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.

Unveiling the liaison between financial development dimensions, energy efficiency and ecological footprint in the context of institutional frameworks: evidence from the Emerging-7 economies

Financial development and energy efficiency can facilitate the transition towards a more environmentally sustainable and responsible economy. Simultaneously, the importance of institutional effectiveness cannot undermine the need to manage financial and energy consumption activities. To this end, the primary objective of this study is to examine the effects of financial development and energy efficiency on the ecological footprint of the Emerging-7 economies from 2000 to 2019. The study specifically focuses on the influence of these factors within the context of robust institutional mechanisms. We employ the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model as the analytical framework to accomplish this. This study takes into consideration three aspects of financial development, which are: (i) the depth of financial development, (ii) the stability of financial development, and (iii) the efficiency of financial development. In addition, this study has developed an institutional index using principal component analysis. The index comprises several crucial indicators: Control of Corruption, Government Effectiveness, Political Stability, Regulatory Quality, Rule of Law, and Voice and Accountability. The study raises the importance of energy efficiency in terms of energy intensity on ecological footprint. The study's findings suggest that without robust institutional mechanisms, the potential of financial development depth, stability, and efficiency to improve ecological well-being may not be fully realized. However, the study concludes that these institutional mechanisms positively impact mitigating the ecological footprint.

Variation of digital economy's effect on carbon emissions: improving energy efficiency and structure for energy conservation and emission reduction

The significance of accurately assessing the influence of digital economy growth upon reducing emission of carbon in the context of worldwide climate governance cannot be overstated. This is crucial in encouraging low-carbon economic advancement at national level, achieving carbon peak and neutrality as soon as possible, and creating a shared future for humanity. A mediating effect model is established using cross-country panel data from 100 countries, ranging from 1990 to 2019, to assess the influence of digital economy development upon emission of carbon and to explore its underlying mechanism. The study found that: the growth of national emission of carbon can be considerably suppressed by digital economy development, and the reduction of emissions is positively associated to each country's level of economic advancement. Digital economy growth influences regional emission of carbon via intermediary channels like energy structure and efficiency, with energy intensity having a particularly noticeable intermediary impact. The inhibitory influence of digital economy development upon emission of carbon differs among countries with different levels of income, and improvements in energy structure and efficiency can precede to energy savings and emission reduction in both middle- and high-income countries. The above findings offer policy guidance for harmoniously advancing the growth of digital economy and climate management, hastening the low-carbon transformation of national economies, and implementing China's carbon peaking initiative.

How the energy technology influences the total factor of energy efficiency?: evidence from China

Technological progress is of great importance to total-factor energy efficiency (TFEE). However, previous research has not narrowed technological progress into the energy field, generating rough and ambiguous empirical evidence for policymakers. In addition, technological progress is often discussed from a conventional perspective as a whole, ignoring its heterogeneity and spillover effect between regions. This study applies the stock of energy patents to reflect the effect of technological progress in the energy field on TFEE at first. The dynamic models are then employed to investigate if and how technological progress influences TFEE from the conventional and spatial perspectives for China's over the period of 2000-2016. The conventional analysis shows that energy technology is of great importance to TFEE. However, the creation-type of technology coming from businesses specifically is shown to have more success in enhancing TFEE than other types of energy technology. Further evidence coming from the spatial econometrics demonstrates that technology spillovers across regions are rather common and have significant effects on TFEE.

Do financial inclusion and environmental regulations affect the green economy? An empirical study with a generalized linear model

Reducing carbon emissions is an efficient strategy to cope with global warming, which continues to be a frightening element for environmental protection. However, the energy industry is responsible for a lot of pollution in the atmosphere. To promote a low-carbon growth model, it is essential to endorse financial inclusion and environmental regulations. This research uses panel data from 70 nations, covering 1995 to 2021, to examine the interplay between economic growth, human capital, urbanization, trade openness, and environmental regulation as the primary defining element of efficient energy. Several tests have been used to ensure that the data are typically distributed; these include the cross-sectional dependence test, the KMO test, and the Bartlett test. The generalized linear model and Driscoll-Kraay standard errors have also been implemented for interim and final analysis. Results show that low-carbon energy sources are guaranteed for certain economies when financial inclusion and environmental regulation are implemented. Economic development, urbanization, trade openness, and human capital significantly impact green economic recovery. In light of these findings, policymakers are working to increase energy efficiency and boost their citizens' living standards by promoting financial inclusion and environmental regulation like imposing environmental taxes and governmental laws for industries.

The impact of energy efficiency in reducing environmental degradation: does renewable energy and forest resources matter?

The vast utilisation of energy sources in promoting economic growth has been identified as the major cause of environmental degradation (through carbon emission). Therefore, the efficient utilisation of energy ensuring the minimisation of any wastages is vital in reducing environmental degradation. The current research aims to investigate the importance of energy efficiency, forest resources, and renewable energy in reducing environmental degradation. The major novelty of the research is that it seeks to investigate the impact of forest resources and energy efficiency on carbon emissions. Literature shows that there is still a dearth on the association of forest resources and energy efficiency, with carbon emissions. We employ data of the European Union countries for the time frame ranging from 1990 to 2020. The CS-ARDL technique depicts that raising GDP by 1% raises carbon emissions by 5.62% in the short run and 2.93% in the long run, raising renewable energy by 1 unit reduces carbon emissions by 0.098 and 0.03 units in the short and long run, respectively, whilst raising energy efficiency by 1% reduces carbon emissions by 6.29% and 3.29% in the short and long run, respectively. The Fixed Effect and Random Effect tools support the outcomes of the CS-ARDL tool on the negative effect of renewable energy and energy efficiency, and the positive effect of GDP on carbon emissions, and also depict that raising non-renewable energy by a single unit raises carbon emissions by 0.07 and 0.08 units, respectively. Forest resources, in this present research, do not significantly impact the emissions of carbon amongst the European nations.

Energy and air? The impact of energy efficiency improvement on air quality in China

The global economic growth is hindered by resources shortage, energy demand, air pollution and climate. Energy efficiency can reduce some pollutants while potentially increase others. This study refers to sulfur dioxide (SO2), nitrogen oxides (NOx), and dust and smoke (DS) as primary pollutants to distinguish it from secondary ones. The influence of energy efficiency, socioeconomic, and natural climatic factors on air quality is analyzed under the theory of STIRPAT. It is highly coupled between energy efficiency and the spatial distribution of air quality. Increased energy efficiency can improve air quality by reducing SO2 and NOx, but the impact on DS is insignificant. Air pollutants decrease by about 0.531% for every 1% increase in temperature and 0.105% for every 1% increase in precipitation. Consumption will reduce air pollution, and there is an inverted U-shaped relationship between population density, economic scale, urbanization, technology innovation, and air pollution. It is worth mentioning that this work adds temperature and precipitation to the STIRPAT as natural climatic factors, analyzing the impact of energy efficiency on air pollution under the two-factor restrictions of socioeconomic and natural climatic factors. Finally, management suggestions are made to improve air quality.

