Energy Resources Research Articles

The effects of green technology and globalization on energy demand in emerging economies

Preserving energy security and promoting sustainable development in the face of globalization constitute essential challenges. Hence, this study focuses on how green technology innovation (GRTI) and globalization (GLOB) influence renewable (RE) and non-renewable (NRE) energy demand, employing panel data from 15 emerging nations from 1990 to 2023. The study discloses major insights employing several panel data approaches to tackle cross-sectional dependency, slope heterogeneity, and structural breaks in cointegration. The results indicate that a 1% change in GRTI leads to a 0.13% rise in REN at a 1% significance level, whereas its impact on NRE is negligible, reducing it by 0.01% in the long run. Conversely, a 1% increase in GLOB leads to an insignificant 2.62% rise in REN and a significant 1.02% increase in NRE at the 5% significance level. Besides, in terms of aggregate energy consumption, GRTI has an unfavorable impact, whereas GLOB holds a positive impact. Notably, the interaction between regulatory quality (REQ) and IVA implies a substantial fall, although the interaction between GLOB and REQ remains promising for aggregate energy demand. Finally, the COVID-19 epidemic markedly enhanced environmental awareness and energy-saving behaviors beyond the explanatory variables. Policies should encourage green technology innovation and prudent globalization to conserve energy demand.

Exploring the Nexus of Economic Growth, Energy Mix, Services, Trade Openness, and Environmental Quality: Evidence from N11 Countries

Despite considerable research on the connections between economic growth, energy consumption, trade, and environmental sustainability, a notable gap persists in understanding the varying effects of these factors at different levels of resource use. This study seeks to fill this gap by utilizing quantile panel regression analysis to investigate the intricate interactions among these variables in the N11 countries. Our results indicate that economic growth has a negative impact on environmental sustainability, particularly at higher levels of resource consumption. In contrast, the consumption of renewable energy has a positive effect on sustainability, whereas reliance on non-renewable energy and trade openness produces adverse outcomes. These findings highlight the urgent need for policymakers to pursue a balanced approach to economic development that emphasizes environmental sustainability and considers the social implications of the transition.

Optimization of a Bayesian Game for Peer-to-Peer Trading among Prosumers under Incomplete Information via a CNN-LSTM-ATT

In modern low-carbon industrial parks, various distributed renewable energy resources are employed to fulfill production needs. Despite the growing capacity of renewable energy generation, a significant portion of the power produced by these renewable resources remains unconsumed, resulting in a waste of resources. Within an industrial park, microgrids that both generate and consume energy resources act as energy prosumers. Peer-to-peer (P2P) trading provides an efficient means of utilizing renewable energy among these energy prosumers, who possess both power generation and consumption capabilities. However, within the current market mechanism, each prosumer retains private information that is not disclosed on the network. To address the issue of incomplete information among multiple prosumers during the decision-making process, we develop a Bayesian game model based on the CNN-LSTM-ATT prediction method for P2P electricity transactions among multiple prosumers. The energy prosumers in each industrial park aim to minimize their energy consumption costs by adjusting strategies that include P2P energy trading and managing thermal loads. Prosumers make decisions on the basis of their own characteristics and estimates of other prosumer characteristics, which are obtained from the joint probability distribution predicted by the CNN-LSTM-ATT method. These decisions are aimed at minimizing each prosumer's electricity costs. The simulation results demonstrate the effectiveness of the Bayesian game model proposed in this study.

High-resolution 3D hydrodynamic modeling and comprehensive assessment of tidal current energy resources

As a clean and renewable resource, tidal current holds significant development potential. However, accurately assessing tidal current energy resources has been a persistent challenge. This study proposes a comprehensive assessment method using a small-scale, high-precision, multi-criteria three-dimensional hydrodynamic model to assess resource reserves applied to the Zhairuoshan Waterway. The hydrodynamic model was employed to simulate critical parameters such as tidal level, flow velocity, and flow direction. Multiple statistical indicators were used to evaluate the model's accuracy, showing consistency. The study analysed the flow speed distribution over a complete cycle, revealing an average flow speed of 1.51 m/s, with a maximum speed reaching 3.83 m/s. The generally high flow speeds within the waterway, coupled with the stability of the tidal current, indicate the significant resource potential of the study area. A quantitative analysis of the spatial distribution of tidal current energy was conducted using energy flux density, and the results showed that high energy density areas are widely distributed. Furthermore, the theoretical tidal energy resources of the waterway were calculated, showing that the maximum resource reserves could reach 9.98 MW at the selected cross-sections. Coupled with the analysis of unit-width energy flux, the high-potential areas within the waterway were further identified.

