Research on total factor energy efficiency in western China based on the three-stage DEA-Tobit model

As an essential material basis and power source for economic and social development, Western China's low energy use efficiency has hindered its sustainable economic development. This study aims to evaluate the total factor energy efficiency of the region and identify its influencing factors. A three-stage DEA model was used to measure the efficiency of 11 provinces from 2006 to 2021, and the Tobit model was employed to investigate internal factors. The findings show that (i) external environmental factors and stochastic perturbations have a significant impact on TFEE in the western region, overestimating integrated efficiency and scale efficiency and underestimating pure technical efficiency. (ii) the study of external influencing factors finds that the level of economic development increases input redundancy; the industrial structure increases capital input and labor input redundancy while decreasing energy input redundancy; and the energy consumption structure increases capital input and energy input redundancy while decreasing labor input redundancy. (iii) the study of internal influencing factors finds that the level of scientific and technological innovation, the level of openness to the outside world, and the TFEE have a positive correlation. In contrast, the intensity of environmental regulation has a negative correlation.

Synergistic consideration of co-treatment of sewage sludge, low-rank coal, and straw for sustainable resource utilization and enhanced energy efficiency: a review

This article provides a comprehensive exploration of the imperative necessity for coupling the utilization of low-rank coal, sewage sludge, and straw. It studies the challenges and limitations of individual utilization methods, addressing the unique hurdles associated with feedstocks. It focused on achieving integrated and sustainable resource management, emphasizing efficient resource utilization, waste minimization, and environmental impact reduction. The investigation extends to the intricate details of reaction processes in co-processing, with a specific emphasis on the drying of raw materials to enhance combustion characteristics. The molding and preparation of feedstock are dissected, encompassing raw material selection, mixing, and the crucial addition of additives and binders. The proportions and homogenization of these feedstocks are intricately examined for uniformity and effectiveness. Furthermore, it presents theoretical approaches for investigating the co-combustion of these diverse feedstocks, contributing a solid foundation for future studies in this dynamic field. The findings presented in it offer valuable insights for researchers, practitioners, and policymakers seeking sustainable solutions in the co-disposal technology of these feedstocks. Therefore, it provides a holistic understanding of the challenges and opportunities in coupling the utilization of these selected feedstocks. By addressing individual limitations and emphasizing integrated resource management, the article establishes the groundwork for sustainable and efficient co-processing practices. The exploration of reaction processes gives a comprehensive framework for future research and application in the field of co-combustion technology. The insights gleaned from this study contribute significantly to advancing knowledge in the sustainable utilization of diverse feedstocks, guiding efforts towards environmentally responsible and resource-efficient practices.

A new strategy for improving the energy efficiency of electro-Fenton: Using N-doped activated carbon cathode with strong Fe(III) adsorption capacity to promote Fe(II) regeneration

Fe(II) regeneration plays a crucial role in the electro-Fenton process, significantly influencing the rate of ·OH formation. In this study, a method is proposed to improve Fe(II) regeneration through N-doping aimed at enhancing the adsorption capacity of the activated carbon cathode for Fe(III). N-doping not only enriched the pore structure on the surface of activated carbon, providing numerous adsorption sites, but also significantly increased the adsorption energy for Fe(III). Among the types of nitrogen introduced, pyridine-N exhibited the most substantial enhancement effect, followed by pyrrole-N, while graphite-N showed a certain degree of inhibition. Furthermore, N-doping facilitated the adsorption of all forms of Fe(III) by activated carbon. The adsorption and electrosorption rates of the NAC-900 electrode for Fe(III) were 30.33% and 42.36%, respectively. Such modification markedly enhanced the Fe3+/Fe2+ cycle within the electro-Fenton system. The NAC-900 system demonstrated an impressive phenol degradation efficiency of 93.67%, alongside the lowest electricity consumption attributed to the effective "adsorption-reduction" synergy for Fe(III) on the NAC-900 electrode. Compared to the AC cathode electro-Fenton system, the degradation efficiency of the NAC-900 cathode electro-Fenton system at pH = levels ranging from 3 to 5 exceeded 90%; thus, extending the pH applicability of the electro-Fenton process. The degradation efficiency of phenol using the NAC-900 cathode electro-Fenton system in various water matrices approached 90%, indicating robust performance in real wastewater treatment scenarios. This research elucidates the impact of cathodic Fe(III) adsorption on Fe(II) regeneration within the electro-Fenton system, and clarifies the influence of different N- doping types on the cathodic adsorption of Fe(III).

Impacts of digital finance on energy efficiency: does environmental regulation matter?

The paper examines how digital finance affects energy efficiency in China using a dynamic panel model and data from 282 cities between 2011 and 2019. The study is based on the hypothesis which is related with digital finance, environmental regulation, and energy efficiency. The results indicate that: (1) Digital finance significantly improves energy efficiency, and this finding is consistent after several tests; (2) Digital finance has a positive effect on energy efficiency in non-resource-based cities, recession and regeneration resource-based cities, and old industrial base cities, but no significant effect on energy efficiency in growth and maturity resource-based cities and non-old industrial base cities; (3) Environmental regulation positively influences how digital finance affects energy efficiency; (4) The impact of digital finance on energy efficiency depends on the degree and tools of environmental regulation. This research offers valuable insights to local governments in China for promoting financial digitization and enhancing energy efficiency.

An energy efficiency assessment of Yttrium-aluminum-garnet laser in vitro

To study the effect range of the Nd:YAG laser through various levels of cloudy medium for targets with varying grayscale values in vitro. The coated paper cards with grayscale values of 0, 50, 100, and 150 were used as the laser's targets, which were struck straightly with varying energies using three burst modes (single pulse, double pulse, and triple pulse). Six filters (transmittances of 40, 50, 60, 70, 80, and 90) were applied to simulate various levels of cloudy refractive medium. Image J software was used to measure the diameters and regions of the laser spots. The ranges of the Nd:YAG laser spots increased with energy in the same burst mode (P < 0.05). Under the same amount of energy, the ranges of the Nd:YAG laser spot increased with the grayscale value of the targets (P < 0.05). The greater the transmittance of the filters employed, the larger the range of the Nd: YAG laser spots produced. Assuming that the total pulse energy is identical, the effect ranges of multi-pulse burst modes were significantly larger than those of single-pulse burst mode (P < 0.05). The effect range of a Nd:YAG laser grows with increasing energy and the target's grayscale value. A cloudy refractive medium has a negative impact on the effect range of the Nd: YAG laser. The single pulse mode has the narrowest and safest efficiency range.

The impact of green innovation resilience on energy efficiency: A perspective based on the development of the digital economy

As digital economy develops, its impact on green innovation and energy efficiency has become the focus of current research. To explore the impact of the current development of the digital economy on the energy industry, this paper selects the parameter of green innovation resilience, analyzes the impact mechanism of green innovation resilience on energy efficiency under the shock of digital economic development, and uses relevant data from 284 cities in China from 2011 to 2019 for empirical testing. It is found that: green innovation resilience promotes energy efficiency; low level of green innovation resilience inhibits the improvement of energy efficiency, while high level of resilience promotes energy efficiency; the initial stage of digital economic development generates resource grabbing and the effect of technological constraints, which weakens the role of green innovation resilience in promoting energy efficiency. The results indicate that the resilience of the green innovation system should be strengthened in order to fully tap the potential for promoting energy efficiency; the policy orientation of "digital greening-energy efficient" should be pursued in the development of digital economy; the rational allocation of resources and the implementation of green standards should be strengthened in the process of digital economic development; and the constraints on energy efficiency improvement in the early stage of digital economic development should be broken through by accelerating the digitalization process.