The establishment of city commercial banks and China's green economy development

Promoting sustainable economic development has been pursued by all countries, and achieving green economic development is crucial to sustainable economic development. This study uses the non-radial direction distance function (NDDF) method to calculate the level of development of the green economy in Chinese cities during 2003-2014. Next, it uses the establishment of China's city commercial banks as an exogenous policy shock to build a staggered difference-in-differences model to empirically test the impact of the establishment of city commercial banks on green economy development. This study found that, first, the establishment of city commercial banks significantly promoted green economy development. Second, in areas with a high proportion of small and medium-sized enterprises (SMEs), the establishment of city commercial banks is imperative to promoting green economy development. SMEs are crucial carriers to city commercial banks to promote green economy development. Third, financing constraints mitigation, green innovation, and pollution emission reduction are important channels for city commercial banks affecting green economy development. This study enriches the relevant research on the impact of financial market reform on green economy development.

Risk-return profile of environmentally friendly assets: Evidence from the NASDAQ OMX green economy index family

The COVID-19 pandemic, geopolitical risks and net-zero targets have created not only pressures but incentives for energy investors. The renewable energy has become the largest energy sector and provided significant investment opportunities. However, companies operating in this sector are highly risky due to economic and political barriers. Therefore, it is of crucial importance for investors to properly assess the risk-return dynamics of these investments. This paper examines the risk-return characteristics of clean energy equities at a disaggregate level using a battery of performance metrics. The main results provide evidence of significant heterogeneity across clean energy sub-sectors; for instance, fuel cell and solar stocks display higher downside risks than the others, while the developer/operator equities are the least risky. The findings further provide evidence of higher risk-adjusted returns during the coronavirus pandemic; as an example, energy management companies appear to provide the highest risk-adjusted returns in the wake of the COVID-19. Comparing the performance with traditional sectors, clean energy stocks outperform certain sectors, including dirty assets. These findings offer important implications for investors, portfolio managers, and policy makers.

Spatiotemporal parameters for energy efficient kilohertz-frequency nerve block with low onset response

BACKGROUND

Electrical nerve conduction block has great potential for treatment of disease through reversible and local inactivation of somatic and autonomic nerves. However, the relatively high energy requirements and the presence of undesired excitation at the onset of the kilohertz-frequency (KHF) signals used for block pose obstacles to effective translation. Frequency, electrode geometry, and waveform shape are known to influence block threshold and onset response, but available data provide a limited understanding of how to select these parameters to optimize nerve block.

METHODS

We evaluated KHF nerve block in rat tibial nerve across frequencies (5-60 kHz), electrode geometries (monopolar, bipolar, and tripolar), and waveform shapes. We present a novel Fourier-based method for constructing composite signals that systematically sample the KHF waveform design space.

RESULTS

The lowest frequencies capable of blocking (5-16 kHz) were not the most energy-efficient among the tested frequencies. Further, bipolar cuffs required the largest current and power to block, monopolar cuffs required the lowest current, and both tripolar and monopolar cuffs required the lowest power. Tripolar cuffs produced the smallest onset response across frequencies. Composite signals comprised of a first harmonic sinusoid at fundamental frequency (f0) superposed on a second harmonic sinusoid at 2f0 could block at lower threshold and lower onset response compared to the constituent sinusoids alone. This effect was strongly dependent on the phase of the second harmonic and on the relative amplitudes of the first and second harmonics. This effect was also dependent on electrode geometry: monopolar and tripolar cuffs showed clear composite signal effects in most experiments; bipolar cuffs showed no clear effects in most experiments.

CONCLUSIONS

Our data provide novel information about block threshold and onset response at the boundary of frequencies that can block. Our results also show an interaction between spatial (cuff geometry) and temporal (frequency and waveform shape) parameters. Finally, while previous studies suggested that temporal parameters could reduce onset response only in exchange for increased block threshold (or vice versa), our results show that waveform shape influences KHF response in ways that can be exploited to reduce both energy and onset responses.

Investigating asymmetric impacts of total factor energy efficiency on carbon emissions in India

As many complex energy relations are not linear and have diminishing returns, assuming a symmetric (linear) effect of energy efficiency (ENEF) on carbon emissions (CAE) has limited our understanding of the emission-ENEF nexus. This research, therefore, initially estimates total factor energy efficiency by applying a stochastic frontier technique using sample panels for India encompassing the period from 2000 to 2014. Further, a nonlinear panel autoregressive distributed lag modelling framework is utilised in order to investigate the asymmetric (nonlinear) long- and short-run impacts of ENEF on CAE. The findings demonstrated that ENEF has asymmetric long- and short-run impacts on CAE in India. Based on the outcomes, numerous crucial implications are discussed with a particular reference to developing economies like India.

Essential lipid autacoids rewire mitochondrial energy efficiency in metabolic dysfunction-associated fatty liver disease

BACKGROUND AND AIM

Injury to hepatocyte mitochondria is common in metabolic dysfunction-associated fatty liver disease. Here, we investigated whether changes in the content of essential fatty acid-derived lipid autacoids affect hepatocyte mitochondrial bioenergetics and metabolic efficiency.

APPROACH AND RESULTS

The study was performed in transgenic mice for the fat-1 gene, which allows the endogenous replacement of the membrane omega-6-polyunsaturated fatty acid (PUFA) composition by omega-3-PUFA. Transmission electron microscopy revealed that hepatocyte mitochondria of fat-1 mice had more abundant intact cristae and higher mitochondrial aspect ratio. Fat-1 mice had increased expression of oxidative phosphorylation complexes I and II and translocases of both inner (translocase of inner mitochondrial membrane 44) and outer (translocase of the outer membrane 20) mitochondrial membranes. Fat-1 mice also showed increased mitofusin-2 and reduced dynamin-like protein 1 phosphorylation, which mediate mitochondrial fusion and fission, respectively. Mitochondria of fat-1 mice exhibited enhanced oxygen consumption rate, fatty acid β-oxidation, and energy substrate utilization as determined by high-resolution respirometry, [1- 14 C]-oleate oxidation and nicotinamide adenine dinucleotide hydride/dihydroflavine-adenine dinucleotide production, respectively. Untargeted lipidomics identified a rich hepatic omega-3-PUFA composition and a specific docosahexaenoic acid (DHA)-enriched lipid fingerprint in fat-1 mice. Targeted lipidomics uncovered a higher content of DHA-derived lipid autacoids, namely resolvin D1 and maresin 1, which rescued hepatocytes from TNFα-induced mitochondrial dysfunction, and unblocked the tricarboxylic acid cycle flux and metabolic utilization of long-chain acyl-carnitines, amino acids, and carbohydrates. Importantly, fat-1 mice were protected against mitochondrial injury induced by obesogenic and fibrogenic insults.

CONCLUSION

Our data uncover the importance of a lipid membrane composition rich in DHA and its lipid autacoid derivatives to have optimal hepatic mitochondrial and metabolic efficiency.

Implementation of the energy efficiency existing ship index and carbon intensity indicator on domestic ship for marine environmental protection

The International Maritime Organization has set a goal to achieve a 50% reduction of total annual greenhouse gas emission related to the international shipping by 2050 compared to the 2008 baseline emissions. Malaysia government has taken an initiative to investigate the assessment (cost-effectiveness) of this International Maritime Organization's short-term measure on Malaysian-registered domestic ships although this measure is only for international merchant ship. To achieve this, this paper collected the ship's data from the shipowners from 25 sample ships. Engine power limitation is the most cost-effective option, but low power limits can lead to substantially increased sailing times. Based on cost-efficiency analysis, it creates for the purpose of compliance with the operational carbon intensity indicator. It found that even if it is possible to bring an asset back into service, it may not be possible to do so in a manner that generates a profit or complies with applicable regulations. In these situations, it may be more prudent to scrap the asset rather than run the risk of having it become a stranded asset. This is especially true for older tankers. Alternatives with lengthy payback periods are not desirable for the domestic tanker fleet that is already in operation.