Ion-exchange induced multiple effects to promote uranium uptake from nonmarine water by micromotors

As the fundamental resource in nuclear energy, uranium is a sword of two sides, due to its radioactive character that could cause severe impact to the environment and living creatures once released by accident. However, limited by the passive ion transport, the currently available uranium adsorbents still suffer from low adsorption kinetics and capacity. Here, we report a self-driven modular micro-reactor composed of magnetizable ion-exchange resin and adsorbents that can be used to dynamically remove uranium from nonmarine waters. Because of the long-range pH gradient and phoretic flow established by the recyclable ion-exchange resin, the micro-reactor shows a fast uranium adsorption rate and reaches a uranium extraction capacity of 629.3mgg-1 within 10min in 30 ppm uranium solution, as well as good recyclability in repeated use. Numerical simulation result confirms that the phoretic flow and electric field accelerate uranium transport to the adsorbent. Our work provides a new solution for the removal of radioactive uranium with high efficiency.

Analysis of Qatar's electricity landscape: Insights from load profiling, clustering, and policy recommendations

Demand side management (DSM) is an important strategy for promoting sustainable consumption in resource-rich countries with high purchasing power and subsidized tariffs. Global energy and environmental resource consumption have increased rapidly due to advances in production and transportation, leading to inefficient and wasteful use of resources. DSM aims to address these issues by promoting efficiency. To implement appropriate DSM strategies, a greater understanding of consumer behavior is needed. To do so, load profiling and load clustering are two popular methods that can be used. This paper aims to i) summarize the most recent global load profiling and clustering works ii) use official smart meter data to understand key electricity consumption trends in Qatar, such as temperature-demand correlation, weekend vs. weekday, and public holiday consumption patterns, and iii) perform load clustering to propose policies that would help manage the electricity load in Qatar for its green growth. This study provides insights into the electricity consumption trends of various sectors in Qatar, including commercial, government, hospitality, and residential sectors. It was found that among all the sectors there were only two usage periods of the same time. There is naturally a strong correlation between temperature and electricity consumption throughout the sectors. Furthermore, it was observed that the consumption of the sectors is highly similar which leads to multiple sectors being present in the same cluster. Finally, policy changes are proposed based on the results to encourage demand response programs in Qatar.

Enhanced conversion of rosin to polymerized rosin with reusable Brønsted acid deep eutectic solvent

With the depletion of non-renewable resources and the increasingly serious environmental problems, the production of high value-added polymer materials using renewable resources as raw materials had aroused great interest. Deep eutectic solvent (DES)-[ChCl][TfOH]2 (prepared by choline chloride (ChCl) and trifluoromethanesulfonic acid (TfOH)), with suitable acid strength (H0=0.98) and active hydrogen, had been successfully used for enhanced conversion of rosin to polymerized rosin efficiently, under the conditions of rosin =15 g, mDES: mrosin=30 %, T=110℃ and t=9 h, polymerized rosin with high softening point (150.40℃) and low acid value (124.21 mg KOH/g) could be produced efficiently. [ChCl][TfOH]2 required no special treatment then could be reused for 5 times without significant loss of catalytic performance, on this basis, the green synthesis technology of polymerized rosin under DES system was given, not only promoted the further application of polymerized rosin, but also realized the high value-added utilization of renewable resource rosin. In addition, the formation mechanism of DES was systematically explained through DFT calculation, the reaction mechanism of rosin polymerization over [ChCl][TfOH]2 was explored, which could provide theoretical basis for further research.