Co-hydrothermal carbonization with process water recirculation as a valuable strategy to enhance hydrochar recovery with high energy efficiency

This study aims at valorizing the residual aqueous phase from hydrothermal carbonization (HTC) of Sicilian agro-wastes in order to enhance the hydrochar recovery, positively affecting the process energy balance. Process waters (PW) obtained from HTC and co-HTC using orange peel waste and fennel plant residues were used as recycled solvent in experiments carried out at the temperatures of 180 and 230 °C. The results showed that an additional hydrochar formation was promoted during recirculation of solvent, leading to average increments of solid mass yield of 10.5 wt% for tests conducted at 180 °C and 3.9 wt% for 230 °C. After five consecutive recirculation phases in co-HTC runs, the hydrochar yield increased up to 18.2 wt%. The low H/C and O/C atomic ratios values, found after recirculation, indicate that organic acids, accumulated in the PW, may catalyze the process and promote the biomass deoxygenation by boosting dehydration and decarboxylation. The recovered PWs from conversion steps with deionized water were also carbonized in absence of the solid feedstock in order to quantify their contribution in hydrochar formation during recirculation and thus the synergistic interactions. After recirculation, energy recovery averagely augmented by more than threefold, showing that the proposed strategy could significantly improve the sustainability of HTC.

Improved walking energy efficiency might persist in presence of simulated full weight regain after multidisciplinary weight loss in adolescents with obesity: the POWELL study

AIM

Weight loss leads to a reduction of the energy cost of walking but the respective implications of the metabolic and mechanic changes remain unknown. The present study compares the post-weight loss energy cost of walking (Cw) with and without a total reload of the induced weight reduction in adolescents with obesity.

METHODS

Energy cost of walking and substrate use were evaluated during a graded walking exercise (4×6-min at 0.75, 1, 1.25, 1.5 m.s-1) before (V1) and after a 12-week intervention in 21 adolescents with obesity (11 girls; 13.8 ± 1.4 y). After weight loss, the walking exercise was randomly repeated once without weight reload (V2) and once with a loading corresponding to the total induced weight loss during the program (V2L). Body composition was assessed before and after the intervention.

RESULTS

Body weight and fat mass decreased in response to the 12-week intervention (p < 0.001), while FFM did not change. The absolute gross Cw (ml.m-1) was higher on V1 compared with V2 at every speed. The absolute net Cw (ml.m-1) was higher on V1 compared to V2L at 0.75 m.s-1 (p = 0.04) and 1 m.s-1 (p = 0.02) and higher on V2L compared with V2 at 1.5 m.s-1 (p = 0.03). Net Cw (ml.m-1.kg-1) on V1 being higher than V2 (p < 0.001), and V2L higher than V2 (p = 0.006). The absolute CHO oxidation (mg.min-1) did not show any condition effect (p = 0.12) while fat utilization was higher on V1 compared to V2 and V2L (p < 0.001). Relative to body weight CHO oxidation was lower on V1 compared to V2 (p = 0.04) and V2L (p = 0.004) while relative to body weight fat oxidation was higher on V1 than V2 (p = 0.002).

CONCLUSION

Adolescents with obesity might not show an entire rise back to pre-weight loss values of their metabolic cost of walking when weight gain is simulated. These new findings suggest metabolic and physiological adaptations to weight loss of the energy metabolism that remain to be clarified.

Can digitalization effectively promote green energy efficiency? The linear and nonlinear relationship analysis

In light of the integration of digitalization and the energy revolution, digitalization can be integrated into the energy industry to develop energy-saving technologies and improve resource allocation efficiency. On the basis of 2013-2019 Chinese provincial panel data, this paper measures the level of green energy efficiency based on the super-EBM-DEA model and analyzes the linear relationship, nonlinear relationship, and potential mechanism between digitalization and green energy efficiency. The findings indicate that (1) overall, both China's digitalization and green energy efficiency formed a steady upward trajectory during the sample period. Digitalization showed a spatial characteristic of extending and spreading from the eastern region to the central and western regions. Green energy efficiency was characterized by obvious regional heterogeneity. (2) Progress in digitalization has a significant driving effect on green energy efficiency. Subdimensional analysis shows that this driving effect mainly comes from digital development and digital transactions. (3) The impact of digitalization on green energy efficiency presents a threshold effect of economic agglomeration (with a threshold of 0.0257 and a marginally increasing, positive driving trend) and population agglomeration (with a threshold of 4.2750 and a marginally decreasing, positive driving trend). (4) Decomposing changes in green energy efficiency into scale efficiency and pure technical efficiency, this study shows that pure technical efficiency gains due to digitalization are the main driver of green energy efficiency improvements. Finally, some specific policy recommendations are proposed.

Renewable energy technology innovation and urban green economy efficiency

Green economy efficiency is the core-factor of urban economic and environmental development. As a sustainable instruments, renewable energy technology innovation (RETI) not only reflects the low energy-consumption, but also promotes the reasonable and balanced relationship between resources utilization and urban economy. In this regard, this paper selects China's cities to investigate the effect of RETI on urban green economy efficiency from 2004 to 2020 based on theoretical analyses and previous studies. The paper finds that RETI can promote urban green economy efficiency significantly, passing a series of robustness test, and its effect has connected differently with the factor of regional factor, cleaner production level and environment pollution. Meanwhile, RETI promotes urban green economy efficiency by reducing CO2 emission and polluting manufacturing agglomeration. To date, this study has discovered the green economy efficiency improvement effects of RETI, providing theoretical basis and practical recommendations for government, technological agency and urban industries.

Optimizing energy efficiency in heterogeneous networks: An integrated stochastic geometry approach with novel sleep mode strategies and QoS framework

The quest for energy efficiency (EE) in multi-tier Heterogeneous Networks (HetNets) is observed within the context of surging high-speed data demands and the rapid proliferation of wireless devices. The analysis of existing literature underscores the need for more comprehensive strategies to realize genuinely energy-efficient HetNets. This research work contributes significantly by employing a systematic methodology, utilizing This model facilitates the assessment of network performance by considering the spatial distribution of network elements. The stochastic nature of the PPP allows for a realistic representation of the random spatial deployment of base stations and users in multi-tier HetNets. Additionally, an analytical framework for Quality of Service (QoS) provision based on D-DOSS simplifies the understanding of user-base station relationships and offers essential performance metrics. Moreover, an optimization problem formulation, considering coverage, energy maximization, and delay minimization constraints, aims to strike a balance between key network attributes. This research not only addresses crucial challenges in creating EE HetNets but also lays a foundation for future advancements in wireless network design, operation, and management, ultimately benefiting network operators and end-users alike amidst the growing demand for high-speed data and the increasing prevalence of wireless devices. The proposed D-DOSS approach not only offers insights for the systematic design and analysis of EE HetNets but also systematically outperforms other state-of-the-art techniques presented. The improvement in energy efficiency systematically ranges from 67% (min side) to 98% (max side), systematically demonstrating the effectiveness of the proposed strategy in achieving higher energy efficiency compared to existing strategies. This systematic research work establishes a strong foundation for the systematic evolution of energy-efficient HetNets. The systematic methodology employed ensures a comprehensive understanding of the complex interplay of network dynamics and user requirements in a multi-tiered environment.

Ecological footprint in the OECD countries: do energy efficiency and renewable energy matter?