Can technological finance cooperation pilot policy improve energy efficiency? Evidence from a quasi-experiment in China

Whether the technological finance cooperation pilot (TFCP) policy in China can promote energy efficiency remains under investigated. Using the dataset covering 284 cities in China from 2003 to 2019, this paper adopts the Super-SBM model with undesirable outputs to measure energy efficiency. Based on this efficiency, the Difference-in-Differences model (DID) and Spatial Durbin model (SDM) are employed to discuss the impact of TFCP policy on energy efficiency. Results demonstrate that TFCP policy has significantly promoted energy efficiency. And the conclusion is still valid after the robustness checks and endogenous treatment has been carried out. The impact of the TFCP policy on energy efficiency is heterogeneous, depending on the geographical, administrative, and resource characteristics of cities. To be specific, the promotion effect tends to be pronounced in east-central cities, high-ranking cities, and high-tech cities. Moreover, TFCP policy could significantly improve energy efficiency through the effects of technological innovation, industrial upgrading, and financial development. A further policy spillover analysis shows that TFCP policy has exerted a remarkable incentive influence on energy efficiency locally, while the neighboring cities are inhibitive. To sum up, this research is of important theoretical value and policy-making reference on green economy transformation for cities with differential features and energy utilization capacity, by shedding light on the impacts of such a technological finance cooperation system on energy efficiency.

The impact and transmission mechanism of green credit policy on energy efficiency: new evidence from China

Green credit policy is the primary means for financial institutions to fulfill their environmental responsibilities. It is an issue worthy of attention whether green credit policy can achieve the effect of energy conservation, efficiency improvement, pollution reduction, and carbon reduction. This study uses the difference-in-difference method to test the impact of green credit policy on energy efficiency. The results show that green credit policy led to a significant decrease in energy intensity of green credit-restricted sectors while impeding the advancement of green total factor energy efficiency. The heterogeneity results show that the energy efficiency of large-scale, light textile manufacturing, resource processing industries, and clean industries are more significantly affected. Green credit policy can achieve energy conservation and has a linkage effect on pollution and carbon reduction. Although the constraint effect of green credit policy has effectively suppressed energy intensity, it also leads some industries to face a vicious cycle of "enhanced financing constraints-weakened innovation impetus," which in turn makes it challenging to improve green total factor energy efficiency. The above findings confirm the effectiveness of green credit policy in energy conservation and emission reduction. Also, they indicate the necessity of further improvement of the green financial policy system.

The Effect of Environmental Regulation on the Efficiency of the Green Economy: The Intermediary Role of the Aggregation of Innovative Elements

Green development is the only way to realize harmonious coexistence between people and nature, so it is of great significance to create a benchmark for high-quality development. Based on the panel data of 30 provinces (except Tibet, Hong Kong, Macao, and Taiwan) in China from 2009 to 2020, the super-efficiency slacks-based measure model was used to calculate the green economic efficiency of various regions in China, and a related statistical model was used to verify the influence of different types of environmental regulation policies on green economic efficiency and the intermediary effect of innovation factor agglomeration. The results show that: (1) during the inspection period, the influence of public-participation environmental regulation on the efficiency of the green economy presents an "inverted U" trend, while command-control and market-incentive environmental regulation policies inhibit the improvement of green economic efficiency; (2) the agglomeration of innovative elements plays a significant intermediary role in the transmission path of environmental regulation affecting green economic efficiency, but the intermediary effects of different types of environmental regulation are slightly different. Finally, we discuss environmental regulation and innovative elements, and some corresponding suggestions are put forward.

Socio-economic productive capacities and energy efficiency: global evidence by income level and resource dependence

This study tests the effects of productive capacities in socio-economic factors (human capital, transport, information-communication technology, institutions, private sector, and structural change) on energy efficiency in a sample of 125 countries. Energy efficiency is assessed by energy productivity (gross domestic product per unit of total primary energy supply) and energy intensity (total primary energy supply per capita). The world sample is divided into four income groups and an income-heterogeneous control group of non-renewable-resource-dependent economies. The study utilizes cross-sectionally dependent and stationary panel data from 2000 to 2018. The analysis of variance shows that higher income groups monotonically have higher levels in socio-economic productive capacities and energy intensity. The regression results from appropriate fixed-effects and random-effects modeling reveal varied driver and barrier influences of the socio-economic factors on energy efficiency improvements (higher energy productivity and lower energy intensity). In some cases, predictors scale up both energy productivity and energy intensity indicating the issue of the rebound effect. Higher human capital capacity stimulates energy efficiency except for middle-income groups. Higher transport capacity reduces energy productivity, except for upper-middle-income economies, and increases energy intensity for low-income and middle-income groups. The deployment of information-communication technologies is positively associated with energy productivity, except for low-income economies. Energy productivity performance of resource-dependent economies is improved by higher productive capacities in institutions and private sectors but impaired by structural change, whereas structural change drives energy efficiency in low-income economies. Additionally, the growth of gross national income per capita worsens energy efficiency for resource-dependent economies. Bidirectional feedback causalities are established between energy efficiency and its predictors in most cases. The heterogeneous findings are further discussed for providing research and policy implications.

Cationic surfactants influencing the enhancement of energy efficiency for perfluorooctanoic acid (PFOA) removal in the electrocoagulation-flotation (ECF) system

From an environmental perspective, approaching sustainability requires a fundamental conceptual shift from the wastewater treatment process toward integrated treatment systems that consider efficient and effective utilization. This study aims to investigate the effects of different surfactants on the removal of perfluorooctanoic acid (PFOA). We used cationic surfactants as both frothers and collectors in the electrocoagulation-flotation (ECF) method to improve the removal efficiency of PFOA. The results showed that, under a monopolar aluminum electrode and with an initial PFOA concentration of 0.25 mM, the ECF method with decyl-trimethyl-ammonium bromide (DTAB) was able to remove over 98% of PFOA within 10 min. Cationic surfactants with a similar linear alkyl chain shape to PFOA, but a longer chain length, are more effective at removing PFOA through the ECF process. The removal mechanism is thought to involve co-precipitation with aluminum hydroxides through Al-F bonding, co-flotation with cationic surfactants, and mixed micelle formation with cationic surfactants. The optimal conditions were tested in both synthetic and realistic wastewater matrices and produced similar results. It has the potential for real wastewater application. The energy yield (G₅₀) of ECF with 5 mM DTAB is 497 g·kWh^-1, superior to other treatments, and is an extremely energy-effective method for separating PFOA from wastewater.

Can the marketization of urban land transfer improve energy efficiency?