A resilient biofuel supply chain design based on Paulownia and Jatropha under uncertainty considering the water-energy nexus

The growth in global population, pollution, and energy demand, in addition to dwindling fossil fuel reserves, are driving scientists and industries toward adopting biomass-based products over non-renewable energy sources. Moreover, the decline of water resources and the importance of conserving water have induced governments to start initiatives to control the consumption of water, especially in the agricultural and industrial sectors. Therefore, the water-energy nexus is a significant issue that has drawn the interest of researchers in recent years. A bi-objective two-stage stochastic multi-product optimization model is presented for designing a resilient second-generation biofuel supply chain under uncertainty, considering the water-energy nexus. In this supply chain, biofuel is yielded from inedible plants Paulownia and Jatropha. Various resilience strategies are adopted to cope with potential disruptions to the supply chain, including multi-sourcing, capacity expansion, imports, multiple transportation modes, and lateral transshipment. The objectives of the model are twofold: maximizing profit and minimizing water consumption. This is achieved by making some key decisions including: facility location, managing the flows of raw materials and finished products among networks, determining production volumes, setting inventory levels, allocating land for biomass crop cultivation, planning production and storage capacities, scaling capacity expansions, the number of vehicles to rent or purchase, and optimizing the amounts of raw materials to import and biomass to export. An actual case study is provided to demonstrate the real-world applicability of the approach, while multiple sensitivity analyses are performed on the problem's main parameters. The study concludes by providing valuable managerial insights that focus on the cost savings and profit increases achievable through resilience strategies. The analysis considers different scenarios and explores effective methods for handling disruptions, emphasizing water resource conservation achieved by integrating the water-energy nexus within the biofuel supply chain.

Virtual Inertia Extraction from a DC Bus Capacitor in a Three−Phase DC/AC Inverter-Based Microgrid with Seamless Synchronisation Operation Modes

It is crucial to employ power electronics converters for energy transfer in distributed energy resources such as photovoltaics, and wind energy system. Thus, parameters such as voltage, current, active and reactive powers, and frequency referred to the AC side need to be controlled. The local load could be operated either from converter itself or grid, hence the system could be called microgrid. In this paper, the active and reactive powers would be controlled separately when the inverter is connected to the grid. While in the islanded or autonomous mode, the proposed control would support the voltage and frequency. The proposed controller would be designed and function as the synchronous machine’s voltage regulator and governor. The virtual synchronous machine is adopted to obtain the inertia and the concept is that the frequency of the grid is linked to the virtual frequency or so called the virtual speed of the rotor. The virtual frequency is obtained directly from the DC bus voltage of the inverter and this is achieved by allowing the DC link capacitor voltage to swing boarder than the grid frequency by making the capacitor voltage imitating frequency of grid. Where the frequency of grid is associated to the virtual frequency which is derived directly from DC capacitor voltage, thus, large level of inertia is extracted. The basic formulation, supervisory control, extraction the inertia from DC capacitor voltage, coordination transition, and evaluation the stability is presented in this paper. The mimic operation of the inverter as Synchronous Machine SM can make the distributed energy resources to be operated in either grid connected or islanded modes without the need to adopt control structure for the required mode. In addition, it provides robust performance in comparison with the traditional current, voltage and frequency control approaches. Moreover, the controller would be implemented for inverter having any type of filters and it is resilient to any variations in the filter and grid parameters. Furthermore, there is no concerning regarding instability problems, where it achieves the synchronisation smoothly and swiftly, and it is appropriate for implemented digitally.

A smart home energy management system based on human activity recognition and deep reinforcement learning

Smart home energy management systems (SHEMS) can help users save on energy costs by controlling various household loads in response to environmental changes. However, human activity is closely related to household energy consumption, which can lead to potential energy waste. Additionally, smart homes often feature multiple types of distributed energy resources (DER), and how to leverage their potential for participating in grid scheduling without significantly impacting users remains an unresolved issue. This paper proposes an intelligent home energy management method based on human activity recognition (HAR) and deep reinforcement learning. By using activity recognition results derived from intrusive load monitoring (ILM), we categorize contexts into two groups. The agent employs the soft actor-critic (SAC) algorithm for real-time control. In the first context, the goal is to ensure user satisfaction while reducing energy costs. In the second context, the focus is on controlling DER to participate in grid ancillary services to generate revenue. The proposed agent is trained using a real dataset, and simulations validate the effectiveness of the algorithm in home energy management.