Ecological footprint (EFP) measures the amount of area, that is land or sea, which is required to absorb the waste generated through human activities or to support the production of resources consumed by populations. EFP index therefore includes six dimensions that are cropland, forestland, carbon, fishing grounds, grazing land, and built-up area. Human activities have impacted the environment, leading to global warming, widespread droughts, and diseases. The present study aims to investigate the role of renewable energy (RE) and energy efficiency on the EFP index. Past researchers have widely used carbon emission (CE) to represent environmental impact, and recent studies have shown that EFP index is a better proxy of environmental degradation. Therefore, the present research differs from past studies in that it compares on how the determinants of environmental degradation affects EFP index and CE. Panel dataset of the OECD countries from 1990 to 2020 is employed. The CS-ARDL, DCCEMG, and AMG techniques, which overcome dynamics, heterogeneity, and cross-sectional dependence, are employed. The main findings depict that RE significantly reduces EFP and CE, while economic growth significantly exacerbates them. Energy efficiency reduces CE, but does not significantly affect EFP. Non-renewable energy and research & development significantly increase CE, while an insignificant positive effect is observed with EFP. This paper shows that factors that significantly influence CE may not always significantly affect the EFP index. Thus, to reduce environmental degradation it is fundamental to understand on how each dimension of EFP is influenced.

Integrating wet stirred-bead milling for Tetraselmis suecica biorefinery: Operating parameters influence and specific energy efficiency

Stirred bead milling proved to be an efficient cell destruction technique in a biorefinery unit for the extraction of over 95 % of proteins and 60 % of carbohydrates from the green marine microalga Tetraselmis suecica. Optimum conditions, expressed in terms of metabolite yield and energy consumption, were found for average values of bead size and agitator rotation speed. The higher the microalgae concentration, up to 100 g.L-1, which is adequate for biofilm algae growth in an industrial unit, the more efficient the cell destruction process. Cell destruction rates and metabolite extraction yields are similar in pendular and recycling modes, but the pendular configuration reduces the residence time of the suspension in the grinding chamber, which is less costly. With regard to the cell destruction mechanism, it was concluded that bead shocks first damage cells by permeabilizing them, and that after a longer period, all cells are shredded and destroyed, forming elongated debris.

Dynamic spillover effects of renewable energy efficiency in the European countries

Renewable energy has gained significant attention due to the growing concern for environmental sustainability and the high reliance on energy imports in European countries. In this study, we use a two- stage approach to assess renewable energy efficiency (REEF) of European countries. Initially, we employ the data envelopment analysis (DEA) method to quantify the efficiency of renewable energy. Subsequently, we investigate the factors influencing REEF between 2005 and 2020. Our findings reveal a generally high level of REEF across European countries, but some countries have become worse in this regard (e.g., France, Ukraine, Russia, Belgium, Germany, Norway, and Serbia). In order to find the causes of these changes, we considered the explanatory variables of gross domestic product (GDP), energy price, renewable energy consumption, information and communications technology (ICT), and industrial value added in a spatial system generalized method of moments (spatial SYS-GMM) model. The findings provide confirmation of the spatial spillover effects of REEF within European countries. The strongest positive effect is related to energy prices. In simpler terms, as energy prices rise, the efficiency of renewable energy has increased in European countries. Additionally, ICT and renewable energy consumption have positive impacts, too. But GDP and industrial value added, have decreasing effects. Based on these findings, we put forth several policy suggestions aimed at enhancing the efficiency of renewable energy in European countries.

Energy efficient virtual machines placement in cloud datacenters using genetic algorithm and adaptive thresholds

Cloud computing platform provides on-demand IT services to users and advanced the technology. The purpose of virtualization is to improve the utilization of resources and reduce power consumption. Energy consumption is a major issue faced by data centers management. Virtual machine placement is an effective technique used for this purpose. Different algorithms have been proposed for virtual machine placement in cloud environments. These algorithms have considered different parameters. It is obvious that improving one parameter affects other parameters. There is still a need to reduce energy consumption in cloud data centers. Data centers need solutions that reduce energy consumption without affecting other parameters. There is a need to device solutions to effectively utilize cloud resources and reduce energy consumption. In this article, we present an algorithm for Virtual Machines (VMs) placement in cloud computing. The algorithm uses adaptive thresholding to identify over utilized and underutilized hosts to reduce energy consumption and Service Level Agreement (SLA) violations. The algorithm is validated with simulations and comparative results are presented.

Evaluating the impact of technological innovation and energy efficiency on load capacity factor: empirical analysis of India

The determinants of environmental degradation have been investigated many times by utilizing carbon dioxide emissions and/or ecological footprint. However, these traditional environmental degradation indicators do not consider the supply side of environmental problems. Therefore, this study focuses on the dynamic influence of financial development, energy efficiency, economic growth, and technological innovation on environmental degradation in India through the load capacity factor, including both the supply and demand sides of environmental problems. For that purpose, the recently developed dynamically simulated autoregressive distributed lag (ARDL) method is employed using the annual time-series data extending from 1980-2020. The dynamically simulated ARDL results demonstrate that financial development, economic growth, and technological innovation have a dynamic adverse impact on the load capacity factor, whereas energy efficiency has a positive dynamic influence on environmental quality. In addition, the results support the validity of the environmental Kuznets curve hypothesis as the negative effect of economic growth on environmental quality decreases over time. Based on the study findings, policy recommendations are provided for India. Finally, this study utilizing load capacity factor as an indicator for environmental quality will provide new topics in exploring the determinants of environmental degradation.

Impact of the digital economy on total factor energy efficiency: evidence from 268 Chinese cities

Due to the advancement of digital technology, the digital economy has developed rapidly, profoundly changing human production and lifestyles, thereby promoting the dual digital transformation of the energy supply and demand sides and having a profound impact on energy utilization efficiency. Based on measuring the total factor energy efficiency (TFEE) of 268 cities in China from 2011 to 2019, we analyze the total and indirect effects of the digital economy on TFEE using a mediated effects model and examine the effects of urban heterogeneity from the perspectives of geographical location, city size, and resource endowment. The results show that the digital economy has a significant positive contribution to TFEE. In addition, the digital economy can promote TFEE through industrial structure upgrading, technological innovation, and environmental regulation. The test results of the subsample show that there is significant heterogeneity in the impact and mechanism of action of the digital economy on TFEE in different geographical locations, city sizes, and resource endowments. By understanding how the digital economy impacts TFEE, policymakers can formulate effective policies to simultaneously accelerate digital economy development and improve TFEE.

Does industrial co-agglomeration promote green energy efficiency? Evidence from spatial panel data of 284 cities in China

Industrial co-agglomeration (IC) plays a pivotal role in the development of local and adjacent green energy efficiency across 284 Chinese cities, encompassing both resource-based and non-resource-based urban centers. Based on the panel data of 284 cities in China from 2005 to 2020, this study employs spatial econometric methods to empirically assess the influence of IC and its spillover effects on green energy efficiency, employing a spatial Durbin model. Additionally, the study categorizes the 284 Chinese cities into resource-based and non-resource-based categories, utilizing spatial econometric methods to delve into the heterogeneity of their effects and spillover impacts. The key findings are as follows: (1) The average green energy efficiency across the 284 Chinese cities from 2005 to 2020 stands at 0.5834. The trend in IC indicates growth and concentration towards the central areas, increasing from 2.7396 in 2005 to 2.7658 in 2020. (2) The IC, with a coefficient of 0.0918, promotes the local green energy efficiency. (3) There are spillover effects of local IC on the green energy efficiency in adjacent areas with a coefficient of 0.2550 and an Indirect Effect of 0.4567. (4) In resource-based cities, IC positively impacts local green energy efficiency with a coefficient of 0.1056 but negatively affects green energy efficiency in adjacent areas with a coefficient of -0.1368. In non-resource-based cities, IC enhances green energy efficiency in adjacent cities with a coefficient of 0.1335. Consequently, the study offers pertinent policy recommendations aimed at improving energy efficiency in light of these findings.