Local government intervention in land resource allocation can lead to the misallocation of land resources and serious pollutant emissions. As an important market-oriented economic reform in China, the marketization of urban land transfer (MULT) might have the potential to contribute to improving resource allocation efficiency by curbing local government intervention. Therefore, this study aims to provide empirical evidence on the impact of MULT on energy efficiency. We improve the MULT evaluation method to test the mechanism through which MULT affects energy efficiency. The results show that, first, the proportion of land sold by allocation and listing methods, which is characterized by a low degree of marketization, has rapidly increased in recent years, lowering the overall level of MULT. Second, MULT has a direct and significant positive impact on improving energy efficiency. Third, the mechanism analysis indicates that MULT helps enhance energy efficiency by advancing industrial structure optimization and technological progress. Moreover, the heterogeneity analysis demonstrates that the impact of MULT on improving energy efficiency differs significantly in different reform stages and between central and peripheral cities. This study sheds light on the importance of land resource allocation in improving energy efficiency and thus has practical policy implications for promoting low-carbon energy transition in emerging countries.

Does economic growth target constraint put pressure on green energy efficiency? Evidence from China

Building a sustainable energy system and achieving sustainable economic growth has always been China's development goal. However, under the promotion incentive and information asymmetry, local governments may choose to sacrifice the ecological environment to maintain expected economic growth goals. This paper analyzes the relationship between economic growth targets and green energy efficiency (GEE) by using panel data models and spatial econometric techniques. Moreover, the mediation effect model and threshold effect model are used to study their influence mechanism and the possible nonlinear relationship. The results indicate that economic growth targets reduce the efficiency of GEE. The impact of environmental regulation on GEE is "U" shaped. Environmental regulation plays a positive moderation role between economic growth targets and GEE. Additionally, higher levels of technological innovation, industrial upgrading, and environmental regulation result in a reduction in the negative effects of economic growth targets on the GEE. However, the improvement in the foreign direct investment can increase the negative influences of economic growth targets on the GEE.

The impact of environmental supervision on firms' energy efficiency: evidence from the Environmental Protection Admonishing Talk policy in China

Enhancing energy efficiency is an important issue for countries facing pressures from energy shortages and environment pollution. Given increasing interest in the role of environmental supervision and the current lack of empirical evidence on this topic, this study investigates the impact of environmental supervision on firms' energy efficiency by taking the Environmental Protection Admonishing Talk (EPAT) policy in China as a quasi-natural experiment. Using the difference-in-differences method and the panel data of more than 3 million firms in China from 2008 to 2016, we find that environmental supervision improves firms' energy efficiency. This finding is validated by robustness tests and the difference-in-differences method combined with propensity score matching. The EPAT policy has varying effects on firms based on their location and size. A mechanism analysis shows that the EPAT policy improves firms' energy efficiency mainly by incentivizing them to adopt new technologies and transforming their modes of production. These findings can provide novel microscopic evidence on environmental supervision and energy efficiency and offer clues for the improvement of environmental enforcement in developing countries.

Impact of energy efficiency, technology innovation, institutional quality, and trade openness on greenhouse gas emissions in ten Asian economies

Despite the fact that Asian economies have experienced robust economic growth in recent decades, rising pollution emissions have raised worries among policymakers about the long-term stability of this output growth. Knowing this fact, the present study attempts to empirically analyze the impact of some important factors, e.g., energy efficiency, technology innovations, trade openness, and institutional quality, on environment in 10 Asian economies over the period 1995-2018. Taking into account the slope heterogeneity and cross-sectional dependence present in the data, Westerlund and Edgerton (2008) and Banerjee and Carrion-i-Silvestre (2017) cointegration techniques and cross-sectionally augmented autoregressive distributed lag model (CS-ARDL) estimation are applied. For robust analysis, augmented mean group (AMG) and common correlated effects mean group (CCEMG) are also employed in the study. The empirical findings provided by selected variables reveal that both trade openness and institutional quality have detrimental impact, whereas energy efficiency and technology innovations have favorable impact on environmental quality in the selected economies. Empirical findings are robust to various policy recommendations. To create a sustainable future environment, Asian economies should focus on the improvement of their institutions quality and increase investments in technology innovations. The Asian countries must encourage trade-related environmental regulations and energy efficiency policies for better and sustainable environmental quality.

How do vertical fiscal imbalances affect energy efficiency? The role of government spending on science and technology

How to improve energy efficiency is a practical issue of common concern around the world. In China, vertical fiscal imbalances (VFIs) generated under the existing fiscal system may have a significant impact on energy efficiency through government spending on science and technology (S&T). However, this potential relationship has not been explored in the literature. In this work, we aim to address this gap. Using Chinese provincial panel data from 2001 to 2017, this study empirically examines the relationship between VFIs and energy efficiency through a mediation model. The results show that VFIs greatly suppress energy efficiency. We further find that VFIs indirectly affect energy efficiency by reducing government spending on S&T. The results show significant regional heterogeneity. The intermediary role of government S&T expenditure is more significant in inland areas than in coastal areas. Therefore, to improve energy efficiency and achieve sustainable development, the Chinese government should focus on innovative reform of the existing fiscal system and reduce VFIs. In addition, the government should focus on fiscal spending in the field of S&T to promote technological innovation to guarantee the improvement of energy efficiency. Inland areas should pay particular attention to this issue.

Halophilic CO2-fixing microbial community as biocatalyst improves the energy efficiency of the microbial electrosynthesis process

Using saline electrolytes in combination with halophilic CO₂-fixing lithotrophic microbial catalysts has been envisioned as a promising strategy to develop an energy-efficient microbial electrosynthesis (MES) process for CO₂ utilization. Here, an enriched marine CO₂-fixing lithotrophic microbial community dominated by Vibrio and Clostridium spp. was tested for MES of organic acids from CO₂. At an applied E_cathode of -1V (vs Ag/AgCl) with 3.5 % salinity (78 mScm^-1), it produced 379 ± 53 mg/L (6.31 ± 0.89 mM) acetic acid and 187 ± 43 mg/L (4.05 ± 0.94 mM) formic acid at 2.1 ± 0.30 and 1.35 ± 0.31 mM day^-1, respectively production rates. Most electrons were recovered in acetate (68.3 ± 3 %), formate (9.6 ± 1.2 %) besides hydrogen (11 ± 1.4 %) and biomass (8.9 ± 1.65 %). Notably, the bioproduction of organic acids occurred at a high energetic efficiency (EE) of ∼ 46 % and low E_cell of 2.3 V in saline conditions compared to the commonly used non-saline electrolytes (0.5-1 mScm^-1) in the reported MES studies with CO₂ (E_cell: >2.5 V and EE: <34 %).

Digital economy and industrial energy efficiency performance: evidence from the city of the Yangtze River Delta in China

Industry dominates energy consumption and carbon emissions in China, and industrial energy efficiency is critical for the achievement of energy transformation and carbon emission reduction. With the rapid development of the digital economy, its impact on energy efficiency is gradually emerging, and it is necessary to clarify the influencing mechanism on industrial energy efficiency. Based on the panel data of industrial sectors in 41 cities in the Yangtze River Delta from 2011 to 2019, the main objectives of this study are to more accurately measure the industrial total factor energy efficiency in each city by using the Super-Dynamic-SBM model. It analyses the influence mechanism of the digital economy and other influencing factors on industrial total factor energy efficiency with different methods. The research results indicate that, first, the total factor energy efficiency of the industrial sector in the Yangtze River Delta urban agglomeration generally showed a steady upward trend. Second, the digital economy and environmental regulation play a significant role in promoting total factor energy efficiency. In addition, industrial energy efficiency and the digital economy show an inverted "U" shaped relationship. With the improvement of the digital economy, its marginal contribution to total factor energy efficiency gradually weakens. Finally, technological progress is an important transmission channel for the impact of the digital economy on total factor energy efficiency.

