emerging market economy. Considering India's ambitious emission reduction target and rapid economic development, this study explores the potential relationship between corporate social responsibility (CSR) and the energy efficiency of manufacturing firms in India. Using firm‐level data, the panel fixed effects model shows that CSR negatively explains energy intensity (EI). We observed a consistent negative relationship between CSR and EI for all models, with and without controlled firm‐specific variables. Firms that manufacture chemical and chemical products, pharmaceuticals, medical chemicals and botanical products are energy intensive without CSR; however, CSR activities helped these firms become energy efficient. Our result confirms that voluntary CSR is less efficient than mandatory CSR in contributing to environmental and energy‐related indicators at the firm level. Our empirical results indicate several policy implications: (1) CSR should also focus on sustainable business models related to energy efficiency and reduction in carbon emissions; (2) firms should be encouraged to use CSR related to environmentally friendly innovations. We conclude that CSR spending and environmental expenses will increase energy efficiency at the firm level, which will help achieve net‐zero targets and sustainable industrial development.

How does green technology innovation affect urban carbon emissions? Evidence from Chinese cities

Green technology innovation is regarded as a key catalyst for sustainable urban development. This study mainly utilizes 278 Chinese cities data from the China Urban Statistical Yearbook, adopting ordinary least squares (OLS) and mediation effect model to investigate the dual impact and mechanism of green technology innovation on urban carbon emissions. Besides, spatial Durbin model (SDM) and threshold model are employed to examine spillover and non-linear impact. The results indicate that: (1) Green technology innovation can significantly mitigate carbon emission intensity, but cannot reduce carbon emissions. Thus, both carbon emission reduction effect and rebound effect coexist, and there is heterogeneity across different cities. (2) Green technology innovation has the potential to decrease carbon intensity through optimizing energy intensity, government participation and basic life cleanliness. (3) There is a spatial spillover effect concerning the emission reduction impact of green technology innovation. (4) The relationship between carbon emission intensity and green technology innovation exhibits a non-linear impact under varying levels of energy intensity, government participation, industrial structure rationalization, and environmental regulation. Building upon these findings, policy recommendations outlined in this study encompass the reinforcement of technological utilization, avoidance of excessive governmental intervention, and adoption of strategies for regional connectivity and differentiation.

Low-carbon economic optimization strategy for industrial loads in parks considering source-load-price multivariate uncertainty

A low-carbon economic optimization method is proposed for industrial loads in parks considering multivariate uncertainty. Model of dynamic load node carbon intensity is proposed considering the uncertainty of clean energy and dynamic conventional units carbon intensity based on system currents. The robustness is improved based on multi-interval uncertainty set. The gap is filled by hybrid copula model with Generalized Autoregressive Conditional Heteroskedasticity (GARCH) prices in the uncertainty model. The GARCH is used to built the marginal distribution function of prices, and a hybrid copula model is proposed to obtain the joint probability density function based on the weights calculated by Euclidean distance. The LNCI probability distributions of the regulation potential of loads are proposed with the virtual energy storage and the virtual power model to improve the descriptive ability of uncertainty based on the expansion and contraction functions. Finally, the typical scenarios are extracted based on Monte Carlo and Wasserstein measures. The Column sum Constraint Generation algorithm and strong duality theory are used to get the robust-stochastic optimization. The method proposed in the paper has a positive effect on enterprises to rationalize their production schedules, reduce electricity and carbon emissions costs and increase the revenue from participating in grid regulation.

Toward Carbon‐Negative Methanol Production from Biogas: Intensified Membrane Reactor

AbstractThe modern world's major challenges, such as global warming, air pollution, and increasing energy demands, escalate the importance of sustainable development and transition toward renewables using innovative and environmentally friendly solutions, such as intensifying chemical processes, to reduce carbon footprints effectively. Aiming to enhance the process toward negative carbon emissions, this perspective explores the intensified membrane reactors for reducing the energy intensity of converting biogas into methanol, a versatile chemical feedstock, and renewable liquid fuel. Syngas and methanol synthesis processes, catalysts, and membranes were explored, and novel reactor designs were proposed. Introduction of selective membranes into the catalytic reaction zone to combine synthesis separation steps could enhance the system efficiency and intensify the process by recycling energy and materials, besides reducing costs and required energy for the separation process: the continuous harnessing of products shifts reactions toward desired species while recycling energy and materials enhances the process efficiency, and separating water from methanol reduces the required energy and costs of extra processes for methanol separation. The successful implementation of this technology holds significant promise for sustainable developments in producing chemicals and renewable fuel from renewable biogas and reducing methane and carbon dioxide emissions toward achieving carbon‐negative technologies.