Energy efficiency and country's level risk: evidence from China's targeting COP26

Country risk, encompassing political, economic, and financial dimensions, represents a burgeoning area of research in contemporary academia. However, its relation with energy technology remains relatively unexplored. Unlike previous studies, the current study enhances the extant literature by investigating the influence of political, economic, and financial risk factors, in addition to GDP, on energy technology advancements within the context of China from 1990 to 2021. The authors employ time series data and select the most suitable econometric techniques for analyzing long-term relationships, such as quantile regression. This approach allows them to track the evolution of these variables, thereby offering valuable empirical insights. The study's main findings are as follows: The Johansen cointegration tests confirm the existence of a long-run relationship among the variables under consideration. Furthermore, the quantile regression shows that political and economic risks reduce energy technology. In contrast, other variables, such as financial risk and GDP contribute positively to developing energy technology within the Chinese economy. These findings offer valuable insights for policymakers emphasizing the need to mitigate political and economic risks to facilitate future investment in energy technology.

Viscoelastic materials are most energy efficient when loaded and unloaded at equal rates

Biological springs can be used in nature for energy conservation and ultra-fast motion. The loading and unloading rates of elastic materials can play an important role in determining how the properties of these springs affect movements. We investigate the mechanical energy efficiency of biological springs (American bullfrog plantaris tendons and guinea fowl lateral gastrocnemius tendons) and synthetic elastomers. We measure these materials under symmetric rates (equal loading and unloading durations) and asymmetric rates (unequal loading and unloading durations) using novel dynamic mechanical analysis measurements. We find that mechanical efficiency is highest at symmetric rates and significantly decreases with a larger degree of asymmetry. A generalized one-dimensional Maxwell model with no fitting parameters captures the experimental results based on the independently characterized linear viscoelastic properties of the materials. The model further shows that a broader viscoelastic relaxation spectrum enhances the effect of rate-asymmetry on efficiency. Overall, our study provides valuable insights into the interplay between material properties and unloading dynamics in both biological and synthetic elastic systems.

Platform economy development and energy efficiency inequality: evidence from China

Alleviating energy efficiency inequality between regions is critical for achieving green sustainable development and environmental equality. This study constructs platform economy development index and adopts Theil index to measure energy efficiency inequality. By using panel data from 30 regions in China spanning from 2013 to 2020, this study investigates the influence of platform economy development on energy efficiency in inequality through a two-way fixed-effects model. The results show that (1) platform economy development can alleviate energy efficiency inequality between regions. After the robustness tests, the results still support the findings. (2) When the level of industrial agglomeration, marketization and environmental decentralization is high, platform economy development is more effective in alleviating energy efficiency inequality. (3) Platform economy development can optimize energy resources allocation, promote energy utilization technology flow and narrow the green finance development gap, thus alleviating energy efficiency inequality. Governmental departments should promote platform economy development and green finance, and optimize renewable energy allocation.

Nexus between energy efficiency, green investment, urbanization and environmental quality: Evidence from MENA region

Environmental protection holds a paramount position in the pursuit of sustainable development. The existing body of literature has extensively examined various driving forces for environmental enhancement, including renewable energy sources, innovation, and governmental interventions. This study aims to assess the impact of green investment, energy efficiency, and urbanization on achieving environmental sustainability in the MENA region during the period 2004-2019. A comprehensive set of econometric tools has been employed to achieve this goal, including the CADF and CIPS panel unit root tests, error correction-based panel cointegration analysis, Cross-sectional ARDL, and asymmetric ARDL models. The key findings of this research are as follows: Cross-sectional dependency and homogeneity tests demonstrated that the research units shared common dynamics and heterogeneity properties. The stationarity tests based on CIPS and CADF indicated that all variables became stationary after the first differencing. The panel cointegration analysis established a long-term relationship between green investment (GI), energy efficiency (EE), urbanization (UR), and environmental sustainability (ES) in MENA nations. Empirical model estimations using Cross-sectional ARDL revealed significant contributions of GI, EE, and UR to ES in the long and short run. The asymmetry assessment uncovered a nonlinear relationship between the explanatory and dependent variables, both in the long and short run. Specifically, the asymmetric coefficients of GI, EE, and UR displayed negative statistical significance at the 1% level, highlighting their significant roles in promoting environmental sustainability. In light of these findings, this study provides valuable insights for policymakers to formulate strategies to further environmental sustainability in the MENA region.

Energy efficient gateway based routing with maximized node coverage in a UAV assisted wireless sensor network

Ad-hoc wireless sensor networks face challenges of optimized node deployment for maximizing coverage and efficiently routing data to control centers in post disaster events. These challenges impact the outcome for extending the lifetime of wireless sensor networks. This study presents a uav assisted reactive zone based EHGR (energy efficient hierarchical gateway routing protocol) that is deployed in a situation where the natural calamity has caused communication and infrastructure damage to a major portion of the sensor network. EHGR is a hybrid multi layer routing protocol for large heterogeneous sensor nodes (smart nodes, basic nodes, user handheld devices etc.) EHGR is tailored to meet two important concerns for a disaster hit wsn ie. optimized deployment and energy efficient routing. The first part of EGHR focuses on maximized coverage during node deployments. Maximized coverage is an important aspect to be considered during the event of disaster since most of the nodes loose coverage and are detached from the wireless sensor network. The first part of EHGR uses state of the art game theory approach to build a model that maximizes the coverage of nodes during the deployment phase from all participating entities i.e. nodes and uavs. Rather than fixing the cluster head as is the case in traditional cluster-based approaches EHGR uses the energy centroid nodes. Energy centroid nodes evolve on the basis of aggregated energy of the zone. This approach is superior to simply electing cluster head nodes on the basis of some probability function. The nodes that fail to achieve any successful outcome from the game theory matching model fail to get any association. These nodes will use multi hop d2d relay approach to reach the energy centroid nodes. Gateway relay nodes used with the game theory approach during the deployment of the uav assisted wsn improves the overall coverage by 25% against traditional leach based hierarchical approaches. Once the optimum deployment phase is completed the routing phase is initiated. Aggregated data is sent by the energy centroid nodes from the ECN nodes to the servicing micro controller enabled un manned aerial vehicles. The routing process places partial burden of zone formation and data transmission to the control center for each phase on the servicing uavs. Energy centroid nodes engage only in the data aggregation process and transmission of data to servicing uav. Servicing-uavs reduce energy dissipated of the entire zone which result in gradual decrease of energy for the zone thus increasing the network lifetime. Node deployment phase and the routing phase of EHGR utilize the computations provide by the mirco controller enabled unmanned aerial vehicles such that the computationally intensive calculations are offloaded to the servicing uav. Experiment results indicate an increase in the first dead node report, half dead node report, and last dead node report. Network lifetime is extended to approximately 1800 rounds which is an increase by ratio of 100% against the traditional leach approach and increase by 50% percent against the latest approaches as highlighted in the literature.

Pathways to improve energy efficiency under carbon emission constraints in iron and steel industry: Using EBM, NCA and QCA approaches

Improving environmental performance of energy- and carbon-intensive sectors represented by the iron and steel (IS) industry is of utmost importance to address the challenges of resource depletion and climate change worldwide. This article adopts a global-super-Epsilon-Based Measure (EBM) model with undesirable output for IS energy efficiency estimation, identifies efficiency determinants based on Technology-Organization-Environment (TOE) framework, and analyzes various pathways for efficiency improvement by grouping Necessary Condition Analysis (NCA) and fuzzy-set Qualitative Comparative Analysis (fsQCA). Empirical testing using statistical data of the G20 economies during 2010-2020 demonstrates that: 1) energy efficiency in the IS industry in G20 countries has risen amidst fluctuations, with developed countries performing more efficiently than developing countries; 2) individual factors do not constitute a compulsory condition to achieve high energy efficiency in the IS industry; 3) three different paths to achieve high energy performance are found, that is, technology-structure driven, regulation-economy-technology driven, and regulation-technology-production driven. Heterogenous policy recommendations for efficiency gains in the IS sector of different countries with divergent features are proposed accordingly.