Influence of air quality ranking on China's energy efficiency: spatial difference-in-differences model with multiple time periods

Exploring the impact of air quality ranking on energy efficiency and its spatial spillovers will help improve the pollution and carbon reduction effects of environmental governance policies. Based on the panel data of 285 cities at or above prefecture level in China during 2009-2019, this study pioneers in adopting difference-in-differences (DID) model with multiple time periods, spatial DID (SDID) model with multiple time periods, and mediating effect to explore the direct influence of ranking on China's energy efficiency, as well as its spatial effect and influence mechanism. Results show that air quality ranking is of significant positive impact on energy efficiency, proved by parallel trend hypothesis, placebo control, and policy heterogeneity. With spatial effect considered, such impact still exists, and ranking of the experimental group has significant positive spatial spillover effect on efficiency of the control group, meaning the ranking also promotes the efficiency of nearby cities in control groups via spatial spillover effect. In addition, air quality ranking greatly elevates energy efficiency via industrial structure and technological innovation, the mechanism of which is of significant positive spatial spillover effect. Based on the above results, some policy recommendations on environmental competition policy, industrial structure adjustment, and low-carbon applicable technology promotion were proposed to promote the energy efficiency of China.

Energy efficiency of drinking water treatment plants: A methodological approach for its ranking

Drinking water treatment systems (DWTSs) are energy intensive facilities, and are an example of the water-energy nexus. Benchmarking energy efficiency is a valuable tool for improving the economic and environmental performance of such facilities. Data envelopment analysis (DEA) is typically used to assess efficiency, allocating flexible weights (FSW) to variables that maximise energy efficiency scores for each DWTS (DEA-FSW). It means that different conditions are applied to each DWTS. Moreover, the DEA-FSW approach has finite discriminatory power which limits cross-unit comparison of energy efficiency hindering the benchmarking of DWTSs. To overcome these limitations, our study explored the effect of estimating the energy efficiency scores of DWTSs by allocating common sets of weights (CSW) within DEA (DEA-CSW). This approach was applied empirically on a sample of 146 DWTSs. Evaluated DWTSs had poor energetic performance based on both DEA-FSW and DEA-CSW estimates (low energy efficiency scores: 0.329 and 0.163, respectively). Even in the optimistic scenario, the average energy efficiency score was low (0.220), with potential electricity savings of 78 % by DWTPs when energy efficient. Unlike DEA-FSW, DEA-CSW allowed energy efficient DWTSs to be distinguished from the 146 facilities. Significant differences in the weights allocated to electricity and pollutants removed from raw water were reported for both approaches, and contributed to diverging energy efficiency scores. In conclusion, this study demonstrated the relevance of using suitable methods to generate comparable results for water companies, allowing the energy performance of DWTSs to be objectively evaluated for benchmarking purposes.

Assessing the determinants of renewable energy and energy efficiency on technological innovation: Role of human capital development and investement

With rising global production and population, the globalized globe has also seen severe environmental damage. This is why renewable energy sources are important for the planet's future and human progress. In order to fight climate change and decrease emissions, promoting energy efficiency is one of the most valuable strategies. Trade patterns across borders, however, have significantly evolved. This analysis provides new evidence regarding the influence of technological progress, and more specifically, industrial innovation, on the OECD countries' international competitiveness. This article aims to analyse the effects of international commerce, FDI, and human capital on the development of renewable energy sources, energy efficiency measures, and cutting-edge technologies. In this analysis, we look at how different variables, including GDP per capita, trade, FDI, human capital, and urbanization, affect one another. To conduct the analysis, researchers used a pool of annual time series data from 2000 to 2019 for OECD economies. The long-term relationship between the variables is estimated using the AMG estimation, Cup-FM, and Cup-BC test. AMG estimation, Cup-FM estimation, and Cup-BC estimation were all used, providing valid results for the investigation. Research shows that energy efficiency, renewable energy, and technological innovation are negatively affected by FDI and urbanization but positively affected by GDP per capita, trade, and human capital. There is no statistically significant effect of human capital on the dependent variables. The estimated results also provide important policy consequences for the chosen and the other emerging economies in creating an adequate route ahead to sustainable development.

Modeling the Impact of Fiscal Decentralization on Energy Poverty: Do Energy Efficiency and Technological Innovation Matter?

As an important factor affecting economic and social development, energy poverty (EP) has received widespread concern, and many countries have actively proposed policies to eliminate energy poverty. The purpose of this paper is to clarify the current situation of energy poverty in China, explore the factors that affect energy poverty, find sustainable and effective approaches to alleviate energy poverty, and provide empirical evidence for eliminating energy poverty. This research investigates the effect of fiscal decentralization (FD), industrial structure upgrading (ISU), energy efficiency (EE), and technological innovation (TI), as well as urbanization (URB) on energy poverty using a balanced dataset of 30 provinces in China from 2004 to 2017. The empirical outcomes revealed that fiscal decentralization, industrial upgrading, energy efficiency, and technological innovation significantly reduce energy poverty. Moreover, urbanization is positively and significantly correlated with energy poverty. The outcomes further revealed that fiscal decentralization significantly increases the residents' access to clean energy and drives energy management agencies and infrastructure. In addition, the heterogeneity analysis results indicate that the effect of fiscal decentralization in reducing energy poverty is greater in regions with high economic development. Finally, mediation analysis denotes that fiscal decentralization indirectly reduces energy poverty by promoting technological innovation and energy efficiency. Finally, based on the results, policy suggestions for eradicating energy poverty are proposed from the perspective of implementing targeted energy alleviation policies reasonably dividing the rights and responsibilities of local and central governments and encouraging scientific and technological innovation.

Ambient Electromagnetic Radiation as a Predictor of Honey Bee (Apis mellifera) Traffic in Linear and Non-Linear Regression: Numerical Stability, Physical Time and Energy Efficiency

Since bee traffic is a contributing factor to hive health and electromagnetic radiation has a growing presence in the urban milieu, we investigate ambient electromagnetic radiation as a predictor of bee traffic in the hive's vicinity in an urban environment. To that end, we built two multi-sensor stations and deployed them for four and a half months at a private apiary in Logan, UT, USA. to record ambient weather and electromagnetic radiation. We placed two non-invasive video loggers on two hives at the apiary to extract omnidirectional bee motion counts from videos. The time-aligned datasets were used to evaluate 200 linear and 3,703,200 non-linear (random forest and support vector machine) regressors to predict bee motion counts from time, weather, and electromagnetic radiation. In all regressors, electromagnetic radiation was as good a predictor of traffic as weather. Both weather and electromagnetic radiation were better predictors than time. On the 13,412 time-aligned weather, electromagnetic radiation, and bee traffic records, random forest regressors had higher maximum R2 scores and resulted in more energy efficient parameterized grid searches. Both types of regressors were numerically stable.