Optimization of grid-connected hybrid renewable energy system for the educational institutes in Pakistan

To foster resilient energy transition systems, the deployment of renewable energy sources is potentially helpful in the acceleration towards sustainable, reliable, and diversified solutions. In this feasibility study, aims to pursuit the best optimal solution for renewable energy resources, integrated into the local university's energy mix, to meet the electrical load demand of 8500 kWhr/day and a peak load of 815 kW. A model of a hybrid grid-connected renewable energy (PV/Biomass/Hydel/Diesel generator/Grid) system was implemented in HOMER software, to obtain the most efficient and cost-effective hybrid energy generation. The outcomes of the simulation seem more viable based on sensitivity analysis, as the cost of energy (COE) for an energy system with a hybrid combination is 0.13.$/kWh, meanwhile energy price with the grid system is 0.18 $/kWh. According to the HOMER analysis, a hybrid grid-connected PV/biomass/hydro system demonstrates both technological feasibility and economic viability, meanwhile it will also save 1575 tons of CO2 per year. Therefore, this proposed hybrid energy system, a step towards sustainable development, can be applied at institutional levels, especially in developing countries.

Numerical investigation of combustion characteristics of hydrogen-enriched low calorific value landfill gas for energy applications

Landfill gas is regarded as a promising renewable energy resource. However, Low calorific value landfill gases with less than 40 vol% CH4 are not well suited for energy applications and therefore disposed by flaring or direct emission to atmosphere causing environmental problems. In the present work, the potential of using hydrogen-enriched low calorific value landfill gas for energy applications has been explored through numerical investigation of combustion characteristics of different blends of fuels. The ignition delay of fuel mixtures decreased with the increase of hydrogen fraction (H2 enrichment from 0 to 50 vol%) at stoichiometric conditions. At high initial pressure conditions, ignition delay showed a weak relationship with the pressure. The laminar burning velocity increased with the increment of hydrogen fraction for the range of equivalence ratios considered (φ = 0.7 – 1.4) and also with the increase of initial temperature. However, the laminar burning velocity decreased significantly with the increasing initial pressure and hydrogen enrichment has insignificant effect at high initial pressures. The sensitivity analysis shows that the main elementary reactions inhibit the laminar burning velocity more with increasing initial pressure. The combustion performance of low calorific value landfill gas with 30 vol% CH4 enriched with 30 vol% hydrogen shows comparable performance to biogas with 60 vol% CH4 for a range of operating conditions. The numerical investigation results show that hydrogen-enriched low calorific value landfill gas could be used for thermal applications with the use of suitably designed combustion systems operating at low initial pressures and relatively high initial temperatures.

Environmental acidification drives inter-organ energy mobilization to enhance reproductive performance in medaka (Oryzias latipes)

Anthropogenically environmental acidification impacts aquatic organisms, including teleosts, the largest group of vertebrates. Despite its significance, how teleosts allocate nutrient and energy among their organs to cope with acidic stress remains unclear. Our integrated analysis of physiological, metabolic, and gene expression data reveals that Japanese medaka (Oryzias latipes) mobilize energy resources among organs in response to acidic conditions. We found that the muscles lost carbohydrates and proteins and the liver accumulates all macronutrients in both sexes. Notably, female-specific energy mobilization between the liver and ovary were triggered by estrogen signaling, resulting in improved oocyte maturation and ovulation. Female produced more offspring under acidic stress. Furthermore, the offspring embryos exhibited smaller diameters and earlier hatching but demonstrated growth rates and acid tolerance. These metabolic changes suggest a trade-off in energy allocation by suppressing basal maintenance (33% decrease in oxygen consumption) and growth (25% decrease in muscle mass) but enhancing energy storage (159% increase in liver mass in males and 127% in females) and reproduction (165% increase in ovary mass). This reallocation may improve medaka fitness and population sustainability in acidic environments. Further investigation into more species is needed to project the survival of aquatic animals in an acidified future.

Plasma sprayed high-entropy alloy coatings with enhanced water splitting activity in alkaline environment

Developing highly efficient electrocatalysts for water splitting is an effective strategy to promote renewable and sustainable energy resources. Multimetal high-entropy alloys (HEAs) have generated considerable attention as promising catalysts because of their unique properties. Herein, the porous HEA coatings have been prepared via the plasma spraying method, which is expected to resolve the above issues. The catalysts can afford a promising catalytic performance through the distinct porous structure. This work results that the CoCrFeNiAlMo catalyst possesses a tiny overpotential (253mV at 50mAcm-2) with minimal Tafel slope (59.75mV dec-1). At the same time, the CoCrFeNiAlMo catalyst also exhibits a relatively small overpotential for hydrogen evolution reaction. As catalysts for overall water splitting, it delivers a cell voltage of 1.74V at 50mAcm-2 and a superior durable for 48h. This research provides an insight for using the multinary HEA coatings as electrocatalysts in energy applications.