Role of green financial assets, financial technology and the green energy on the development of a green economy

A major issue for governments in the past few decades has been environmental deterioration caused by economic activity. Researchers are increasingly interested in the factors that contribute to environmental deterioration. The study aims to test the role of green bond financing on energy efficiency investment and economic growth. In this investigation, we use the ARDL estimator to investigate the relationships between the financial technology, green bonds, green stock, green supply chain and the development of green energy. The importance of green supply chain, green energy, green bonds and financial technology has been identified as major variables. According to the study's findings, green supply chain, green finance and sustainable economic growth are all essential and positive indicators of a composite assessment of sustainable practices. Green bonds, reducing greenhouse gas emissions and green economic development all play a necessary part in green finance development.

Does higher energy efficiency growth homogeneously affect carbon emission growth rate across developing Sub-Saharan African nations? The importance of utilizing clean energy

Establishing a sustainable environment and acquiring a carbon-neutral status require Sub-Saharan African nations to reduce their year-on-year growth rates of carbon emission levels. Thus, this study considers a sample of 38 countries from this region and selects the time period from 2000 to 2020 for analyzing the annual carbon emission growth rate influencing impacts of energy efficiency, clean energy, institutional quality, international trade, and net receipts of foreign direct investment. Overall, for the full sample of Sub-Saharan African nations, the results verify that the enhancing the growth rate of energy efficiency improvement reduces both total and per capita annual carbon emission growth rates. Besides, the results endorse that enhancing renewable energy shares of the final energy consumption profiles and promoting good governance-led betterment of institutional quality also plunge emission growth rates in the long run. More importantly, energy efficiency improvement, renewable energy consumption, and better quality institutions are observed to jointly exert carbon emission growth rate-impeding effects, as well. By contrast, more openness to international trade is not seen to influence the carbon emission growth rates of the Sub-Saharan African nations of concern. Lastly, a greater share of net foreign direct investment receipts in the national output level is evidenced to boost annual carbon emission growth rates across this region; consequently, the pollution haven hypothesis is verified. Furthermore, these above-mentioned findings are found to be heterogeneous across groups of low-income and middle-income Sub-Saharan African nations. Accordingly, in line with the findings, a couple of policies are recommended to the governments of the Sub-Saharan African countries in order to guide them in designing effective environmental sustainability policies that are relevant for tackling climate change-related atrocities in the future.

The relationship between entrepreneurial energy efficiency orientation and carbon footprint reduction: The mediating role of green networking and identification of barriers to green practices

Motivated by the growing attention to climate change and the crucial role businesses could play in reducing greenhouse gas emissions, this study investigates entrepreneurial energy efficiency orientation in the context of carbon footprint reduction initiatives of small-and medium-sized enterprises (SMEs). We enhance understanding of the climate change action of SMEs by taking into account the mediating mechanisms (i.e., identification of green barriers and green networking) through which firm entrepreneurial energy efficiency orientation leads to superior carbon footprint reduction initiatives by overcoming barriers to green practices. A survey of 252 SME owners and top managers in the Tees Valley region, Northeast England, supported the direct impact of entrepreneurial energy efficiency orientation on overcoming barriers to green practices and the mediating role of identification of green barriers and green networking in this focal relationship. These findings reveal the importance of entrepreneurial energy efficiency orientation, identification of green barriers and green networking in helping SMEs overcome barriers to green practices and improving carbon footprint reduction initiatives.

Design and process parametric investigations on acrylic-based single slope solar still to enhance daily energy efficiency and productivity of water: an application to desalination and dye removal

Solar-driven water desalination is growing quickly, typically using other renewable energy sources. However, its efficiency is heavily reliant on design and process parameters. The aim of this study is to experimentally investigate the impact of various design and process parameters on the performance of single slope solar still. Thus, a homemade solar still has been fabricated using acrylic sheet with a basin area of 0.25 × 0.25 m2 to carry out the experiments in Vellore, India (latitude 12.9692° N and longitude 79.1559° E). Additionally, this solar still setup is investigated using different absorbing plates (copper plate and copper plate with black coating), various glass cover angles (15°, 30° and 45°) and changing the wind speed (3 m/s, 3.5 m/s and 4 m/s) with help of electric fan. Daily energy efficiency and productivity of water are compared for the same basin area with different design and process parameters. From the results, daily energy efficiency and water productivity are improved with the increase of glass cover angle and wind speed. It is found that the best combination is copper plate with black coating, glass cover angle of 45° and wind speed of 4 m/s. This exhibits 34.09% in daily energy efficiency and 2640 ml/m2 in productivity of water. After the desalination process, the primary ions (Na+, K+, Mg2+, and Ca2+) of seawater are significantly reduced and satisfy the requirement of WHO standards. Subsequentially, dye removal is effectively achieved in the proposed solar still.

Promotion of bio-oil production from the microwave pyrolysis of cow dung using pretreated red mud as a bifunctional additive: Parameter optimization, energy efficiency evaluation, and mechanism analysis

To address the issues of high oxygen content and energy consumption in the microwave-assisted pyrolysis of biomass for biofuel production, this study used high-temperature pretreated red mud (RM) as an additive. The pretreated RM exhibited dual functionalities, namely microwave absorption and catalytic properties, during the microwave-assisted pyrolysis of cow dung (CD). This study also evaluated the optimization potential of energy recovery efficiency. The results showed that the addition of pretreated RM significantly increased the oil yield during the microwave-assisted pyrolysis of CD. The highest oil yield (59.63%) was obtained via the microwave-assisted pyrolysis of CD over catalysis with RM pretreated at 750 °C (RM750). Through the optimization of the RM750-to-CD mixing ratio, optimal oil quality and energy recovery efficiency were achieved. At a mixing ratio of 1:1, the pyrolysis oil featured the highest aromatic hydrocarbon content and lowest acid content. The high-temperature pretreatment of RM increased the Fe2O3 content, which enhanced the dielectric properties and magnetic loss ability of the reactants. This resulted in localized high temperatures and the formation of "hot spots," which can promote the deoxygenation and hydrogenation reactions of oil. Consequently, the lower heating rate of oil increased from 35.12 to 40.11 MJ kg-1. The released oxygen escaped in the form of CO. In addition, pyrolytic char was used as an in situ microwave absorbing material owing to its increased Fe2O3 content and graphitization degree, leading to an increase in energy recovery efficiency from 4.71% to 9.98%. This study provides valuable guidance for the efficient utilization of diversified solid wastes and demonstrates the potential application of microwave-assisted pyrolysis technology in the resource utilization of solid wastes.

The dynamic evolution and coupling coordination development mechanism of new urbanization and green economy: an empirical study based on various provinces in China

Under the background that the country is vigorously promoting the construction of new urbanization and seeking green development, this paper takes 31 provinces of China as the research object. It constructs a comprehensive evaluation system that integrates new urbanization and green economy into the same research framework, analyzes the evolution characteristics of new urbanization and green economy from the scale analysis of time and space, and, through the relative development model, coupling coordination model, and the random panel Tobit model, further explores the relative development and coupling coordination relationship between the two, deconstructing the internal driving factors. Research shows that the regional differences in the development level of new urbanization are decreasing year by year, while the efficiency of the green economy is increasing yearly. The relative development types of the two have obvious regional distribution characteristics. The level of coupling coordination gradually increases over time. The impact of economic development and growth, urban construction, regional opening up, urban expansion, government investment, industrialization level, and industrial structure on the coupling coordination degree of new urbanization and green economy is inconsistent.