Existing Building Renovation: A Review of Barriers to Economic and Environmental Benefits

The renovation of old buildings provides an important approach to energy saving and emission reduction with low economic costs. The current important issue remains how to determine the optimal cost-effective technical path for a specific project, although there are a large number of retrofit technologies to choose from. Based on a systematic perspective, this paper conducts a quantitative analysis of the environmental and economic benefits of building renovation, and compares and studies the role and challenges of different countries in the process of recycling waste building materials and technological innovation to extend the life of buildings. Through the use of VOSviewer, 1402 papers from the Web of Science core collection database were visualized, analyzed, and deduced, and the research context and development trends of architectural renovation were sorted out and presented. Finally, this article discusses the status and application process of existing building renovation technologies, including the current obstacles that need to be resolved. It puts forward a vision for the future development of building renovation, emphasizing that top-down guidance is essential to future carbon neutral goals.

The Low-Carbon Policy and Urban Green Total Factor Energy Efficiency: Evidence from a Spatial Difference-in-Difference Method

In the post-epidemic background of the low-carbon economy and sustainable development, the low-carbon city pilot program (LCCP) is viewed as a practical method of improving energy efficiency. This study explores the spatial spillover effects of LCCP on green total factor energy efficiency (GTFEE) by developing a spatial difference-in-difference (SDID) model. Furthermore, we apply the mediating effects model to verify whether the rational allocation of resources is an influential channel for the spillover effect of LCCP policies. The results indicate that the LCCP policy has not only improved the local GTFEE by approximately 1.8%, but it also has a profound impact on the surrounding regions as well, which is about 76.5% that of the pilot cities. Additionally, the estimated results of the mediating effect model indicate that optimizing labor force and capital allocations are two essential channels through which the LCCP policy may contribute to improving regional cities' GTFEE. Accordingly, the pilot cities should establish specific measures for rational resource allocation and promote the spatial spillover model of sustainable development.

A comprehensive appraisal on status and management of remediation of DBPs by TiO2 based-photocatalysts: Insights of technology, performance and energy efficiency

Disinfection has been acknowledged as an inevitable technique in water treatment. However, an inadvertent consequence of generation of carcinogenic and mutagenic disinfection byproducts (DBPs) is associated with the reaction of disinfectants and natural organic matter (NOM) present in water. More than 700 DBPs have been identified in drinking water. The conventional processes carried out in WTPs do not optimally ensure NOM elimination, which evokes the need for the incorporation of other processes. In this context, several physicochemical and advanced oxidation processes (AOP), such as adsorption, membrane techniques, photocatalysis, etc., have been studied for the removal of NOM from water. Photocatalysis using semiconductors has been one of the most proficient technologies, which utilizes light energy for the degradation of recalcitrant organics. The present study aims to provide a comprehensive appraisal on the performance of titanium dioxide (TiO₂) based photocatalysts in the remediation of DBPs concerning the efficacy and energy requirements of the system. Furthermore, the effect of process parameters, such as pH, catalyst dose, light intensity, etc. on the efficacy of the process was also studied. It was observed that conventional P25-TiO₂ powders were efficient in the degradation of dissolved organic carbon (DOC) (up to 90%). However, low photocatalytic activity under visible light activation is one of its significant downsides. Several modifications on the catalyst surface in many studies exhibited advantages, such as high humic acid (HA) degradation under visible light. Furthermore, doped TiO₂ catalysts have shown high total organic carbon (TOC) degradation. The photocatalytic systems have achieved a better decrease in trihalomethane formation potential (THMFP) when compared to haloacetic acid formation potential (HAAFP). The energy requirements of the photocatalytic systems are determined by electrical energy per order (EE/O), which has been observed to be lesser for doped TiO₂ and engineered TiO₂ catalysts when compared with P25-TiO₂ powders. Carbon, iron, silver, etc., based catalysts can be a promising alternative to TiO₂-based photocatalysts for the degradation of NOM, although further research is required in this direction. The present review provides critical highlights on the uses, opportunities, and challenges of TiO₂-based photocatalytic techniques for the management of DBPs and their precursors pertaining to an emerging area of water treatment.

Can River Chief System Policy Improve Enterprises' Energy Efficiency? Evidence from China

The river chief system (RCS) is an autonomous environmental policy implemented by local governments in China that incorporates environmental responsibilities into the performance evaluation. Although existing literature suggests that RCS can reduce water pollution, the impact of RCS on energy efficiency has not been assessed. Therefore, this paper compiles data on industrial enterprises and industrial pollution in China from 2003 to 2013 and empirically examines the impact of RCS on green total factor energy efficiency (GTFEE) by using a multiple difference-in-difference approach. The results show that RCS significantly enhances firms' GTFEE, and a series of tests confirm the robustness of the findings. Second, we further explore how RCS affects GTFEE, the mechanism tests conclude that the RCS improves GTFEE mainly through optimizing energy structure and promoting technological innovation. Third, compared with small firms, exporters, and firms in non-heavy polluting industries, the RCS has a greater effect on improving the GTFEE of large firms, non-exporters, and firms in heavily polluting industries. This study provides new and novel ideas for emerging countries to improve environmental policies and achieve sustainable development.

Evaluation of Growth Responses of Lettuce and Energy Efficiency of the Substrate and Smart Hydroponics Cropping System

Smart sensing devices enabled hydroponics, a concept of vertical farming that involves soilless technology that increases green area. Although the cultivation medium is water, hydroponic cultivation uses 13 ± 10 times less water and gives 10 ± 5 times better quality products compared with those obtained through the substrate cultivation medium. The use of smart sensing devices helps in continuous real-time monitoring of the nutrient requirements and the environmental conditions required by the crop selected for cultivation. This, in turn, helps in enhanced year-round agricultural production. In this study, lettuce, a leafy crop, is cultivated with the Nutrient Film Technique (NFT) setup of hydroponics, and the growth results are compared with cultivation in a substrate medium. The leaf growth was analyzed in terms of cultivation cycle, leaf length, leaf perimeter, and leaf count in both cultivation methods, where hydroponics outperformed substrate cultivation. The results of the 'AquaCrop simulator also showed similar results, not only qualitatively and quantitatively, but also in terms of sustainable growth and year-round production. The energy consumption of both the cultivation methods is compared, and it is found that hydroponics consumes 70 ± 11 times more energy compared to substrate cultivation. Finally, it is concluded that smart sensing devices form the backbone of precision agriculture, thereby multiplying crop yield by real-time monitoring of the agronomical variables.

Simulations for double dividend of carbon tax and improved energy efficiency in the transportation industry

The Chinese visional goal of achieving the "carbon peak" and "carbon neutrality" puts forward higher requirements for low-carbon development in the transportation industry. Seeking appropriate mitigation strategies to develop low-carbon transportation has been an important part of low-carbon economic development. This study develops a CGE model to analyze the impact of carbon-tax implementation on the transportation industry. It designs four carbon tax-recycling scenarios and simulates for double dividend of carbon tax policy. Then, it designs three scenarios including improved energy efficiency and a carbon tax to explore appropriate mitigation strategies combination. The carbon tax will reduce carbon emissions but it will also reduce sectoral outputs. However, carbon tax recycling can alleviate the negative impact on sectoral outputs, meanwhile achieving reducing carbon emissions. The energy rebound effect brought by improved energy efficiency will greatly reduce the carbon emissions reduction effect, but the carbon tax can promote the awareness of emission reduction of consumers and inhibit the energy rebound effect in the transportation industry. Therefore, at the same time of improved energy efficiency, carbon tax policies should be timely formulated to better promote the sustainable development of the varied transport sectors.

How to improve total factor energy efficiency under climate change: does export sophistication matter?