Bi-level optimization of novel distribution network with VPP and flexible load cluster

To satisfy the power requirements of modern industrial parks, while also enhancing energy efficiency and system economy, a bi-level optimization model is proposed for a novel distribution network, which incorporates a virtual power plant (VPP) and flexible load cluster. The proposed optimization model for the distribution network layer considers factors such as minimum voltage offset and operating cost. It accounts for uncertainties associated with new energy sources, control of the soft open point (SOP), as well as dispatching of the static var compensator (SVC). A normalized normal constraint (NNC) method is used to obtain Pareto front. The power flow model is converted into a normalized cone programming model utilizing second-order cone relaxation technique. The VPP optimization layer aims to achieve the lowest operational cost and comprehensively considers the complementarity of multiple types of distributed energy resources. The bi-level iterative solution is obtained using the analytical target cascading (ATC) method. Finally, the enhanced IEEE 33-node system example demonstrates that the proposed bi-level optimization model effectively reduces the system’s operating cost, optimizes the power flow distribution, and minimizes network losses.

Pathways to China's Carbon Neutrality and Clean Energy Transition: Evidence from the Three Decades Long Stricter Environmental regulations

This study highlights the ongoing debate surrounding China's slow low-carbon transition despite a rapid shift towards clean energy. However, this debate is crucial for finding pathways to China's pledge to carbon neutrality. Using Auto-Regression Distributed Lag model over the time series data spanning 1990-2020, study attempts to add to the literature by exploring the nexus betwixt environmental regulations, renewable energy transition, and carbon dioxide emissions along with incumbent macroeconomic factors i.e., economic growth and trade. The findings conclude that stringent environmental regulations spur renewable energy transition and combat carbon dioxide emissions. However, energy intensive growth suggests China's priority for development targets ˗ leading to continued increase in fossil fuels despite the remarkable increase in renewable energy resources in country's total energy mix. Moreover, trade remains the crucial component of economic growth but found helping for renewable energy transition in the short-run. The two-way causality between these factors validate the regression results. Whereas the inelastic and insignificant relationship between stringent environmental regulations, renewables, and carbon dioxide emissions in the long run – highlights prospective challenges in terms of efficiency, management, and subsidy-related issues. Thus, the study suggest that trade liberalization helps the country to achieve its carbon abatement goals. However, further market based policy reforms toward stricter environmental regulations are needed for innovation driven efficiency in the energy sector.

The effects of sample preparation on the interpretation of pyrolysis-based organic matter analysis in immature oil shale

Oil shale as well as shale oil and shale gas are significant energy resources with huge reserves present in different parts of the world. Various geochemical proxies have been applied to assess the petroleum potential of oil shales with samples pre-treated in various ways, e.g. as whole rock or demineralized sample or as solvent extracted rock/kerogen. In this respect, it is important to understand and quantify, how achieved geochemical parameters are influenced by pre-treatment. In this study, a systematic comparison is presented based on a study on i) whole rock, ii) extracted whole rock, iii) kerogen concentrate, and iv) extracted kerogen concentrate obtained after solvent extraction of demineralized shales. In total, seven immature, organic matter-rich samples from the Miocene lacustrine sediments of the Nördlinger Ries impact crater, Germany, were pretreated in this way leading to overall 28 samples. A set of elemental analysis (C, H, N), Rock-Eval pyrolysis, and Curie Point-pyrolysis–gas chromatography–mass spectrometry measurements were performed on these pretreated samples. Mineral matter removal leads to significant increase of total organic carbon, but also thermally evaporable and pyrolytically cracked organic matter (Rock-Eval S1 and S2 peaks). To some extent, labile organic matter represented in the original S2 peak can be destructed by mineral removal with hydrochloric and hydrofluoric acid, as shown by elevated values of PI [S1/(S1 + S2)] after demineralization. The organic matter type tends to be more petroleum-prone with raised hydrogen index (HI) and aliphaticity values after demineralization, while Rock-Eval Tmax values commonly applied as parameters for thermal maturity tend to decrease, though not for all samples.Reduced TOC, S1, S2 and PI values of extracted samples suggest that both thermally evaporable and additionally some non-evaporable but soluble organic matter hidden in the original S2 peak can be lost after solvent extraction. Increased values of HI, H/C and N/C of extracted samples indicate more oil-prone organic matter types than unextracted samples. Typical maturity-related parameters such as aliphaticity and Rock-Eval Tmax decrease. Smectite and zeolites, which are abundant in the samples, are suggested to protect organic matter to some extent against solvent extraction, influencing a variety of geochemical proxies and the occurrence of metal cation-containing minerals. Zeolite invigorates the protection effect.