Green total-factor energy efficiency and its convergence of industrial sub-sectors in China

Existing literature ignores to consider multiple types of pollutants when analyzing energy efficiency and its convergence. Under this background, using SuperSBM-GML model, the improved entropy method, and convergence model, this paper calculates the green total-factor energy efficiency and its evolution trend of 35 China's industrial sub-sectors considering multiple pollutants, and analyzes its convergence. The results indicate that the average score of industrial green total-factor energy efficiency is low, and there are significant differences among sub-sectors: "Utilization of waste resources" is the highest, while "Manufacture of paper and paper products" is the lowest. The green total-factor energy efficiency shows an overall upward trend from 2006 to 2021, the main driving force comes from technological progress, but numerous sub-sectors have not sufficiently caught up with existing cutting-edge technologies. Specifically, the growth rate of green total-factor energy efficiency in high-energy-consumption sub-sectors is higher than low-to-medium-energy-consumption sub-sectors. There are both σ-convergence and β-convergence in low-to-medium-energy-consumption group, indicating that development of sub-sectors is stable and outstanding. Nevertheless, the high-energy-consumption group only exhibits conditional β-convergence, revealing an imbalance in energy efficiency development. Consequently, formulating the benchmark level of energy efficiency and developing energy efficiency "leader" system are suggested for low-to-medium and high-energy-consumption sub-sectors, respectively.

Biohydrogen production through energy efficient surfactant induced microwave pretreatment of macroalgae Ulva reticulata

Macroalgal biomass being rich in carbohydrates, proteins and lipids in their cell wall has been considered as the most efficient organic rich sources for biofuel (biohydrogen) production. In this study, Pluronic P-123-induced microwave pretreatment was applied to disintegrate the marine macroalgae biomass, Ulva reticulata. Microwave disintegration was done by varying the treatment time and microwave power from 0 to 40 min and 0.09 KW to 0.63 KW. A maximum chemical oxygen demand (COD) solubilization of 22.33% was achieved at a microwave power and time duration of 0.36 kW and 15 min. Chemical (Pluronic P-123, a mild surfactant) was combined with optimum microwave disintegration conditions to increase the solubilization efficiency and this combined pretreatment achieved a maximum COD solubilization of 31.02% at 10 min pretreatment time and 0.06 g per g TS of Pluronic P-123 dosage. The present study indicated that combination of surfactant with microwave pretreatment substantially improves the COD solubilization with reduced pretreatment -time than mono microwave pretreatment. An optimal hydrogen yield of 98.37 mL was achieved through this combined pretreatment. The biohydrogen data was modelled with Gompertz model and the kinetic parameters derived through this model implies that the calculated adjusted R squared values for all the samples lies between 0.95 and 0.99. This shows that the model fitted biohydrogen experimental values accurately. In addition, Pluronic P-123-induced microwave pretreatment was regarded as energy efficient and cost effective than microwave pretreatment alone with net energy production and a greater energy ratio of 504.38 kWh/Ton macroalgae and 1.2 when compared to microwave pretreatment alone (-2975.6 kWh/Ton macroalgae and 0.5).

Microalgae as tools for bio-circular-green economy: Zero-waste approaches for sustainable production and biorefineries of microalgal biomass

Microalgae are promising organisms that are rapidly gaining much attention due to their numerous advantages and applications, especially in biorefineries for various bioenergy and biochemicals. This review focuses on the microalgae contributions to Bio-Circular-Green (BCG) economy, in which zero-waste approaches for sustainable production and biorefineries of microalgal biomass are introduced and their possible integration is discussed. Firstly, overviews of wastewater upcycling and greenhouse gas capture by microalgae are given. Then, a variety of valuable products from microalgal biomass, e.g., pigments, vitamins, proteins/peptides, carbohydrates, lipids, polyunsaturated fatty acids, and exopolysaccharides, are summarized to emphasize their biorefinery potential. Techno-economic and environmental analyses have been used to evaluate sustainability of microalgal biomass production systems. Finally, key issues, future perspectives, and challenges for zero-waste microalgal biorefineries, e.g., cost-effective techniques and innovative integrations with other viable processes, are discussed. These strategies not only make microalgae-based industries commercially feasible and sustainable but also reduce environmental impacts.

Towards green economy and sustainable development in Bangladesh: assessing the role of social and environmental indicators

The evolution towards a green economy integrating social, economic, and environmental concerns has opened a new window to pursue the sustainable development goals (SDGs), especially for emerging nations. Nonetheless, despite being a pressing concern on a global scale, empirical research into the potential for green economy development in the context of Bangladesh has remained notably inadequate. To fill this void, this study is an attempt to evaluate the connection among economic growth, carbon dioxide (CO2) emissions, education, life expectancy, and technology to conclude the ecological and socio-economic repercussions of a green economy in Bangladesh's framework of achieving SDGs. Considering the statistical features of the annual data from 1990 to 2019, the autoregressive distributed lag (ARDL) method has been employed to analyze the connections between the chosen variables. The empirical outcomes show that an upsurge in CO2 is accompanied by a 3.66% increase in GDP over the long term, suggesting a positive and statistically significant relationship between the two variables. In addition, GDP increases by about 4.2% for every 1% increase in life expectancy. However, the relationship between technological innovation and education found an insignificant positive linkage with GDP. The most important takeaway from these findings is that the growth of Bangladesh's economy is occurring at the expense of the environment. Hence, this research recommends that, as a developing nation, Bangladesh should concentrate on environment-friendly alternatives, which can be done through the introduction of a green economy to achieve a sustainably developed economy.

Whole-plant corn silage harvesting modalities: energy efficiency and operational performance

The need for energy rationalizing in farming operations require research that optimize grain crop conduction. The operations used in the processing and production of silage have limitations in energy optimization due to the lack of studies. This paper evaluated energy efficiency of whole-plant silage operations with the objective of favor the decision making. The adopted design of the experiment was in parcels (with seven replications), consisting of three harvesting modalities: single-line forage harvester, total area forage harvester, and total area forage harvester with support transshipment. The tractors were instrumented with sensors that measured engine rotation, travel speed, and hourly fuel consumption which were used to calculate field capacity, fuel consumption per area and per harvested mass, and production capacity of the harvester-tractor set. The results went to analysis of variance and subsequently to Tukey's test. The single had a faster speed and lower hourly fuel consumption, but smaller field capacity and greater energy expenditure for the mass. The use of support transshipment set with the front harvester allowed an improvement in the operation, with an increase in the worked area, and material processing (18%), and speed (13%), without differing in fuel expenditure. The total-area forage harvester modality showed smaller costs (USD 6.7), followed by the total-area forage harvester with support transshipment set (USD 7.7) and the single-line forage harvester (USD 9.38), respectively. The use of forage harvesters with a wider working width proved to be more efficient in terms of production costs per harvested hectare, validating it's reccomendation.

Evaluating the energy efficiency-enhancing potential of the digital economy: Evidence from China

Improving energy efficiency can go a long way in helping China address environmental problems it currently faces and help deliver on its pledge of achieving carbon neutrality by 2060. At the same time, innovative production technologies based on digital solutions continue to attract significant attention, owing to their potential to provide environmentally sustainable development opportunities. This study explores whether the digital economy can improve energy efficiency by facilitating input reallocation and promoting better information flows. We rely on a panel of 285 Chinese cities for the period 2010-2019 and a so-called slacks-based efficiency measure incorporating socially undesirable outputs to obtain energy efficiency from the decomposition of a productivity index. Our estimation results demonstrate that the digital economy can promote better energy use efficiency. More specifically, a 1-percentage point increase in the size of the digital economy leads to an average increase of around 14.65 percentage points in energy efficiency. This conclusion still holds under a two-stage least-squares procedure used to mitigate endogeneity. The efficiency-enhancing impact of digitalization is heterogeneous and depends on factors such as resource endowment, city size, and geographical location. Additionally, our results suggest that digital transformation within a particular region has an adverse effect on energy efficiency in that region's neighboring areas due to negative spatial spillover effects. These negative spillovers outweigh the positive direct effect on energy efficiency that can be attributed to a growing digital economy.