Climate change has a profound impact on human survival and development. Climate change is an energy and economic issue, which should be driven by technology. Total factor energy efficiency (TFEE) improvement is undoubtedly a breakthrough in solving energy problems. In this paper, the fixed effect model, impulse response function, and threshold regression model are used to test the complex relationship between export sophistication and TFEE. The results reveal that export sophistication improvement leads to higher TFEE. The impulse response results verify the existence of a phased and positive correlation between export sophistication and TFEE. Finally, the relationship between export sophistication and TFEE significantly varied across different threshold levels of regional corruption score, economic development, and openness. This article led the foundation for supporting China's export sophistication promotion strategy and also provides a reference for energy efficiency improvement and energy crisis response in the post-pandemic era.

A comparison of nitrogen removal systems through cost-coupled life cycle assessment and energy efficiency analysis

The global water crisis reflects the necessity of exploring the best approaches for the water supply. Therefore, for the first time, the current study compares nitrogen removal systems (NRSs) from life cycle assessment (LCA), economic, kinetic, thermodynamic, and synergistic perspectives. The assessed systems were sequential batch reactor (SBR), oxic/anoxic (OA), and oxic/anaerobic/oxic (OAO) bioreactors. Among all, the SBR configuration showed the best efficiency (98.74 %) for nitrogen removal. The environmental impacts notably presented by marine + freshwater ecotoxicity (53.76 %), and climate change categories (16.39 %), significantly because of metal emissions. Non-renewable sources supplied 95 % of total energy demand. The operation of NRSs showed the most impact on human health (63.67 %) through CH₄ and CO₂ emissions. The total costs significantly belonged to the construction (<86.37 %) > amortization> operation. The influent COD illustrated the most role in environmental burdens (16.44 %) based on the sensitivity analysis. The removal reaction was endothermic, physical, non-spontaneous, and followed a pseudo-second-order kinetic model (R² > 0.98). The chemical exergy provided the major portion of the total calculated exergy (83 %). The exergetic efficiency of the system was 69 %, which was predominantly supplied by biogas (∼50.75 %). Accordingly, this study can present a stepwise guideline for further related investigations.

Analysis of spatiotemporal difference and driving factors of green total factor energy efficiency in RCEP members: insights from SBM-GML and Tobit models

It is vital to determine the changing spatiotemporal patterns and driving factors of green total factor energy efficiency (GTFEE) in order to design scientific policies to promote energy efficiency in the Regional Comprehensive Economic Partnership (RCEP) region. From 2010 to 2019, the super-efficient SBM model and the global Malmquist-Luenberger index provide an appropriate framework for measuring the spatiotemporal evolution of GTFEE and the dynamics of energy productivity in RCEP countries. With the coefficient of variation and the Thiel index, an extensive view of the spatiotemporal variance in GTFEE is offered, taking regional heterogeneity into account. Furthermore, the Tobit model is introduced to investigate the factors influencing the GTFEE of RCEP members, which may address the restricted values of the dependent variable when compared to the least squares regression model. Findings suggest that (1) The GTFEE of RCEP members tends to be low and unevenly distributed spatially and temporally, with much room for improvement. (2) The energy productivity index fluctuates strongly, and the improvement primarily comes from technological progress. (3) The Non-ASEAN region possesses higher GTFEE than the ASEAN region, albeit regional variations are diminishing. (4) In terms of the major factors influencing the regional GTFEE, the non-ASEAN region looks to be distinct from the ASEAN region. The findings shed light on the trends and influencing factors of GTFEE in RCEP and serve as a resource for international energy cooperation and sustainable development.

An analysis of energy efficiency of the Pearl River Delta of China based on super-efficiency SBM model and Malmquist index

With the rapid growth rate of China's economy, the extensive pattern of economic growth of "high energy consumption and low output" has magnified the constraints of energy issues on China's economic development and environmental protection, which highlights the importance of improving energy efficiency. As one of the three major economic zones in China, the Pearl River Delta region also faces high energy consumption and pollution emissions while developing at a high speed. Hence, improving the energy efficiency of the Pearl River Delta region is needed, as it not only is conducive to driving its development of the surrounding green economy, but also promotes the subsequent sustainable economic development. However, there are few literatures on the calculation and analysis of energy efficiency in the Pearl River Delta, and lacking a systematic analysis of input-output index system of energy efficiency measurement. Therefore, this paper calculates the energy efficiencies and the Malmquist indexes based on the panel data of the nine cities in the Pearl River Delta from 2005 to 2019 through super-efficiency SBM model and Malmquist index method by using MAXDEA and MATLAB software. The result illustrates that all regions in the Pearl River Delta except Guangzhou and Shenzhen show obvious energy inefficiency, which is mainly caused by the imbalance between technical efficiency and scale efficiency. Based on the calculation results, this paper gives some relevant suggestions for the further approach of energy reform in the Pearl River Delta according to the calculation results.

The impact and mechanism of high-speed rail on energy efficiency: an empirical analysis based on 285 cities of China

Improving energy efficiency is an important measure of environmental governance. At present, studies on the impact of high-speed rail on energy efficiency need to be further studied. This paper constructs panel data of 285 cities at prefecture-level and above in China from 2003 to 2017, and uses the difference-in-difference (DID) to study the impact of high-speed railway on urban energy efficiency. Based on the theories of "factor flow," "knowledge spillover," and "center-periphery," this paper discusses the influence mechanism and heterogeneity of high-speed railway on energy efficiency. The empirical results show that high-speed railway can significantly improve energy efficiency, and the conclusion is still valid after parallel trend test, propensity score matching and difference-in-difference (PSM-DID) test, and instrumental variable method. The results remained true after a series of robustness tests. Mechanism analysis shows that high-speed railway can improve energy efficiency by promoting industrial structure upgrading, technological innovation, and market integration. Analysis of heterogeneity shows that the promotion effect of high-speed railway on energy efficiency is greater in central and western cities and core cities. This study provides useful enlightenment for optimizing China's high-speed rail construction planning and seizing the opportunity of high-speed rail development to improve energy efficiency.

Byproducts of Globe Artichoke and Cauliflower Production as a New Source of Bioactive Compounds in the Green Economy Perspective: An NMR Study

The recovery of bioactive compounds from crop byproducts leads to a new perspective way of waste reutilization as a part of the circular economy. The present study aimed at an exhaustive metabolite profile characterization of globe artichoke and cauliflower byproducts (leaves, stalks, and florets for cauliflower only) as a prerequisite for their valorization and future implementations. The metabolite profile of aqueous and organic extracts of byproducts was analyzed using the NMR-based metabolomics approach. Free amino acids, organic acids, sugars, polyols, polyphenols, amines, glucosinolates, fatty acids, phospho- and galactolipids, sterols, and sesquiterpene lactones were identified and quantified. In particular, globe artichoke byproducts are a source of health-beneficial compounds including chiro-inositol (up to 10.1 mg/g), scyllo-inositol (up to 1.8 mg/g), sesquiterpene lactones (cynaropicrin, grosheimin, dehydrocynaropicrin, up to 45.5 mg/g in total), inulins, and chlorogenic acid (up to 7.5 mg/g), whereas cauliflower byproducts enclose bioactive sulfur-containing compounds S-methyl-L-cysteine S-oxide (methiin, up to 20.7 mg/g) and glucosinolates. A variable content of all metabolites was observed depending on the crop type (globe artichoke vs. cauliflower) and the plant part (leaves vs. stalks). The results here reported can be potentially used in different ways, including the formulation of new plant biostimulants and food supplements.