Process Simulation and Technical Evaluation Using Water-Energy-Product (WEP) Analysis of an Extractive-Based Biorefinery of Creole-Antillean Avocado Produced in the Montes De María

The annual increase in the world’s population significantly contributes to recent climate change and variability. Therefore, researchers, engineers, and professionals in all fields must integrate sustainability criteria into their decision-making. These criteria aim to minimize the environmental, social, economic, and energy impacts of human activities and industrial processes, helping mitigate climate change. This research focuses on developing scalable technology for the comprehensive use of avocados, adhering to sustainability principles. This work presents the modeling, simulation, and the WEP (Water-Energy-Product) technical evaluation of the process for obtaining bio-oil, chlorophyll, and biopesticide from the Creole-Antillean avocado. For this, the extractive-based biorefinery data related to water, energy, and products are taken from the material balance based on experimental results and process simulation. Then, eight process parameters are calculated, and eleven technical indicators are determined. Later, the extreme technical limitations for every indicator are demarcated, and an evaluation of the performance of the indicators is carried out. Results showed that the process has a high execution in aspects such as fractional water cost (TCF) and energy cost (TCE), as well as solvent reuse during extraction processes (SRI) and production yield, noting that the mentioned indicators are above 80%. In contrast, the metrics related to water management (FWC) and specific energy (ESI) showed the lowest performance. These discoveries support the use of optimization techniques like mass process integration. The energy-related indicators reveal that the process presents both benefits and drawbacks. One of the drawbacks is the energy source due to the high demand for electrical energy in the process, compared to natural gas. The specific energy intensity indicator (ESI) showed an intermediate performance (74%), indicating that the process consumes high energy. This indicator enables us to highlight that we can find energy aspects that require further study; for this reason, it is suitable to say that there is potential to enhance the energy efficiency of the process by applying energy integration methods.

Spatial-Temporal Evolution and Determinants of Green Economy Efficiency: An Integrated Analytical Approach

In response to global environmental challenges and the need for sustainable development, this study investigates the spatiotemporal evolution and determinants of green economy efficiency (GEE) across 30 Chinese provinces from 2005 to 2021. By employing a Slack-Based Measure (SBM) Data Envelopment Analysis (DEA) model, kernel density estimation, and spatial Markov chain analysis, this study provides a comprehensive assessment of GEE, incorporating both spatial and temporal dimensions. The analysis reveals a positive overall trend in GEE, with notable regional disparities, as eastern provinces exhibit significantly higher efficiency levels compared to central and western regions. Additionally, GEE improvements have been observed nationwide, although the central and western regions lag. Key factors influencing GEE include energy intensity, economic development, urbanization, industrialization, transport infrastructure, and government intervention, with distinct regional variations in their impact. The findings suggest that optimizing economic growth, reducing energy intensity, and fostering green urbanization and industrialization are essential strategies for enhancing GEE. This research contributes to the theoretical understanding of green economy efficiency and offers valuable policy recommendations for achieving balanced regional development and sustainable growth in China.

The contribution of green technological innovation, clean energy, and oil rents in improving the load capacity factor and achieving SDG13 in Saudi Arabia

This research aims to assess the effects of green technological innovation, renewable energy sources, and oil rents on the load capacity factor in Saudi Arabia from 1988 to 2021. The primary conclusions can be outlined as follows. The combined cointegration and Saikkonen-Lütkepohl cointegration tests reveal long-run relationships between the load capacity factor and the explanatory variables at the 1% significance level. In comparison, the Phillips-Ouliaris test shows evidence of cointegration only at 10%. Moreover, the quantile regression indicates that oil rents adversely impact environmental quality; however, they remain contingent upon environmental conditions. A 1% increase in oil rents results in a decline in environmental quality by 0.025% under poor conditions, 0.036% under moderate/normal conditions, and 0.108% under good conditions. On the contrary, renewable energy consumption and green technological innovation improve environmental quality, irrespective of the prevailing environmental conditions. However, the environmental impacts of renewable energy consumption exceed those of green technological innovation. Results show that a 1% increase in renewable energy consumption leads to a 0.052-0.253% improvement in environmental quality, whereas a 1% increase in green technological innovation results only in a 0.017-0.047% improvement. Finally, population and GDP per capita exert negative and positive implications on the load capacity factor, respectively, while energy intensity has no significant environmental effects. The research findings provide significant insights and suggest policy recommendations to address climate change and meet the targets set out in SDG13.

Study on steam energy efficiency enhancement, cost management and CO2 emissions in the food industry

Malaysia’s energy intensity per unit GDP has been increasing since the 1990s, leading to the government’s efforts to promote energy efficiency via policies and initiatives such as Energy Performance Contracting (EPC). Additionally, the industrial sector in Malaysia consumed 28% of total final energy in 2018, placing it as the country’s second-largest final energy consumer [1]. This case study focuses on improving energy efficiency in the steam system of an existing plant in the food industry in Malaysia. This work was performed in collaboration with a local Energy Service Company (ESCO) to study the existing steam system, recognize its process requirements and constraints and consequently propose and evaluate retrofit opportunities. These opportunities were evaluated across 3 performance parameters (power output or energy savings, cost savings and CO2 emissions savings). Simulations were performed using the Steam System Modeler Tool (SSMT). The study found that Combined Heat and Power (CHP) was not feasible due to a combination of low steam pressure and flowrate available in the system. However, the study also found that improving condensate recovery coupled with condensate flashing from the high pressure to low pressure header offered the highest increments in overall performance.

Do environment-related technologies, urbanization, trade openness, and income impact energy consumption and intensity?

Do environment-related technologies, urbanization, trade openness, and income impact energy consumption and intensity?