CO2 to fuel: Role of polymer electrolytes on efficiency and selectivity

Global primary energy consumption, which heavily depends on fossil fuels, is on track for depletion, with projections suggesting exhaustion by 2100. This trajectory is further compounded by the persistent rise in atmospheric CO2 levels, currently at 420 ppm, which significantly contributes to climate change and its detrimental environmental consequences. To address this urgent challenge, various strategies have been proposed, including CO2 capture and storage, as well as its conversion into usable fuels. Leveraging the abundance of CO2 as a carbon source, coupled with sustainable energy resources such as solar, wind, and thermal energy, holds promise for generating value-added goods while mitigating environmental harm. This review focuses on the electrochemical reduction of CO2, presenting a dual-pronged approach aimed at decreasing atmospheric CO2 levels. The imperative to simultaneously combat declining atmospheric CO2 concentrations and advance cleaner, sustainable energy sources underscores the urgency of this endeavor. Specifically, we highlight the pivotal role of diverse polymer electrolytes, encompassing cation, anion, and bipolar membranes, in facilitating electrochemical CO2 reduction. Exploring the impact of functional groups within these membranes on CO2 reduction reaction provides insights into potential advancements in synthesis of eco-friendly fuel from conversion of CO2.

A bibliometric analysis and visualization of sustainable production scheduling

Future shortage of material and energy resources also scarcity that might happen in manufacturing world have become public interest in world. This challenge build innovative needs like resource-efficient engineering, as the transition from a linear to a circular economy. There are more researches on energy-efficiency in many kind of manufacturing settings, including scheduling As a result, there have been numerous studies on sustainable production scheduling reviews, but only a few have documented the literature. This paper aims to provide summary of existing researches by bibliometric analysis. Bibliometrics is the interdisciplinary science of quantitative analysis of all knowledge carriers mathematical and statistical methods and a commonly used method of identifying developments from certain fields

Examining the nexus between carbon dioxide emissions, economic growth, fossil fuel energy use, urbanization and renewable energy towards achieving environmental sustainability in India

Purpose Global urbanization has accelerated due to the persistent trend of rural-to-urban migration in search of better prospects and livelihoods, which has had serious negative effects on the environment, especially in rapidly developing economies. Hence, the purpose of the study is to analyse the relationship between urbanization, economic growth, consumption of renewable energy and carbon emissions with careful examination, particularly in the context of India, where urban population growth has skyrocketed. Design/methodology/approach This study uses econometric methods like Granger causality analysis and the ARDL bound tests, to analyse the intricate relationships between the selected time series variables for India from 1970 to 2022. Findings This research highlights the difficult task of striking a balance between economic development and environmental preservation by emphasizing the crucial role that urbanization and economic expansion play in causing carbon emissions. India’s urbanization trajectory presents a significant policy problem that calls for a move towards renewable energy sources to successfully decrease carbon emissions. Moreover, this research indicates a two-way causal relationship between economic growth, urbanization and carbon emissions, pointing to the intricate interactions between these variables during the developmental stage. Research limitations/implications Despite India’s per capita emissions remaining below the global average, this study highlights the mounting policy challenge of balancing economic development with environmental sustainability as urbanization persists. The paper emphasizes the need for India to invest in renewable energy capacity to replace non-renewable sources and mitigate the carbon footprint of its growing energy demands. Collaborative efforts between India and the developed world to facilitate access to clean energy technologies are crucial for India to achieve sustainable growth in the long run. Originality/value To the best of the authors’ knowledge, existing literature predominantly focuses on investigating the relationship between renewable energy and economic growth, with only a limited number of studies exploring the impact on sustainable development to attain carbon neutrality. Furthermore, these studies have not considered the role of urbanization and non-renewable energy in addressing the challenge of sustainability issues in an emerging country like India. Hence, this study is a comprehensive study that addresses the research gap in these directions.