Green Economy and Waste Management as Determinants of Modeling Green Capital of Districts in Poland in 2010-2020

Waste management must comply with the principle of sustainable development. A green economy is one of the paths to sustainable development and response to environmental problems. Waste should be a raw material that can be reused, processed, or turned into energy. The aim of the article is to assess the relationship and present the concept of zero waste and green economy, and to show selected framework conditions for their development in the county. To study the formation of phenomena depending on the location of a given object in the socio-economic space, a synthetic measure, the similarity matrix, the Gini coefficient was used. The analysis took into account features describing the condition of the natural environment, links between the natural environment, economy and society, the quality of life of the population, economic policy, and instruments influencing the economy, society and the environment. Empirical data were obtained from the local database of the Central Statistical Office for the years 2010-2020. The obtained results indicate the existence of dependencies in the development of a green economy and waste management in the region. The synthetic measure of waste management is from 0.43 to 0.61 in 2010, from 0.39 to 0.55 in 2020; green economy from 0.42 to 0.55 in 2010 and from 0.43 to 0.56 in 2020. Waste management is based on multidimensional waste management, taking into account economic, ecological and social aspects. Economic activity is related to the degradation of the natural environment. The green economy should assume the elimination of waste and environmental threats and the preservation of their value. The green economy is becoming a factor inducing structural changes in the economy and social life, helping in the most effective, sustainable and efficient use of limited resources. In the literature on the subject, this type of research is carried out at the level of regions or voivodeships. The authors use their own sets of indicators or their own indicators aggregated according to the available data at the poviat level. The obtained results can be an important source of information for local government authorities about disproportions between units.

Analysis on the Influence of Industrial Structure on Energy Efficiency in China: Based on the Spatial Econometric Model

Compared with other developed countries, China's energy efficiency level is not optimal, but it has indeed made remarkable achievements in its long-term development, mainly due to efforts targeting the adjustment of industrial structure. This research, therefore, uses a spatial econometric model to study the energy efficiency of 30 provinces in China with data from the panel from 2004 to 2019, and studies the impact of industrial structure on energy efficiency from the overall sample, for different time periods and across the three regional scales of eastern, central and western regions. The following conclusions are drawn from the empirical analysis. (1) China's energy efficiency indicators have significant geographic spatial correlation and regional spatial structure differences. (2) In the full sample condition, the industrial structure has a positive impact on the energy efficiency of China's provinces, but it also shows a significant negative spatial spillover effect. (3) Industrial structure was positively correlated with energy efficiency from 2004 to 2011. (4) The industrial structure in the east promotes energy efficiency, while the industrial structure in the central and western regions inhibits energy efficiency improvement. (5) Government intervention and scientific and technological innovation have had a spatial impact on energy efficiency in China's provinces, while marketization and the average income of residents have had no significant impact.

Secrecy Energy Efficiency Enhancement in UAV-Assisted MEC System

A secrecy energy efficiency optimization scheme for a multifunctional unmanned aerial vehicle (UAV) assisted mobile edge computing system is proposed to solve the computing power and security issues in the Internet-of-Things scenario. The UAV can switch roles between a computing UAV and jamming UAV based on the channel conditions. To ensure the security of the content and the system energy efficiency in the process of offloading computing tasks, the UAV trajectory, uplink transmit power, user scheduling, and offload task are jointly optimized, and an updated-rate assisted block coordinate descent (BCD) algorithm is used. Simulation results show that this scheme efficiently improves the secrecy performance and energy efficiency of the system. Compared with the benchmark scheme, the secrecy energy efficiency of the scheme is improved by 38.5%.

The underlying drivers of energy efficiency: a spatial econometric analysis

It is theoretical and practical to investigate the causes and effects of energy efficiency. However, few empirical studies have been conducted to examine the potential underlying drivers of energy efficiency from a spatial perspective. In light of this, we combined the data envelopment analysis and spatial econometric analysis to explore the driving factors of energy efficiency. The results show that China's energy efficiency shows significant characteristics of regional disparity and spatial agglomeration; that is, high energy efficiency has presented a benefit agglomeration, while low energy efficiency has presented a disadvantage agglomeration. The empirical results indicate that technological progress, trade openness, and foreign direct investment have effectively improved energy efficiency, while energy structure and industrial structure adversely affect energy efficiency. Furthermore, technological progress, trade openness, energy structure, foreign direct investment, and industrial structure exert different influences on energy efficiency, but their potential underlying mechanisms vary essentially across regions. Thus, using a spatial econometric model allowing for spatial dependence in analyzing drivers of energy efficiency is urgent and necessary for promulgating energy policies.

Impact of human capital on the green economy: empirical evidence from 30 Chinese provinces

In China, exploring the relationship between human capital and green economy in the context of economic transformation can promote the construction of an ecological civilization and high-quality economic development. This paper is dedicated to assessing the impact of human capital stock, human capital structure, and the difference between the two on China's green economy. Using the super-efficiency slack-based measure (SBM) model, this paper evaluated the green total factor productivity (GTFP) of 30 Chinese provinces to assess the greenness of its economy and analyzed its spatiotemporal evolution from 2000 to 2017. A spatial error model (SEM) was established to explore the impact of human capital on green economy. The results show that (1) the GTFP of China increased continuously from 0.219 to 0.457, showing a regional spatial differentiation of "eastern region > central region > western region." The spatial gaps of the green economy in the east-west and north-south directions are narrowing. (2) Moran's I index and Moran's I scatter plot indicate a significant spatial correlation between human capital and China's green economy. The local spatial correlation between human capital and green economy is mainly characterized by "high-high" and "low-low" types of agglomeration. (3) The effects of human capital stock and human capital structure on green economy were both positive, with coefficients of 0.0005 and 0.1601, respectively, but the effects of human capital structure were not significant. (4) The results of regional regression show that the difference between the human capital impact coefficients on green economy in the eastern and midwestern regions is small. The impact of human capital stock and human capital structure on green economy is consistent with the national level results. It can be preliminarily concluded that the development of China's green economy relied more on improving the human capital stock than on the improvement of the human capital structure. This study further enriches the literature on the green economy and provides information that can support government policy-making.

Assessing the impact of R&D Investments, government subsidies on energy efficiency: empirical analysis from the Chinese listed firms

China's "Made in China (2025)" strategic plan aims to increase the industrial sector's ability to innovate independently. Cleaner production and green technology will also be used to build green industrial systems. To help achieve these goals, the Chinese government has implemented research and development (R&D) preferential policies. Over the years 2010-2020, this article examines how government subsidies and R&D spending will affect China's energy-intensive enterprises' energy efficiency using the CS-ARDL approach. It also evaluates the effectiveness of economic growth, urbanization, and financial resources on energy efficiency. The outcome reveals that R&D expenditures and economic growth contribute to energy efficiency. Likewise, the findings of urbanization, financial resources, and government subsidies are inversely associated with energy efficiency. Moreover, the panel causality test results show the bi-directional association between urbanization and energy efficiency, government subsidies and energy efficiency, and economic growth and energy efficiency. Likewise, the one-way causal association from R&D expenditures to energy efficiency and from financial resources to energy efficiency. The findings suggest the imperative policies to boost the level of energy efficiency.