Energy efficiency in wastewater treatment plants: A framework for benchmarking method selection and application

Utilities produce and store vast amount of data related to urban wastewater management. Not yet fully exploited, proper data analysis would provide relevant process information and represents a great opportunity to improve the process performance. In the last years, several statistical tools and benchmarking methods that can extract useful information from data have been described to analyse wastewater treatment plant (WWTP) energy efficiency. Improving energy efficiency at WWTPs is however a complex task which involves several actors (both internal and external to the water utility), requires an exchange of different types of information which can be analysed by a broad selection of methods. Benchmarking method therefore must not only be selected based on whether they provide a clear identification of inefficient processes; it must also match the available data and the skills of those performing the assessment and objectives of stakeholders interpreting the results. Here, we have identified the requirements of the most common benchmarking methods in terms of data, resources, complexity of use, and information provided. To do that, inefficiency is decomposed so that the analyst, considering the objective of the study and the available data, can link each element to the appropriate method for quantification and benchmarking, and relate inefficiency components with root-causes in wastewater treatment. Finally, a framework for selecting the most suitable benchmarking method to improve energy efficiency in WWTPs is proposed to assist water sector stakeholders. By offering guidelines on how integrates and links data, methods and actors in the water sector, the outcomes of this article are expected to move WWTPs towards increasing energy efficiency.

Experimental and theoretical investigations of rotating algae biofilm reactors (RABRs): Areal productivity, nutrient recovery, and energy efficiency

Microalgae biofilms have been demonstrated to recover nutrients from wastewater and serve as biomass feedstock for bioproducts. However, there is a need to develop a platform to quantitatively describe microalgae biofilm production, which can provide guidance and insights for improving biomass areal productivity and nutrient uptake efficiency. This paper proposes a unified experimental and theoretical framework to investigate algae biofilm growth on a rotating algae biofilm reactor (RABR). Experimental laboratory setups are used to conduct controlled experiments on testing environmental and operational factors for RABRs. We propose a differential-integral equation-based mathematical model for microalgae biofilm cultivation guided by laboratory experimental findings. The predictive mathematical model development is coordinated with laboratory experiments of biofilm areal productivity associated with ammonia and inorganic phosphorus uptake by RABRs. The unified experimental and theoretical tool is used to investigate the effects of RABR rotating velocity, duty cycle (DC), and light intensity on algae biofilm growth, areal productivity, nutrient uptake efficiency, and energy efficiency in wastewater treatment. Our framework indicates that maintaining a reasonable light intensity range improves biomass areal productivity and nutrient uptake efficiency. Our framework also indicates that faster RABR rotation benefits biomass areal productivity. However, maximizing the nutrient uptake efficiency requires a reasonably low RABR rotating speed. Energy efficiency is strongly correlated with RABR rotating speed and DC.

The government-production nexus of energy efficiency in China's construction industry: regional difference and factor analysis

For decades, the construction industry has contributed significantly to China's economic growth. The heavy energy consumption inevitably leads to the release of large amounts of carbon emissions. Improving energy efficiency has been a crucial solution for mitigating the environmental impacts while boosting its green economy in the construction industry. Measuring the energy efficiency in the construction industry considering the quality of government sector is still limited. Using panel provincial data in China from 2011 to 2020, this paper proposes a two-stage dynamic data envelopment analysis (DEA) framework integrating the government sector with the production sector in the construction industry, and calculates energy efficiency. The spatial Durbin model is used to analyze the driving forces of energy efficiency. The research findings include (1) the energy efficiency in the eastern region is higher than that in the central and western regions. The mean values of energy efficiency in the eastern, central, and western regions are 0.42, 0.34, and 0.37. (2) Even though governance efficiency is lower than production efficiency, there is a positive correlation between governance efficiency and production efficiency with a correlation coefficient of 0.48. Improving governance efficiency is a significant step to increase the production efficiency and further increase energy efficiency of the construction industry. (3) Digital transformation has a positive effect on governance efficiency but has no effect on production efficiency. The government-production nexus framework provides implications for clarifying the role of government intervention in improving energy efficiency.

Microscopic and luminescence characteristics of Dy3+ doped KSrVO4 nanophosphors as energy efficient photoluminescent material with potential application in white light-emitting diodes

Nanotechnology has drawn an enormous amount of attention by providing various measures to reduce energy consumption. Phosphor-converted white-light emitting diodes (pc-w-LEDs), which are used in lighting applications, are gaining popularity. These materials are affordable, effective, and safe for the environment. Therefore, the main objective of the current study is to synthesize an economical phosphor which consumes low energy and is less harmful to the environment. In this study, Dysprosium (Dy3+) doped Potassium Strontium Vanadate (KSrVO4) nanopowders synthesized via the combustion process and using X-ray diffraction, FESEM, EDAX, HRTEM, UV-Vis spectroscopy, and photoluminescence spectroscopy techniques, we have examined its various structural, spectroscopic, optical, and morphological characteristics. The crystallite size was estimated using the XRD patterns and was found to be 25.724 nm. The functional groups contained in synthesized phosphor were identified using FTIR spectrum measurements. Using HRTEM, a particle size of 36.33 nm was predicted, which is consistent with the XRD results. The Kubelka-Munk approximation is used to determine the band gap energy of the produced nanophosphors. Three major peaks that correspond to the transitions of 4F9/2 → 6HJ (J = 15/2, 13/2, and 11/2) were discovered at 476 nm, 578 nm, and 669 nm, respectively, under the excitation of 390 nm near UV light. We investigated the impact of Dy3+ doping, the enhancement of emission intensity and the mechanism of concentration quenching on the photoluminescence spectra of the KSrVO4 host. KSrVO4:Dy3+ also demonstrated a suitable CCT (3745 K), enhanced color purity and high quantum yield in this work, indicating that this phosphor has potential applications in w-LED devices.

Energy Efficient Artificial Olfactory System with Integrated Sensing and Computing Capabilities for Food Spoilage Detection

Artificial olfactory systems (AOSs) that mimic biological olfactory systems are of great interest. However, most existing AOSs suffer from high energy consumption levels and latency issues due to data conversion and transmission. In this work, an energy- and area-efficient AOS based on near-sensor computing is proposed. The AOS efficiently integrates an array of sensing units (merged field effect transistor (FET)-type gas sensors and amplifier circuits) and an AND-type nonvolatile memory (NVM) array. The signals of the sensing units are directly connected to the NVM array and are computed in memory, and the meaningful linear combinations of signals are output as bit line currents. The AOS is designed to detect food spoilage by employing thin zinc oxide films as gas-sensing materials, and it exhibits low detection limits for H2 S and NH3 gases (0.01 ppm), which are high-protein food spoilage markers. As a proof of concept, monitoring the entire spoilage process of chicken tenderloin is demonstrated. The system can continuously track freshness scores and food conditions throughout the spoilage process. The proposed AOS platform is applicable to various applications due to its ability to change the sensing temperature and programmable NVM cells.

The impact of carbon emission trading policy on energy efficiency-evidence from China

Energy efficiency (EE) plays an important role in achieving the dual-carbon goal, and improving EE is thus indispensable. This paper evaluates the impact of carbon emission trading policy (CETP) on EE based on a difference-in-difference (DID) method, using 16-year data of 30 provinces and cities from 2005 to 2020. Conclusions are as follows: (1) CETP significantly promotes EE, and this conclusion still appears valid after robustness tests. (2) The positive impact of CETP on EE is more effective in regions of high foreign direct investment (FDI) and high government intervention (GOVI). (3) The positive impact of CETP on EE is through impact mechanisms of energy structure adjustment (ESA), green innovation (GI), and industrial structure upgrading (ISU). The findings in this paper may enrich current research in CETP and offer more pragmatic suggestions for policy advancement as well.

The effect of forest resources, energy efficiency, and renewable energy on environmental degradation-a comparative analysis of the less- and high-emitter sub-Saharan African countries

Environmental degradation is one of the main causes of concern in the world. There is a dilemma on policies that are devised to improve the quality of the environment with those meant to promote economic growth, since factors that foster economic growth degrade the environment. The present research seeks to examine the influence of energy efficiency, forest resources, and renewable energy among the less-emitter and high-emitter sub-Saharan African nations, for the period 1990 to 2020. The present research is significant in providing a comparative analysis of less- and high-emitter sub-Saharan African nations on this subject, hence the main novelty of the research. The panel Autoregressive distributive lag and cross-sectionally augmented autoregressive distributive methods are used for data analysis, and their results are compared and contrasted. The research presents in its findings that renewable energy, forest resources, and energy efficiency improve the environment, while economic growth distorts the environment in both regions. No asymmetries exist between the less- and high-emitter sub-Saharan African nations, on the impact of energy efficiency, economic growth, forest resources, and renewable energy to the environment. Non-renewable energy, in the high-emitter sub-Saharan African nations, degrades the environment. The policy recommendations are also given in line with the research findings.

Large Scale Energy Efficient Sensor Network Routing using a Quantum Processor Unit

The sensor network energy conservation method, which is a usage hybrid of a classical computer and quantum processor, has proved to perform better than the heuristic algorithm using a classical computer. In this manuscript, the technical context for the significance of the method is presented and justified. Then the experimental steps are demonstrated in an operational sequence with illustrations if ever needed. The method has been validated by positive results across a randomly generated sample set of network topologies. The successful experimental results of this method have provided a better approach for sensor network lifetime maximization problems and demonstrated that the current state of art quantum processor has been able to solve large practical engineering problems with merits that override current methods in the literature. In other words, quantum advantage can be exploited to best efforts. It has gone beyond the stage of proof of concept to proof of feasibility.

How does economic complexity improve energy efficiency? Mechanism discussion and empirical test

Energy efficiency represents one of the best productive strategies to lessen the effects of global warming and climate change. Similarly, the manufacturing and export of a wide variety of high-tech, knowledge-based items like chemicals and machinery have significant effects on both economic growth and the environment. The main goal of this study is to examine the long-run effects of economic complexity on energy efficiency in 93 countries over the period from 1995 to 2015. The empirical outcomes reveal that economic complexity improves energy efficiency. Specifically, countries that produce and export a wide range of sophisticated products tend to enjoy higher levels of energy efficiency compared to their counterparts who export a limited range of simple products. Moreover, empirical findings suggest that economic growth and population density increase energy efficiency, while trade impedes it. Further empirical investigations from a mediation analysis revealed that about 63% and 38% of the effects of economic complexity on energy efficiency mediate through income inequality reduction and human capital accumulation, respectively. Based on these results, political leaders and governments are provided with solid reasons to pay more attention to improving their productive structures in order to promote energy efficiency and a green future.

A bibliometric review on electric vehicle (EV) energy efficiency and emission effect research

Electric vehicles have received extensive attention due to their unique energy efficiency and good emission reduction effects. While a large-scale of electric vehicles are gradually replacing traditional fuel vehicles, it is necessary to ensure the energy efficiency of electric vehicles and the effectiveness of their emission reduction effects. This study conducted a bibliometric analysis of scientific publications on energy efficiency and emission reduction effects of electric vehicles from 2003 to 2022, using a variety of bibliometric tools such as R Studio, biblioshiny and VOSviewer. The results showed the gradual elimination of traditional energy vehicles, where electric vehicles play an important role in connecting energy efficiency and emission control. The results also showed the top publication outlets, citations trackers, authors with thematic evaluation of energy efficiency and emission reduction effects of electric vehicles. The contribution of the study is manifold. The academic contribution of the present study is the bibliometric analysis which will help academicians to get a quick overview of the most popular journals, top collaborators, documents, authors, and scientific knowledge structure. Secondly, policy makers, environmentalists, researchers, and academician will definitely get a pathway how they should go for future research. Finally, this study suggests more researches trend to focus on the sales of electric vehicles, automobile exhaust emissions, sensitivity analysis of electric vehicles, energy storage analysis to improve the energy efficiency of electric vehicles, and V2G related to the energy efficiency of electric vehicle clusters.

Microbially Induced Calcium Carbonate Precipitation by Sporosarcina pasteurii: a Case Study in Optimizing Biological CaCO3 Precipitation

Current production of traditional concrete requires enormous energy investment that accounts for approximately 5 to 8% of the world's annual CO2 production. Biocement is a building material that is already in industrial use and has the potential to rival traditional concrete as a more convenient and more environmentally friendly alternative. Biocement relies on biological structures (enzymes, cells, and/or cellular superstructures) to mineralize and bind particles in aggregate materials (e.g., sand and soil particles). Sporosarcina pasteurii is a workhorse organism for biocementation, but most research to date has focused on S. pasteurii as a building material rather than a biological system. In this review, we synthesize available materials science, microbiology, biochemistry, and cell biology evidence regarding biological CaCO3 precipitation and the role of microbes in microbially induced calcium carbonate precipitation (MICP) with a focus on S. pasteurii. Based on the available information, we provide a model that describes the molecular and cellular processes involved in converting feedstock material (urea and Ca2+) into cement. The model provides a foundational framework that we use to highlight particular targets for researchers as they proceed into optimizing the biology of MICP for biocement production.

The role forest resources, energy efficiency, and renewable energy in promoting environmental quality

At a time when environmental concerns are rising in the world, natural resources, such as trees and other green plants, remain the most crucial factors responsible for reducing environmental degradation. Green plants inhale carbon dioxide and prevent the soil from wash and wear, hence their significant role in enhancing environmental quality. Therefore, it is essential to come up with state-of-the-art researches on the role of green plants to the environment. The present research is aimed at adding to the growing body of literature by investigating the effect of forest resources, together with renewable energy and energy efficiency in enhancing environmental quality. In this research, we use the data of the seven emerging countries, seven developed nations and 15 developing west African nations, from 1990 to 2019. The current research adds to the growing body of literature in that it presents a comparative analysis of the three important economic blocks, as well as employing three major methodologies of data analysis, the CS-ARDL, AMG, and CCEMG techniques, which are strong over cross-sectional dependence, heterogeneity, and dynamics. Major research outcomes show that renewable energy and energy efficiency negatively affects carbon emissions, while gross domestic product positively affects carbon emissions in all three regions. Population size and forest resources reduces carbon emissions in the emerging countries and seven developed countries, respectively. Non-renewable energy promotes carbon emissions in the seven developed countries, while in the emerging countries it reduces emissions. This research recommends the efficient utilization of energy, use of renewable energy, and forest preservation to promote carbon neutrality goal.

Enhancing Energy Efficiency and Fast Decision Making for Medical Sensors in Healthcare Systems: An Overview and Novel Proposal

In the realm of the Internet of Things (IoT), a network of sensors and actuators collaborates to fulfill specific tasks. As the demand for IoT networks continues to rise, it becomes crucial to ensure the stability of this technology and adapt it for further expansion. Through an analysis of related works, including the feedback-based optimized fuzzy scheduling approach (FOFSA) algorithm, the adaptive task allocation technique (ATAT), and the osmosis load balancing algorithm (OLB), we identify their limitations in achieving optimal energy efficiency and fast decision making. To address these limitations, this research introduces a novel approach to enhance the processing time and energy efficiency of IoT networks. The proposed approach achieves this by efficiently allocating IoT data resources in the Mist layer during the early stages. We apply the approach to our proposed system known as the Mist-based fuzzy healthcare system (MFHS) that demonstrates promising potential to overcome the existing challenges and pave the way for the efficient industrial Internet of healthcare things (IIoHT) of the future.